Animal Husbandry I.
Komlósi, István
Stündl, László
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Animal Husbandry I.
írta Komlósi, István és Stündl, László
TÁMOP-4.1.2.A/1-11/1-2011-0009
University of Debrecen, Service Sciences Methodology Centre
Debrecen, 2013.
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Tartalom
Tárgymutató ....................................................................................................................................... 1
1. 1. Breeding objectives ................................................................................................................... 2
1. Setting a breeding goal in dairy cattle ................................................................................... 3
2. Breeding objective in dual purpose cattle breeds .................................................................. 6
3. Setting a breeding goal in beef cattle .................................................................................... 7
4. Potential new traits to include in selection programs ............................................................ 9
5. PIG ...................................................................................................................................... 10
6. Sheep ................................................................................................................................... 14
7. Questions ............................................................................................................................ 19
8. References and literature suggested ................................................................................... 19
2. 2. PERFORMANCE RECORDING ............................................................................................. 21
1. Questions ............................................................................................................................. 27
2. Lierature cited and suggested .............................................................................................. 28
3. 3. estimation of Genetic parameters ............................................................................................. 29
1. Questions ............................................................................................................................. 40
2. Suggested literature ............................................................................................................. 40
4. 4. breeding value evaluation – BLUP ........................................................................................... 41
1. SELECTION AND SELECTION RESPONSE .................................................................. 53
2. Questions ............................................................................................................................. 65
3. Suggested literature ............................................................................................................. 65
5. 5. Quantitative traits of the Poultry ............................................................................................... 66
1. Questions ............................................................................................................................. 67
2. Literature consulted ............................................................................................................. 67
6. 6. QUANTITATIVE POULTRY TRAITS. PARAMETERS AND HERITABILITY ................ 68
1. Questions ............................................................................................................................. 73
2. Literature cited .................................................................................................................... 73
7. 7. Inbreeding and crossbreeding ................................................................................................... 74
1. Questions ............................................................................................................................. 79
2. Literature ............................................................................................................................. 79
8. 8. GENOTYPE-GENOTYPE INTERACTION ........................................................................... 80
1. Questions ............................................................................................................................. 81
2. Literature ............................................................................................................................. 82
9. 9. Marker assisted selection in poultry breeding ........................................................................... 83
1. Questions ............................................................................................................................. 87
2. Literature cited .................................................................................................................... 87
10. 10. BREEDING FOR RESISTANCE ........................................................................................ 89
1. Questions ............................................................................................................................. 91
2. Literature cited .................................................................................................................... 91
11. 11. Animal behaviour, animal welfare ........................................................................................ 92
1. Questions: ......................................................................................................................... 102
2. Annex 1. ............................................................................................................................ 102
12. 12. Feeds - nutritional value and use ........................................................................................ 104
1. Nutritional Requirements of Poultry ................................................................................ 104
2. Energy in Poultry Diets ..................................................................................................... 104
3. Energy feeds ...................................................................................................................... 105
4. Protein in poultry diets ...................................................................................................... 106
5. Minerals ............................................................................................................................ 108
6. Vitamins ............................................................................................................................ 108
7. Water ................................................................................................................................. 108
8. Feed formulation – formulated feeds ................................................................................ 109
9. Factors affecting the quality .............................................................................................. 109
10. Questions: ........................................................................................................................ 110
11. Annex 1. .......................................................................................................................... 110
12. Annex 2. .......................................................................................................................... 111
13. Annex 3. .......................................................................................................................... 112
13. 13. Nutrition by genotype (species/variety/hybrid) .................................................................. 114
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Animal Husbandry I.
1. Nutrient requirements of meat chickens (broilers) ............................................................
2. Nutrient requirements of egg laying chickens/hens ..........................................................
3. Feeding chickens/hens ......................................................................................................
4. Feeding Turkeys ................................................................................................................
5. Feeding Geese ...................................................................................................................
6. Feeding Ducks ...................................................................................................................
7. Questions: .........................................................................................................................
14. 14. Poultry keeping technologies ..............................................................................................
1. Key elements of the keeping technology ..........................................................................
2. Management operations in poultry keeping ......................................................................
3. Egg and meat production technologies .............................................................................
4. Turkey farming technologies ............................................................................................
5. Goose farming technologies ..............................................................................................
6. Duck farming technologies ...............................................................................................
7. Questions: .........................................................................................................................
15. 15. Processing technologies .....................................................................................................
1. Main steps in the processing plants ...................................................................................
2. Raw & processed poultry products ...................................................................................
3. Environmental issues connected to processing ................................................................
4. Product quality ..................................................................................................................
5. Egg Quality .......................................................................................................................
6. Questions: .........................................................................................................................
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Az ábrák listája
1.1. Fig. 1.1. Holstein-frieasian cow ................................................................................................... 4
1.2. Fig. 1.2. Hungarian Simmental. ................................................................................................... 7
1.3. Fig. 1.3. A Charolais bull in Hódmezővásárhely in 2009. ........................................................... 9
1.4. Fig. 1.4. Limousine breed. ......................................................................................................... 10
1.5. Fig. 1.5. Landrace. ..................................................................................................................... 10
1.6. >Fig. 1.6. Large White pig. ........................................................................................................ 11
1.7. Fig. 1.7. The Pietrain pig. .......................................................................................................... 12
1.8. Fig. 1.8. The Hampshire breed. ................................................................................................. 12
1.9. Fig. 1.9. Duroc pig breed. .......................................................................................................... 12
1.10. Fig. 1.10. The breeding pyramid .............................................................................................. 13
1.11. Fig. 1.11. Hungarian Merino. .................................................................................................. 18
1.12. Fig. 1.12. Suffolk sheep. .......................................................................................................... 18
1.13. Fig. 1.13. The Lacaune breed. ................................................................................................. 18
2.1. Fig. 2.1. The organisational structure of the ICAR .................................................................... 21
2.2. Fig.2.2. Member states of the ICAR .......................................................................................... 22
2.3. Fig. 2.3. Tag and electronic devices used for identification. ..................................................... 22
2.4. Fig. 2.4. The visual assessment of stature and chest width ........................................................ 25
2.5. Fig. 2.5. The visual assessement of body depth ......................................................................... 25
2.6. Fig. 2.6. Assessement of fat cover ............................................................................................. 26
2.7. Fig. 2.7. After slaughter conformation scale of beef carcass ..................................................... 26
2.8. Fig. 2.8. Examples for genotype x environment interactions (after Brandsch) .......................... 27
3.1. Table 3.2. Phenotypic, genetic and environmental values of three genotypes ........................... 32
3.2. Table 3.3. The calculation of variance for data in Table 3.2. .................................................... 33
3.3. Table 3.4. Variance table for a fullsib design, N families and n individuals in each family ...... 34
4.1. Fig. 4.1. The presentation of within and between generation change ........................................ 54
4.2. Fig. 4.2. The selection differential and the proportion selected ................................................. 54
4.3. Fig. 4.3. Directional selection .................................................................................................... 56
4.4. Fig 4.4. Seletion for threshold trait with T threshold level (after Lynch and Walsh). ............... 58
4.5. Fig. 4.5. Selection differential and frequency of liability in thershold traits (after Lynch and Walsh. ).
The intitial frequency is 0.05. the heritabilty is 0.25. ....................................................................... 58
4.6. Fig. 4.6. The relationship between correlations. ........................................................................ 63
6.1. Fig. 6.1. Flow chart of typical broiler or turkey operation ........................................................ 69
6.2. Table 6.3. Heritabilities for growth and body composition in chicken ..................................... 71
6.3. Table 6.4. Correlation between broiler traits ............................................................................. 71
6.4. Table 6.5. Heritabilities of layer traits ....................................................................................... 72
6.5. Table 6.6. Correlation between layers traits .............................................................................. 72
9.1. Table 9.1. Gene effects on chicken fatness and mucle fiber traits (Lei et al..2007) .................. 86
9.2. Fig. 9.1. Marker assisted introgression ...................................................................................... 86
10.1. Fig. 10.1. Chromosomal map location of the MHC ................................................................. 91
11.1. Fig. 11.1. White Hungarian Chicken, female and male ........................................................... 92
11.2. Fig. 11.2. Bronze and Copper Turkey flock ............................................................................ 93
11.3. Fig. 11.3. Broiler stock on deep litter ...................................................................................... 95
11.4. Fig. 11.4: Caged laying hens ................................................................................................... 96
11.5. Fig. 11.5. Geese farm ............................................................................................................... 97
11.6. Fig. 11.7. Combined deep litter & battery floor technology .................................................. 100
11.7. Fig. 11.8. New “EU conform” cage ....................................................................................... 100
11.8. Fig. 11.9. Fattening for liver .................................................................................................. 101
12.1. Fig. 12.1. Grains used in feeds ............................................................................................... 105
12.2. Fig. 12.2. Oil cakes (soybean, sunflower, groundnut & cottonseed) ..................................... 106
12.3. Fig. 12.3. Protein meals (fish, meat & blood meal) ............................................................... 107
12.4. Fig. 12.4. Egg structure & quality ......................................................................................... 110
13.1. Fig. 13.1. The Broiler growth curve ...................................................................................... 116
13.2. Fig. 13.2. The phases of egg production ................................................................................ 117
13.3. Table 13.9. Requirement of other minerals for domestic fowls ............................................. 121
14.1. Fig. 14.1. Elements of air exchange ...................................................................................... 131
14.2. Fig. 14.2. Cage laying technology ......................................................................................... 132
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14.3. Fig. 14.3. EU conform cages (interior & with hens) ..............................................................
14.4. Fig. 14.4. Barn laying technology ..........................................................................................
14.5. Fig. 14.5. Free range technology ...........................................................................................
14.6. Fig. 14.6. Barn technology for turkey ....................................................................................
14.7. Fig. 14.7. Geese farming technology .....................................................................................
14.8. Fig. 14.8. Duck farming technology ......................................................................................
15.1. Fig. 15.1. A typical processing plant .....................................................................................
15.2. Fig. 15.2. Poultry slaughtering ...............................................................................................
15.3. Fig. 15.3. Possible ways of salmonella infection in poultry ..................................................
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A táblázatok listája
1.1. Table 1.1. The relative weight of some traits in the breeding objectives in some countries for
Holstein-Friesian and Simmental ........................................................................................................ 5
1.2. Table 1.2. Marginal economic values (MEW, in € per unit of trait, per sow and year when improving
the trait level), genetic standard deviation (GS) and standardized economic values (SEV, in €/GS) 14
1.3. Table 1.3. Genetic parameters of slaughter traits ...................................................................... 15
1.4. Table 1.4. Relationship between prolificacy and some slaughter .............................................. 15
1.5. Table 1.5. Genetic parameters for Lacaune milk production traits ............................................ 16
1.6. Table 1.6. Relationship between wool traits and fertility and mature weight ............................ 17
1.7. Table 1.7. Relative economic weight of Hungarian Merino traits ............................................. 17
3.1. Table 3.5. Examples of heritabilities of some livestock traits (after M.B. Willis, 1991) ........... 35
3.2. Table 3.6. The repeatability of some livestock trait ................................................................... 37
3.3. Table 3.7. Genetic correlations between some livestock traits (according to Legates, J.E and Warwick,
E.J., 1990) ......................................................................................................................................... 38
3.4. Table 3.8. The phenotypic, genetic and environmental correlations for some traits (According to
Legates, J.E and Warwick, E.J., 1990) ............................................................................................. 39
6.1. Table 6.1. The feed conversion ratio of different species ......................................................... 68
6.2. Table 6.2. The comparison broilers and quality chicken .......................................................... 71
7.1. Table 7.1. Inbreeding coefficient for some typical mating ........................................................ 74
7.2. Table 7.2 The effect of heterosis in some sheep traits ............................................................... 78
8.1. Table 8.1. Layers selected for high and low group performance ............................................... 81
8.2. Table 8.2. The effect of group selection on immunological parameters .................................... 81
11.1. Table 11.1. Factors affecting the animal behaviour ................................................................. 95
11.2. Table 11.2. Distribution of different behaviour forms of laying hens in cages at 13 hour long
illuminating period ........................................................................................................................... 96
11.3. Table 11.3. Measurement/estimation of malaise or well-being ............................................... 98
12.1. Table 12.1. Factors limiting the use of alternative feed ingredients in poultry feed formulations 108
12.2. Alternative energy sources that can replace maize in poultry diets ....................................... 110
12.3. Alternative protein sources that can replace soybean meal in poultry diets .......................... 111
12.4. Alternative animal protein sources for use in poultry diets ................................................... 112
13.1. Table 13.1. Bodyweight and cumulative feed consumption for male and female broilers (g) 114
13.2. Table 13.2. Examples of broiler diets ................................................................................... 115
13.3. Table 13.3. Body weights and associated feed consumption for a brown-egg laying breed during the
growing period ................................................................................................................................ 116
13.4. Table 13.4. Nutrient levels in animal protein meals .............................................................. 118
13.5. Table 13.5. Growing period nutrition recommendations ....................................................... 118
13.6. Table 13.6. Examples of layer diets (at 100g per day intake level) ....................................... 119
13.7. Table 13.7. Requirement of other minerals for poultry ......................................................... 120
13.8. Table 13.8. Specifications in diet for chicken ........................................................................ 120
13.9. Table 13.10. Examples of turkey diets ................................................................................... 122
13.10. Table 13.11. Body Weights and Feed Consumption of Large-Type Turkeys during the Holding and
Breeding Periods ............................................................................................................................. 123
13.11. Table 13.12. Growth Rate and Feed and Energy Consumption of Large-Type Turkeys ..... 123
13.12. Table 13.13. Nutrient Requirements of Turkeys (Males and Females) as Percentages or Units per
Kilogram of Diet (90% dry matter) ................................................................................................ 124
13.13. Table 13.14. Nutrient Requirements of Geese as Percentages or Units per Kilogram of Diet (90%
dry matter) ...................................................................................................................................... 127
13.14. Table 13.15. Approximate Body Weights and Feed Consumption of Commercially Reared Male
and Female Geese to 10 Weeks of Age .......................................................................................... 127
13.15. Table 13.16. Suggested Macronutrient Requirements of Ducks1 ......................................... 128
13.16. Table 13.16. Suggested Micronutrient Requirements of Ducks .......................................... 128
13.17. Table 13.17. Example Rations for Ducks (% of complete ration) ....................................... 129
15.1. Table 15.1. Nutrient composition of roasted or broiled poultry cuts(per 100 grams) ............ 140
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Tárgymutató
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1. fejezet - 1. Breeding objectives
“We cannot suppose that all the breeds were suddenly produced as perfect and as useful as we see now them;
indeed, in several cases, we know that this has not been their history. The key is man’s power of accumulative
selection: nature gives successive variations; man adds them up in certain directions useful to him. In this sense
he may be said to make for himself useful breeds” (C. DARWIN (1859): On the origin of species, p. 30).
A breeding program consists the following elements: determining the breeding objectives and their economc
values, 2. determination of the selection critereas, 3. data recording, 4. breeding value evaluation, 5. selection, 6.
mating, 7. evaluation of the breeding program.
The long-term goals for animal production are resource efficiency, profitability, productivity, environmental
soundness, biodiversity, social viability, and ethical aspects. However, animal breeding determined only by
short-term market forces leads to unwanted side effects. Olesen at al. (2000) suggested a procedure for defining
animal breeding goals with ethical priorities and weighing of market and non-market values that contribute to
sustainable production systems. They think, important prerequisites for breeding programs for sustainable
production are appropriate governmental policies, awareness of our way of thinking, and a more communal
worldview informed.
Questions
• What is a breeding objective?
• Why is it important?
• What should it focus on?
• How much progress can be made?
What is a breeding objective?
1. A weighted combination of traits defining aggregate breeding value for use in an economic selection index.
2. A general goal for a breeding program - a notion of what constitutes the best animal in a given economic
circumstance.
Why is it important?
By determining the breeding objective, we set long term production goals that helps make faster progress. The
consistent breeding direction provides the basis against which we can measure improvement.
What should it focus on?
Traits in a breeding objective should be economically important, heritable and measurable. Objectives include
traits to be changed, desired level of performance and time frame. The traits have to have genetic variation and
heritable, on the other hand have to have economic importance. Heritability is a measure of how much of the
variation that we see between animals in a herd is genetic in origin. Selection of parents will only result in a
change in progeny performance if the selected trait is heritable. Generally we know that fitness and reproduction
traits such as fertility, herd life, prolificacy, stillbirth, survival rate have got a low heritability (0-20%),
production traits have got a medium heritability (20-40%), e.g. milk production, growth rate, egg production,
feed efficiency, and the so called (product) quality traits have got high heritability (40% +), e.g. fibre diameter,
lean meat percentage, lean/bone proportion.
The traits in the breeding objectives are connected to the increase of production level, or connected to the
decrease of production cost. The number of traits in the breeding objective need to be limited due to the known
relationship and the possible unfavourable correlation between the traits. If the correlation between the traits
hinder the joint improvement, specialized lines or breeds needs to be developed e.g. maternal lines or sire lines.
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1. Breeding objectives
By choosing the traits to improve, we need to be aware of the market environment, in which the progenies of the
breeding animals will perform. The bio-economic models are used efficiently to calculate the economic weights
of the traits, based on profit functions, on the biological relationship between the traits, and on managementfeeding-market conditions applying gene-flow models. In bio-economic models we suppose that, the costs and
prices are known. If the market condition is uncertain, or the costs and prices are not known, the desired gain
approach is suitable for determining the economic value. The tool is also used by breeding firms with large
capital, many breeding lines and if they are present in several markets. In uncertain market situation, this
approach can be extended with conjoint market analysis, when the possible consumers are asked to rank the
traits to improve. The general objective is the longterm sustainability of breeding and commercial companies.
Sometimes the interest of traits for selection in nucleus, multiplier, commercial level or processing, commerce
and consumer level are opposing. In a consolidated situation all players have got the same objective. In some
cases the economic value of a trait can be diverted from the real market value, due to political reason, but this
situation can not be maintained for long term.
The aggregate genotype is the product of the additive genetic value (or breeding value) of the traits in the
breeding objectives and their economic value:
H = v1g1 + v2g2 + …vngn
where H is the aggregate genotype, v1, v2,…vn is the economic value of the traits and g1, g2, gn are the additive
value of the traits.
Selection criterias. The selection criterias are those traits for which the data recording aims at and selection can
be based on to improve traits in the breeding objectives. The selection criterias can be the same as the breeding
objectives but can be different, but genetic correlaton should exist between trait groups. This serves in indirect
selection. The selection criteria is the information source (x).
The selection index consists selection criterias:
I = b1x1 + b2x2+…,+ bnxn
where, I is the indexpoint, b1 is the weighing factor for x1 selection criteria. The aim is to maximise correlation
between H and I (rHI). By increasing the number of selection criterias, the correlation increases, such as by
known performance information of relatives.
How much progress can be made?
The progress, or selection response is the difference of genetic value the unselected parents and the selected
parents, or the difference of the average pehotypic value of the unselected potential parents and the phenotipyc
value of the progenies of the selected parents. This shows us the success of our selection work. If the response is
satisfactory, we maintain the breeding program. If the response (or the unwanted increase in inbreeding) is
behind our expectation we readjust our breeding programme. The response depends on the selection intensity,
accuracy of breeding value, and the genetic standard deviation, and its yearly advancement depends also on the
genetic interval. Since the accuracy and selection intensity is higher in males, they effect response and
inbreeding at a higher rate.
1. Setting a breeding goal in dairy cattle
Production traits in dairy cattle include: 305-day milk yield, milk protein and fat are the major determinants of
dairy farmer’s income. The relative economic weight depends on the quota or non-quota pricing system. Usually
feed intake is not included in the profit function (has got a high correlation of 0.8 with milk yield), the economic
weights for milk, fat and protein need to include the extra feed cost associated with extra milk yield.
Fitness traits are health, fertility, calving ease, body weight, feed intake, milking speed, temperament and
longevity. Fitness traits usually negatively correlated with production traits. Incidence of mastitis is the most
important health trait, but only a few countries record it, in most countries only somatic cell count is recorded
and somatic cell score is included in the index. Fertility traits are measured as days open, non-return-rate till the
56th day, or the 90th day of insemination, service period, calving interval, number of insemination till
conception, age at first calving. Poor fertility increases insemination and veterinary cost. Long calving interval
lengthen the lactation when milk production is already low. The economic weight of fertility can be assumed
half that of the milk protein yield. Good persistency (lower peak yield) favourable contributes to high fertility.
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1. Breeding objectives
Calving ease, which is coded from 1 – easy calving to 5 - cesarian operation is also important because dystocia
increases veterinary and labour cost, delays conception and effect calf survival. Calving ease affected by the size
of the calf and also by the mother, and these effects need to be separated. The body weight effects maintanence
cost so large body weight is not desirable. Milk speed usually is also included amongst the breeding objectives,
since slow milkers increase the labour cost of milking. Temperament, or workability are also included, due to
the large number of cows needed to be handled in farms. The long life of a cow has got a monetary value,
because it decreases replacement cost and an indirect measure of low service cost.
Type traits are tools for achieving sustainable production. A new approach is the assessement of functional
conformation that facilitates the development of a cow’s natural ability to produce higher volumes of milk over
longer lifetimes. The classification is a herd improvement tool by the means of the corrective mating.
Conformation traits have got a wide range of heritability (0.1-0.7). The most important conformation
characteristics with known relationship to functional survival are: udder conformation, feet and leg
conformation, thoratic and abdominal body conformation and rump and loin structure. According to Zavadilová
et al. (2011) the dairy form, udder and final score have got the strongest relationship with functional longevity.
This followed by body condition score, angularity, udder attachment and udder depth. Foot and leg showed
substantially lower effect on functional longevity, and the effect of foot angle was minimal. Functional
longevity declined with decreased body condition of cows. Cows with deep udders had significantly lower
functional survival compared with cows with shallow udders. Interestingly dairy form and angularity, cows
classified as very good were the worst with respect to longevity, and an intermediate optimum was evident for
rear view and rear legs set.
Growth and Carcass Traits include birth weight, growth rate of calves until weaning and in the rearing period,
from month 6 until first calving, weight increase during the fattening period, mature weight of cows, dressing
percentage. Both sexes needs to be considered when calculating the economic value of birth weight and weight
increase, but it needs to be expressed for females only.
1.1. ábra - Fig. 1.1. Holstein-frieasian cow
Source: http://www.teara.govt.nz
A bio-economic model was used to estimate economic values of 15 milk production, functional, growth and
carcass traits for Hungarian Holstein-Friesian cattle by Komlosi et al. (2010). The calculations were carried out
for the situation in Hungary from 2000 to 2007, assuming no production quotas. The marginal economic values
were defined as partial derivatives of the profit function with respect to each trait in a production system with
dairy cow herds and with sales of surplus male calves. The economic weights for maternal and direct
components of traits were calculated multiplying the marginal economic values by the number of discounted
expression summed over a 25-year investment period for 2-year-old bulls (candidates for selection). The
standardized economic weight (economic weight x·genetic standard deviation) of the trait or trait component
expressed as percentage of the sum of the standardized economic weights for all traits and trait components
represented the relative economic importance of this trait or trait component. The highest relative economic
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1. Breeding objectives
importance was obtained for milk yield (25%), followed by productive lifetime of cows (23%), protein yield and
the direct component of a cow’s total conception rate (9% each), the maternal effect of the total conception rate
of cows and the somatic cell score (approximately 7% each), fat yield (5%) and mature weight of cows and
daily gain in rearing of calves (approximately 4% each). Other functional traits (clinical mastitis incidence,
calving difficulty score, total conception rate of heifers and calf mortality) reached a relative economic
importance between 0.5% and 2%. Birth weight and dressing percentage were least important (<0.5%). Based
on these results, the inclusion of productive lifetime and cow fertility in the breeding programme for HolsteinFriesian cattle in Hungary is advisable. For comparison, the importance of traits in the objective in different
countries is shown in Table 1.1.
1.1. táblázat - Table 1.1. The relative weight of some traits in the breeding objectives in
some countries for Holstein-Friesian and Simmental
Breed
Holstein-friesian
Simmental
Trait/country
USA$
Canada
Germany
Hungary
Germany/
Austria
Hungary
milk(kg)
<1
-
-
-
-
25
protein (kg)
16
30,6
33,75
40/30a
33,4
50
fat (kg)
19
20,4
9
15/15
4,4
25
protein (%)
-
-
2,25
-
-
-
milking speed (min)
-
0,45
-
-
2
-
somatic cell count
-10
-3
-7
-10/-10
9,7
-
persistency (%)
-
-
-
-
2,0
-
longevity (day)
22
6,8
20
*/10
13,4
-
udder traits
7
15,1
-
23/16
-
-
feet and leg
4
10,2
-
12/16
-
-
body capacity
-6
-
-
-
-
conformation
-
3,4
15
*
fertility (%)
11
10,05
10
-
6,8
-
calving ease (%)
5
-
3
-/3
3,7
-
Production traits
Fitness traits
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*
1. Breeding objectives
stillbirth (%)
-
-
-
-
8,1
-
body gain (g)
-
-
-
-
7,3
-
killing out (%)
-
-
-
-
4,6
-
EUROP (class)
-
-
-
-
4,6
-
Growth traits
$http://www-interbull.slu.se/national_ges_info2/framesida-ges.htm. Date: 2011.06.12;
§ ZAR Rinderzucht, Austria Ausgabe (2010): Zentrale Arbeitsgemeinschaft österreichischer Rinderzüchter;
German Fleckvieh (Simmental) Tradition with Success (2010): Arbeitgemeinschaft Süddeutscher Rinderzuchtund Besamungsstationen e.V.;
*non-index traits, but independent culling level is practiced; a before 2011 April/after 2011 April
2. Breeding objective in dual purpose cattle breeds
The Hungarian Fleckvieh being a member of the Mountain Fleckvieh group is a dual-purpose breed with good
fitness attributes and high milk yield. The members of the group adapt well to extreme environments, and their
firm metabolism ensures of good beef and milk production even during the peak periods. During the past
decades the milk production of the Mountain Fleckvieh breed variants increased, while, in the absence of direct
selection − fitness traits such as productive life, vitality, and fertility showed slightly unfavourable changes
(Füller, 2010). The first breeding value estimation and selection activity targeting functional traits was started in
Austria in 1995 for productive life of breeding bulls, which was followed by the other traits in the subsequent
years (1998) (Fürst, 2001). As a result, milk yielding traits had a share of 88.2%, beef yielding traits 4.2%,
fitness traits 7.6% progress in economic value (Miesenberger and Fürst, 2006).
German and Austrian Mountain Fleckvieh breeders identified breeding goals in the increase of milk protein,
improvement of fitness and animal health, increase of life performance, and maintenance of beef yielding traits.
They aimed at functional productive life with 30 000 kg of milk yield. Tischler (2002) highlights that the
importance of production traits (milk and beef) and fitness traits in Mountain Fleckvieh breeding programs
varies between countries in Europe and overseas, which can be explained by the differences in market and
socio-political requirements resulting from the role of the sector. Countries aiming at maximum profit stress the
importance of production oriented traits (USA, New Zealand, Canada), while in European countries where
agriculture is a multifunctional industry (Germany, Austria, France, Italy), so production and fitness traits weigh
in almost equal proportions in their breeding programs (Füller, 2010).
Breeding goals identified by the Hungarian Fleckvieh Association (2009) are high milk and beef yielding
capacity, high feed intake necessary for high performance, fertility, good growth rate and adaptability. The
index of adaptability is expressed in productive life. Traits such as firm, easily milking udder of appropriate
shape; limbs with flawless, strong, dry foot; muscularity and optimal frame are prioritized. As breeding goals for
dual-purpose herds they translate as 6500 kg milk, 4.1% fat, 3.6% protein, 2.0 kg/s average milking speed.
Heifers are to be mated between 16-18 months of age, with 380-400 kg of body weight, productive life covers 57 calvings and lactations on the average. Adult cows are not to surpass 700 kg of body weight. The cow herds
recorded produced 5416 kg of milk, 3.86% fat, and 3.8% protein on average (based on yearly performance of
2008).
To achieve these goals, performance and selection indices were applied for the following traits: amount of milk
(kg), milk fat (kg; %), milk protein (kg; %), somatic cell count, persistence, fertility, productive life,
conformation traits, calving ease, and stillbirth.
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1.2. ábra - Fig. 1.2. Hungarian Simmental.
Source http://www.allattenyesztok.hu
3. Setting a breeding goal in beef cattle
Production traits. Managing variation in birth weight is a tool to control dystocia but also contributes to the
viability of the calf and to postnatal growth. Environmental effects included in genetic evaluations are:
contemporary group, sex, age of dam (parity), calving type (single or twin), calving season and permanent
maternal environment. Direct weaning weight (WW) adjusted to 200, 205 or 210 days of age is the main trait
targeted for improvement in all beef breeding schemes. Environmental effects influencing this trait include
contemporary groups, sex, age of dam (parity), calving type, calving season and permanent maternal
environment. Direct and maternal influences on WW often are assessed concurrently in a two trait animal
model. The sign and size of the genetic correlation between these two traits may depend upon whether the
model includes sire x herd or sire x year interaction. The correlation also depends on the milk production level
of the breed. In some analyses, a zero correlation is assumed. The appropriate emphasis to be placed on maternal
WW is dependent upon market weight and the production environment. Most schemes record weight only once,
around 200-d, or twice, once before and once after 200-d. In test stations, body weights is generally recorded
monthly, allowing utilizatin of random regression models to estimate breeding values for growth curve
parameters.
For selection within terminal breeds, the target weight is the yearling weight (YW), which is influenced by
contemporary group, sex, age of dam and season. Several reviews have described unfavorable correlated
responses in reproductive traits of cows from populations selected for growth. Studies carried out in favourable
nutritional environments, however, it is reported that selection for increased body weight did not compromise
the reproductive performance with respect to days to calving and calving success. Selection for increased
juvenile weight increases mature weight, which many breeding programs seek to moderate due to correlated
responses in nutritional requirement and dystocia.
In performance test programs that record food consumption, breeding value evaluation for food conversion rate
or residual feed intake is possible. Genetic improvement in feed efficiency could thus be achieved with minimal
correlated responses in growth and the other postweaning traits.
Conformation traits. Selection to improve conformation traits should be conducted primarily to improve
economically relevant traits to which they are genetically correlated- soundness, longevity and slaughter value
for example. Although genetic parameters have been estimated for such traits, performance records are
generally not processed for breeding value estimation. Rather they are used directly as independent culling level
criteria or to augment final selection decisions.
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Reproduction traits. Due to the categorical nature of dystocia scores, estimation of breeding values for direct
and daughter calving ease requires sophisticated evaluation software. As a consequence, they are calculated in
fewer instances than for production traits. Calving difficulty is positively correlated with gestation length, hip
height, age at puberty, scrotal circumference (SC) and retail product. A bivariate model, including birth weight
(linear) and calving ease (threshold) is a good option for predicting both maternal and direct effects. In a small
herd-year group size situation, a fixed linear model is also a practical choice. Environmental effects generally
considered are sex of calf, twining rate, age (parity) of dam and herd-year-season effects. Heifer fertility and
cow fertility should be treated as different traits. Alternative measures of reproductive merit include age at first
calving, calving interval, calving date, days to conception from the onset of the breeding season and calves
produced per lifetime. SC is correlated to female fertility. SC also shows favourable correlations with sperm
quality and with age at puberty in males and females. The genetic correlation between SC and days to calving is
generally negative, suggesting that inclusion of days to calving in selection might improve genetic merit for bull
fertility as well.
Although pregnancy rate and environmental heat stress are negatively associated, meterological data generally
are not accounted for in genetic evaluations of reproductive traits.
Slaughter traits. Slaughter value can be assessed as early as weaning, but more often is assessed during postweaning performance testing. Traits recorded on a monthly basis include muscularity, body condition score,
ultrasound subcutaneous fat, marbling and eye muscle area. Random regression analyses can be applied on the
repeated records to estimate for breeding values for tissue growth curve parameters. The aim is to connect these
measurements to post-slaughter traits such as carcass muscularity and fatness, lean% and carcass weight.
However, selection for increased lean yield carries risks of older age at puberty, increased mature size,
decreased fertility and possibly increased maternal calving difficulty. To avoid detrimental effects on maternal
traits in a purebreeding system, genetic management should apply index selection. Structured crossbreeding
exploiting heterosis is an additional option.
International evaluation schemes. The Australian BREEDPLAN is the only program known to the author
which includes all the above mentioned traits in a multiple-trait evaluation model. BREEDPLAN is presently
used in 10 countries. An European initiative is INTERBEEF, with five countries currently participating in. Even
though data structure and quality differs among countries, information is not adequate to precisely estimate
maternal (co)variance components and there are cases in which sires are identified differently in diferent
countries, genetic correlations between breeding value estimates for the same trait across countries range from
0.67 to 0.90. Genotype x country interactions do exist, however, in some instances.
Performance information from crossbred progeny is used for breeding value estimation in purebred parents in
only a few countries. Although its utilization would require performance recording in commercial herds and a
sophisticated genetic evaluation to account for heterosis and recombination effects, the reliability of the
breeding value estimates would increase substantially, and purebred and crossbred breeding values could be
calculated. A Bayesian implementation of the multiple-breed animal model represents a viable alternative to
animal model for multiple-breed genetic evaluations, providing the necessary flexibility in modeling
heteroskedastic genetic variances of breed composition groups. A reranking of sires for purebred and crossbred
breeding values would be expected for weight-related traits, with little expected change for carcass traits.
Breeders should choose the appropriate traits and economic weights for their production conditions and for the
requirements of their target market. The Australian BREEDOBJECT is a flexible tool for deriving the index
weights. The Czech program ECOWEIGHT, a bio-economic model, is a powerful tool for calculating economic
weights for dairy and beef traits. Sample results of an ECOWEIGHT application were that conception rate of
cows and weaning weight reached about 50% of the standardized economic weight of calving performance in
purebred systems with sale of weaned calves; whereas in purebred systems with fattening, the economic
importance of the direct component of cow conception rate, losses at calving, mature weight of cows, weaning
weight and fattening traits were of equal importance (each approximately 20% that of calving performance). In
terminal crossing systems, weaning weight was important when calves were sold at weaning, and fattening traits
were important for systems selling fattened animals.
Because advanced reproductive technologies have been less extensively used in beef catle than in dairy cattle
breeding schemes, inbreeding accumulation is not as serious a problem. In the future, however, selection and
mating strategies might need to incorporate its monitoring and management.
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4. Potential new traits to include in selection
programs
Disease resistance. The estimated heritability of resistance to bovine respiratory disease on an underlying
continuous scale is substantial, inferring that response to selection could be substantial as well.
Meat quality. Consumer need for healthier food might bring more attention to fatty acid composition of the
meat. Since no antagonism has been found between carcass traits and fatty acid composition, favourable
response in both trait groups could possibly be achieved. Results indicate that improvement in tenderness based
on selection for favourable shear force, sensory panel tenderness or calpastatin activity would be slow.
Longevity. Longevity of breeding stock has a substantial effect on economic efficiency of a production system.
Survival analysis is the usual tool to calculate longevity breeding values. Relatively low heritability and the lack
of indicator traits expressed early in life suggest that genetic improvement of longevity will be difficult. Calving
difficulty seems to be an important risk factor contributing to the early culling of beef females.
Temperament. Genetic evaluations for feeding behaviour and temperament may be useful. because behavioural
traits may contribute to variation in efficiency of growth and meat quality.
Heat tolerance. Because increasing summer temperatures are a likely long-term prospect, improved heat
tolerance may be an important breeding goal. Evidence supports the existence of a slick hair gene that is
responsible for a very short, slick hair coat. The cold tolerance during continental winters of cattle with the slick
hair phenotype is, however, not known.
1.3. ábra - Fig. 1.3. A Charolais bull in Hódmezővásárhely in 2009.
Source: http://www.charolais.hu
In our study (Keller et al., 2009) we analysed the impact of mature cow weight on the profitability of beef cattle
farming and on the economic importance of 10 performance and functional traits in Hungary. The examined
traits were: calving performance, stillbirth and calf losses till weaning, weight of calves at birth, at 120 and at
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205 days of age, mature weight of cows, conception rates of heifers and cows and productive lifetime of cows.
The cow weight was varied from 500 to 700 kg in 50 kg intervals. The economic efficiency of all farming
systems was expressed as profit per cow and year. The economic importance of a trait (marginal economic
value) was defined as partial derivative of the profit function with respect to trait mean. The program package
ECOWEIGHT was used for all calculations. The results showed that beef cattle farming with all cow weight
classes could be profitable when including subsidies in the incomes of a farm. Without subsidies, a positive
profitability can be reached only when keeping small-framed cows (500 to 550 kg). In all modelled production
systems, the most important trait was conception rate of cows followed by weaning weight of calves (at 205
days of age) for light cows or productive lifetime of cows in systems with heavy cows.
1.4. ábra - Fig. 1.4. Limousine breed.
Source: Szarvasmarha01.blogspot.com
5. PIG
Setting a breeding goal in pig (swine)
Profit in pig industry is the result of highly productive females producing fast growing, efficient pigs that
produce high-quality meat. Since reproduction and production traits are negatively correlated, specialised
(maternal and sire) lines are formed. By crossing the two lines (or more) heterosis (in addition to the additive
genetic effects) is utilised.
The breeding objectives in maternal lines are reproduction (number born or weaned, number alive at 5 days (or
21 days), and litter weaning weight (maternal ability), growth rate and feed efficiency, sow longevity (breed and
rebreed for multiple parities and structural soundness) and health traits. Longevity is defined as the probability
of a gilt inseminated for first litter to proceed to insemination for second litter after weaning of the first litter.
Too frequently the breeding herd has difficulty with structural soundness. If we compromise soundness, culling
rates and sow death rates will increase, performance will decrease. Breeds used as maternal lines are: Landrace,
Large White, Yorkshire (as primary maternal lines), Chester White, Meishian (as secondary maternal lines).
Conformation is weighed twice as much in the dam lines as the sire line. Conformation is a subjective
evaluation of the physical appearence of the individual animal.
1.5. ábra - Fig. 1.5. Landrace.
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Source: http://www.cedarridgegenetics.com
The characteristic of the Landrace is high milking ability, good maternal ability and instincts, good udder
quality. The Large White or Yorkshire is characterized by high litter size, good milking ability, good fertility
and good udders.
1.6. ábra - >Fig. 1.6. Large White pig.
Source: http://pigs.co.nz
Breeding objectives in terminal sire lines are growth rate, feed efficiency, lean meat yield, meat quality, fitness
and health, semen production and fertility. Breeds used for sire lines are: Pietrain, Hampshire and Duroc. The
aim characteristics of the Pietrain is very lean muscle, and animal is heavy muscled, slow growing, and
susceptible to stress.
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The small holder’s pig breeding objective in the third world countries in resource-driven production system are
the adaptive traits: reproduction, disease resistance and appearance. In the demand-driven (i.e. market-oriented)
systems the performance traits are preferred, such as: growth and feed requirements (Roussier et al., 2008).
1.7. ábra - Fig. 1.7. The Pietrain pig.
Source: http://www.isv.hu
1.8. ábra - Fig. 1.8. The Hampshire breed.
Source: http://www.profimedia.hu
The main feature of the Hampshire is the moderate growth, high lean mean, but due to the possible presence of
the Napole gene, the meat has got a poor water holding capacity.
1.9. ábra - Fig. 1.9. Duroc pig breed.
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Source: http://www.geneplus.com
The Duroc is known as the highest growth breed, moderate in fat, high in lean growth rate, altough high in feed
intake, high in intramuscular fat. It’s meat tender and flavourful and acceptable colour.
The swine industry is built up to utilise the additive, dominance and epistatic gene effects in a breeding pyramid
(Fig. 1.10.).
1.10. ábra - Fig. 1.10. The breeding pyramid
At the seedstock level, purebreds, synthetic lines or strains are kept, where the highest genetic improvement is
achieved by intense selection focusing in a relatively small number of traits. Genetic markers or genes are used
in the selection. Due to the large capital investment nucleus herds are owned by companies or breed
cooperatives. The business model of the international pig breeding companies is that, breeding stock is
maintained, reproductive services and other support is provided for sustainable profit of the commercial farmers.
Breeding companies set up an unified goal, they have access to business and legal specialists, they have capital
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for infrastructure, research and development. There is an opportunity for vertical integration, and make longterm contracts and agreements. Nucleus farms are isolated for biosecurity, they maintain many pure commercial
and experimental lines for a variety of commercial market. On the other hand due to the intense competition
they maximize current profits and maximize genetic trend that may result in over emphasis of some traits and
under emphasis of others, ignoring future industry needs In the breeder-owned companies performance
recording is focused on nucleus farms and central stations, sib testing is practiced for carcass traits, herds are
ulinked with AI, breeding values are estimated centrally, some traits are also recorded in multiplier or
commercial herds (longevity e.g.). The role of the multiplication level is to cross pure line sor strains by which
combination of superior attributes of each breed or line can be exploited.
At commercial level crossbreeding is extensively used to maximize heterosis (both maternal and paternal
heterosis). The focus is on the end-product, what is meat and by-products for human consumption. Production
efficiency is critical for success. Commercial breeders produce large volume of production. To maximise
genetic performance and exploit high-quality sires, extensively use AI.
An example of the mating system is using Hampshire and Landrace as great grandparent, their progeny is
crossed with Large White, then the females of this cross is mated with Duroc.
Marginal economic values for production and reproduction traits of pigs were estimated applying a bioeconomic model to Hungarian commercial sow herds with integrated fattening of piglets (Houska et al., 2010).
Data collected between 2002 and 2008 were used for the calculation. Results are shown in Table 1.2.
1.2. táblázat - Table 1.2. Marginal economic values (MEW, in € per unit of trait, per sow
and year when improving the trait level), genetic standard deviation (GS) and
standardized economic values (SEV, in €/GS)
Trait (unit)
MEW
GSDDD
SEVWW
Number of piglets born alive (piglets)
54.22
0.61
33.07
Age at slaughter (days)
2.71
15.02
40.70
Days in fattening
2.84
9.91
28.14
Lean meat content in the carcass (%)
22.45
1.62
36.37
Percentage of valuable cuts in the carcass (%)
28.81
2.55
73.46
6. Sheep
The sheep is kept mainly on marginal areas so choosing a suitable breed to the given nutritional, climatic and
geographical environment is crutial. In marginal areas the keeping of midle-small sized, good mothering ability,
prolific ewes, which is mated with large sized terminal breed is economical. In the sheep industry emphasis
should be given to cost reduction. Traits associated with cost are survival, resistance and breed crossings should
be more important.
Fertility and prolificacy. Traits belong to this trait group is age at first lambing, number of lambs borned,
survival of lambs, lambing interval and longevity. Selection for age of first lambing is successfully carried out
by independent culling level, by which the nutritional cost of replacements can be decreased. This trait is
affected by year and season of birth. Breeds with high growth rate reach earlier maturity. Similarly in beef
cattle, relatives of a large testis circumference ram, can breed earlier, and more frequently. Selection for early
maturity however requires outmost care. Yearly lamb production depends by number of lambs per lambing and
lambing interval. 60% of Merino ewes can breed twice a year in Hungary. Selection for ewes born out of season
is effective for short lambing interval. There is difference between breeds in aseasonal lambing. Suffolk is less
susceptible for aseasonal lambing, but Romanov and Finish Landrace are more able to breed out-of-season.
However, ewes lambing frequently are more exposed to early culling.
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The heritability of fertility is low (0.01–0.2). Positive correlation exists between fertility and mothering ability.
Fertility of rams became important with the advent of artificial insemination.
The prolificacy is the trait which mostly influences the profitability of sheep farming. High prolificacy not only
has got an effect on income, but also effects selection intensity. The prolificacy is a composite trait determined
by ovulation rate and uterus capacity and prenatal survival. The ovulation rate of the Merino is 1.6, while for the
Cambridge is between 5 and 6. Since the heritability of individual lambing is low, successfull selection for
several lambings is more effective. Lambs born in multiple lambings have got less chance to survive, due to
lower birth weight and less milk per capita. Selection for lamb survival can also be effective.
Some breeds carry the so called prolificacy major gene, like the Booroola carries the Fecundity gene, and the
Inverdale carries the Inverdale (FecX) gene.
Growth and meat production. Few farms record birth weight (BW), which determines the early growth rate
and the survival of the lamb. The heritability of BW is 0.1-0.2. The BW is influenced by litter size, sex, age of
the dam, year and season. Increasing growth rate before weaning is the aim of farms selling weaned lambs.
Weaning weight is amongst the objective in all breeds irrespective of the utilisation. The trait is influenced by
the same environmental factors mentioned for birth weight. Growth rate after weaning is important for farms
selling fattened lambs. The heritability of the trait is moderate or high together with the slaughter traits.
Correlation between body weight traits measured at different ages is high.
The genetic parameters of slaughter traits is shown in Table 1.3.
1.3. táblázat - Table 1.3. Genetic parameters of slaughter traits
Trait
Carcass weight
Lean*
Fat*
Conformation
Carcass weight
0.25
0.40
0.30
0.20
Lean
0.50
0.30
0.35
0.25
Fat
0.40
0.10
0.30
0.15
Conformation
0.50
0.30
0.10
0.30
Heritability is on the diagonal, phenotypic correlation above, and genetic correlation is below the diagonal. *
amount of lean and fat in carcass.
The income of a slaughtered sheep is determined by slaughter weight, fatness and conformation. Traits
influencing consumer preference is meat colour, tenderness, meat/bone, but is not reflected in economic weight
yet. Approaching mature weight, animals becoming fat. Due to positive correlation between live weight and the
carcass fat and lean content, within breed at standard age, animals having larger mature weight are leaner. In
meat breeds the objective is to increase lean growth rate and lean content in the carcasse. The increament of
mature weight can be attained by selection of large growth rate, but large ewe mature weight increases feeding
cost, so in dual purpose breeds selection for large mature weight is qustionable by economic viewpoint.
The correlation between prolificacy and some slaughter traits is presented in table 1.4.
1.4. táblázat - Table 1.4. Relationship between prolificacy and some slaughter
Trait
Prolificacy
Birth
weight
Weaning
weight
Yearling
weight
Prolificacy
0.15
-0.10
0.05
0.10
Birth
weight
0.20
0.15
0.30
0.30
Loin area*
0.10
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Weaning
weight
-0.10
0.40
0.20
0.50
0.40
0.40
Yearling
weight
0.15
0.30
0.80
0.30
0.60
0.50
Loin area
0.35
-0.05
0.60
0.50
0.35
-0.05
Fat depth
-0.05
0.50
0.40
-0.10
0.30
Heritability is on the diagonal, phenotypic correlation above, and genetic correlation is below the diagonal. *
Measured with ultrasonic device on live animal.
Milk production
The milk is an additional income in Merino enterprices, in milk breed enterprices however the main source of
income. In some countries the 20-40% of milk produced by sheep e.g. Syria, Greece, Algeria. Sheep milk has
got larger fatfree dry content, which makes it more suitable for cheese and yogurt, compared to cow milk.
During a 10-120 day lactation dual purpose breed can produce 65-85 liter milk, while dairy sheep (Awassi,
Lacaune, Chios) can produce 200-600 liter milk. The correlation between milk production traits for the Lacaune
breed is shown in table 1.5.
1.5. táblázat - Table 1.5. Genetic parameters for Lacaune milk production traits
Trait
Milk yield
Fat yield
Protein yield
Fat
%
Protein
%
Milk yield
0.32
Fat yield
0.82
0.29
Protein yield
0.92
0.91
0.27
Fat %
-0.34
0.24
-0.05
0.62
Protein %
-0.47
-0.05
-0.10
0.75 0.53
Heritabilities on the diagonal, genetic correlation below the diagonal, phenotypic correlation above the diagonal.
Similarly in dairy cattle, the improvement of milk content and the decrease of somatic cell count became
selection objective in dairy sheep. With the advent of mashine milking, the importance of udder traits (teat
placement, size, form) also increased.
Disease resistance
The disease resistance gained more attention, due to zoonosis, heavy live animal import, high veterinary cost,
and high destruction cost of dead animals. Typical measured health traits are clinical mastitis, somatic cell
count, and parasite resistance (faecel egg count).
Wool
For a long time, the wool was the primary product of sheep (in Australian Merino is still). The wool is the row
material of the textile industry in 10-15%. The wool traits are the grease fleece weight, clean fleece weight, fibre
diameter, staple length. Their heritability is usually high, 0.6–0.7. The relationship between wool traits, fertility
and mature weight is presented in table 1.6.
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1.6. táblázat - Table 1.6. Relationship between wool traits and fertility and mature
weight
Trait
GFW
CFW
Greace fleece weight 0,35
(GFW)
0,85
Clean fleece
(CFW)
0,35
weight 0,80
Fibre diameter (FD)
FD
0,2
5
Staple length (SL)
0,15
-0,25
0,30
-0,10
0,2 0,50
0,1
-0,40
0,3 -0,20
0
5
0
Fertility (F)
0,4 0,25
0,0
0,10
0,1 -0,05
0
0
0
Mature weight (MW)
0,1 0,00
0,1
0,30
0,3 -0,20
0
5
0
Rendement (R)
0,4 0,40
0,4
0,30
0,3 -0,10
5
0
5
MW F
0,3 -0,05
0,2
0,15
R
0
5
0,20
SL
0,2
0,2 0,10
0
5
0,1
0,1 0,10
0
0
Heritabilities on the diagonal, phenotypic correlations are above the diagonal, genetic correlations below the
diagonal.
The relative economic weight for the Hungarian Merino is presented in table 1.7. The fitness traits (prolificacy,
still birth, survival rate) have got the largest economic value, followed by the production traits (growth rate and
weaning weight).
1.7. táblázat - Table 1.7. Relative economic weight of Hungarian Merino traits
Trait
REW(%)
Birth weight (kg)
1.3
Growth rate till weaning (g/day)
11.3
Weaning weight (kg)
6.7
Growth rate after weaning (g/day)
1.8
Growth in fattening (kg)
0.2
Mature weight (kg)
1.1
Fertility of yearlings (%)
2.1
Fertility of ewes (%)
4.9
Number of lambs born
26.8
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Still birth (%)
16.7
Survival rate till weaning (%)
19.8
Longevity (days)
6.8
Greacy fleece weight (kg)
0.5
1.11. ábra - Fig. 1.11. Hungarian Merino.
Source http:/www.mjksz.hu
The Merino was selected as a wool producer, with moderate meat and milk production. As the wool price in
Europe decreased the meat and prolificacy with mothering ability and aseasonal breeding became more
important. The breed is kept mainly in marginal environment.
1.12. ábra - Fig. 1.12. Suffolk sheep.
Source: http://www.mjksz.hu
The Suffolk is a major meat breed, with high lean content. Since it was bred in good pastures of England and in
the USA, it has got a high nutritional requirement. Extensively used in crossing as a terminal breed. Seasonal
oestrus is a disadvantage of the breed.
1.13. ábra - Fig. 1.13. The Lacaune breed.
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Source: http://www.mjksz.hu
The Lacaune breed is selected for high milk production (more than 300 liter per lactation) in France in one line
and for meat production in the other. The meat line is prolific (1.8 lambs for one lambing) with higher growth
and better slaughter value than the milk Lacaune.
7. Questions
1. How do you define the breeding goal?
2. List the requirements for a trait to be in the breeding goal!
3. Please describe a pig breeding system from breeding goal’s viewpoint.
4. Which traits to improve in beef cattle?
5. Which traits to improve in dairy cattle?
6. Which traits to improve in sheep breeds?
8. References and literature suggested
Simm, G. (1998): Genetic Improvement of Cattle and Sheep. Farming Press. Miller Freeman, UK.
Kinghorn, B., Werf, J. van der, Ryan, M. (2001): Animal Breeding, Use of New Technologies. Beef CRC and
University of New England.
KOMLÓSI, I., WOLFOVA, M, WOLF, J., FARKAS, B., SZENDREI, Z., BÉRI, B. (2010). Economic weights
of production and functional traits for Holstein-friesan cattle in Hungary. Journal of Animal Breeding and
Genetics. 127. 143-153.
ZAVADILOVÁ, L., NÉMCOVÁ, É., STIPKOVÁ, M. (2011): Effect of type traits on functional longevity of
Czech Holstein cows estimated from Cox proportional hazard models. J. Dairy Sci. 94. 4090-4099.
Füller, I. (2010). Hústermelő képesség javítására irányuló szelekció továbbfejlesztése a magyartarka fajtában.
Ph.D Dissertation. Kaposvár University.
Magyartarka Tenyésztők Egyesülete (2009). A
http.//www.magyartarka.hu date of access: 06.13. 2011.
magyartarka
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fajta
tenyésztési
programja.
In
1. Breeding objectives
Miesenberger, J., Fürst, C. (2006). Experiences in selecting total merit index in the Austrian Fleckvieh breed.
Biotechnology in Animal Husbandry, 22, 1-2, 17-27.
Fürst, C. (2001). Zucht auf Fitness und Gesundheit beim Fleckvieh-Nutzungsdauer und Langlebigkeit. 24.
Kongress der Europäischen Vereinigung der Fleckviehzüchter. 10-14. 10. 2001. Romania, Brasov.S
Tischler, J. (2002). Fleckviehzucht im Wettbewerb mit speziellen Milchrassen. 4. Fleckviehseminar der AGÖF,
2002. April 5. Strass/Zillertal, Tirol.
KELLER, K., WOLFOVÁ, M., FEKETE, ZS., KOMLÓSI, I., SZABÓ, F. (2009): Der Einfluss des
Kuhgewichts auf die Betriebsrentabilität und auf die ökonomischen Gewichte der Fleischrindmerkmale. Archiv
Tierzucht. 52. 3. 255-264.
HOUSKA, L., WOLFOVÁ, M., NAGY, I., CSÖRNYEI, Z., KOMLÓSI, I. (2010): Economic values for traits
of pigs in Hungary. Czech Journal of Animal Science, 55., 4. 139-148.
Olesen, I., Gjerde, A. F., Groen, B. (2000): Definition of animal breeding goals for sustainable production
systems. Journal of Animal Science. 78. 570-582.
Rousier, R., Drucker, A. G., Scarpa, R., Markemann, A., Lemke, U., Thuy, L., Zárate, A., V. (2008): Using
choice experiments to assess smallholder farmers' preferences for pig breeding traits in different production
systems in North–West Vietnam. Ecological Economics. 66. 1. 184-192.
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2. fejezet - 2. PERFORMANCE
RECORDING
Questions
• What are the tendencies in animal recording?
• Why performance test is important?
• What is it used for?
• Is recording country specific or are there international standards?
The performance reording is a data collection aims to assist breeding value evaluation and selection. During data
collection we focus on selection criterias. The protocoll of recording is being set up by species and utilisation.
The most important part of the performance recording is the correct animal identification, which ulinks not only
the data to the animal, but ulinks relatives and generations. Since every data collected cost money and human
effort, it is imperative that only those data is recorded which is used for calculating genetic difference between
animals. In the past mainly subjective data were collected which has been replaced by data collected by the help
of devices, which increased precision. One way of expressing reliability of the data recorded is the repeatability.
The repeatability (intra-class correlation) is calculated between successive measurements made by the same
instrument either by the same operator or by different operator. If the repeatability is over a defined level,
usually 0.8, or below a defined mean squared error, usually 2.5 it is considered reliable. It is neeed to be
emphasized that the industrial measurement range of the instrument only holds on the interval, in which it was
tested. Bearing in mind that the performance recording is expensive, and keeping the animal till the data can be
recorded, there is a tendency to record as an early age as possible and with less frequency, on the other hand
using real-time data (precision farming) and setting up devices on the farm or in processing plants where data
collection can be automated. More and more physiological data (e.g. heart beat, milk temperature, rumen bolus)
is being collected, we can say that the continuous monitoring of the animal thorought its life is geting more
evident. The instruments adopted either from the military industry or from human medical applications.
To speed up genetic progress, an another tendency is to replace progeny test with self-performance test in all
possible traits. The progeny test is only justified if selection response is higher by time unit than selfperformance test. We do not forget on the other hand, testing of epistatic effect and inter-allele interactions is
not possible without progeny testing.
Since the data collected is used for genetic parameter calculation and breeding value evaluation, all the
environmental factors, significantly influence the trait, needs to be recorded.
The International Committee for Animal Recording (ICAR) is an international organisation for the
standardization of identification, performance recording and evaluation of livestock. The ICAR promotes
improvement of farm animal recording and evaluation through the formulation of definitions and standards for
the measurement of traits of economic importance (www.icar.org). The structure of the organisation is shown in
Fig. 2.1.
2.1. ábra - Fig. 2.1. The organisational structure of the ICAR
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The ICAR has got member countries thorought the World (Fig. 2.2.). The species in the scope of the
organisation are cattle, sheep, goats, buffalo and alpaca. Animal breeding associations, governmental and
private agencies are the members of the ICAR. ICAR issues guidelines for performance testing and genetic
evaluation for production and fitness traits.
2.2. ábra - Fig.2.2. Member states of the ICAR
In performance recording the first step is animal identification. The identification must be unique both in the
herd, both in the country, never be re-used, must be visible. Animals which lose their identification, must be reidentified with its original. The identification is a sole number or a combination of numbers and letters. This
identity may be attached to the animal by tag, tattoo, brand or electronic device (Fig. 2.3.).
2.3. ábra - Fig. 2.3. Tag and electronic devices used for identification.
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2. PERFORMANCE RECORDING
Presently the animal identity number is a maximum of 12 digits, including check digits. The identification is a
base for herd management and genetic evaluation, is essential for tracebility for sanitary reasons and food.
Parentage recording
After servicing a dam, the sire must be recorded. After birth, the sex, the day, the progeny identity must be
recorded. Even with serious administration misidentification can occur. Mainly in double AI. Misidentification
will effect the breeding value both the progeny and its parents’. Parentage can be tested by blood typing,
microsatellites or SNP parentage analysis. The breeding association issues a certificate on which parentage
(usually two generation), date of birth and sex, with the identity number and the name of the breeder is shown. If
there is any genetical defect, that also must be reported. If there is any production record, that may be reported.
Performance recording
Minimum requirements is needed to ensure a satisfactory degree of uniformity of recording and maximum
flexibility in the choice of methods. The performance testing is a systematic collection of comparative
production information. Animals are usually compared within contemporary groups, which a group of animals
that are of same breed, age, sex and have been raised in the same management group. These are also called
adjustment factors.
Reproduction and fertility of male and females are the most important economic trait in each breeding system.
Since environment has got a great impact on these fitness traits, the careful collection of environmental effect is
imperative. Measures used to describe the trait are: days at first insemination (puberty), conception rate, fertility
index, days open, service period, non-return rate at day-56, day-60, or day-90 after insemination, number of
inseminations, calving (lambing, farrowing) interval, survival rate, weaning rate, prolificacy, still birth, dystocia
(calving ease), productive life or longevity. Longevity may be measured, from birth or from onset of production
to the date of measurement of the specific trait for the last time in an animal’s life usually the time of disposal.
Environmental factors are those that effect the trait are usually: herd, year, season, age (or lactation),
inseminator and AI station. In beef cattle or in sheep the scrotal circumference, mating behavior can also be
measured.
Semen can be examined generally and microscopically and quantity and quality. These include the volume of
the ejaculate, the spermatozoa concentration, the proportion of live spermatozoa, the sperm percent forward
motility, morphological abnormalities and semen freezeability.
The mothering ability is accessed thorough behavior (temperament), survival of the progenies, weaning weight
of the litter.
Health traits. Irrespective of the importance, few health traits are recorded. It is generally assumed that
unhealthy animals will not survive, or will be culled due to low production or low product quality. On the other
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hand, it is assessed during conformation judgment. These are somatic cell count, milk fever, clinical mastitis,
number of treatment, locomotion score, lameness score.
Milk recording can take place by method A or B. Method A is the way, where official recording takes place by
a representative of the organization, usually once a month in dairy cattle or sheep. In method B, the records are
collected by the farmer. The devices used for milk collection must be officially approved. The milk sampled is
analysed for fat, protein and somatic cell count. From these data lactation yield is calculated. The ICAR
standard method for calculating lactation yield is:
where M1, M2 are the weights in kilograms of the milk yielded in the 24 hours of the recording day, I 0 is the
interval (days) between the lactation period start date and the first recording date, I 1, I2 are the intervals between
recording dates. Test-day yield is more often used in genetic evaluation. In dairy cattle a 305-day standard
lactation yield is used for comparison. Persistency of milk production is the ability to maintain milk production
at a high level after peak production. Three groups of parameters can be distinguished to describe the trait.
Parameters from mathematical models describing the lactation curve form the first group of criteria. The
Wilmink function is of a mathematical model describing the lactation curve. The function is: y = a + b * t + c *
exp ( -0,05*t ). The parameters are ulinked to the lactation curve: a to the level of production, b to the production
decrease after peak yield, c to the production increase towards peak yield and the factor - 0.05 to the moment of
peak yield, i.e. around 50 days in lactation. Another, way to fit a lactation curve through test day (TD) yields is
random regression. This method makes it possible to estimate the shape of the genetic lactation curve for every
cow by fitting the curve through the test day yields individually for each lactation, with a simultaneous
correction for fixed and random effects on phenotypic performances. The second group that can be
distinguished are measures of ratios between partial, maximum or other yields (e.g. day 60). The third group of
criteria containes measures of the variation of TD yields during the lactation.
Milkability is an expression of milking speed, milking ease or milk flow. This is a trait with an intermediate or
optimum level.
Sheep is milked usually after weaning (after peak yield) and therefore milk yield is smaller than total milk yield
during lactation. The ICAR has not defined a standard lactation because milking very much differs by breed and
area. The recording of the chemical composition of milk is optional for the sheep.
The environmental effects influencing the trait are herd, year, season, lactation (or age or parity).
Weights. The collection of live weights is critical to the analysis of productivity of pig, sheep and beef farms.
Weights are collected: birth weight (within 48 hours of birth, optional), 21-day weight (pig), weaning weight
(100-day weight (sheep), 205-day weight, in beef), finishing weight, slaughter weight, yearling weight, mature
weight (optional). Amongst the weights the weaning weight is the most generally recorded, which is an
indicator of the dam and the genetic potential of the calf for pre-weaning growth. It also serves as an initial
weight for determining post-weaning growth. It also serves as an income if the calf is sold after weaning.
Growth rates are calculated between different defined ages, like pre-weaning growth rate and post weaning
growth rate or test growth rate. The adjustment for the reference performance trait (205-day) is advised as
follows:
RW = ((Wt-Wb)/At)*205+Wb
where: At is the age at weaning in days, Wt is the weight in kilograms, W b the recorded birth weight or a breed
standard.
Visual assessement
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Visual assessement is being taken place by the the mean of linear scoring. Linear scoring is the description of
animal morphology. Within one single anatomical site, linear scoring provides a description of the biological
extremes and the number of intermediates (1-9). The extremes and the intermediates are ordered. A high or low
score has no particular meaning. The scoring should be consistent. In dairy cattle the scoring include stature,
strength, body depth, dairy form, rump amgle, pin width, pasterns, rear leg side and rear view, foot angle, fore
udder attachment, rear udder height and width, udder cleft and depth, front teat placement. In beef cattle these
are: shoulder width, loin width, rump length and width, thigh width, depth, inside and rounding. The judging is
assisted by score cards and trainings which increase the repeatability that is need to be attained within and
between scorers.
Condition scoring provides a means of attaining the desired target condition scores for optimum production and
reproduction. The score ranges usually between 1 (extremely thin) and 5 (extremely fat) with half scores
sometimes use between main scores. The fat cover over the loin area is the most important scoring area, since
changes in fat deposition can be felt.
2.4. ábra - Fig. 2.4. The visual assessment of stature and chest width
(Source: ICAR)
2.5. ábra - Fig. 2.5. The visual assessement of body depth
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2.6. ábra - Fig. 2.6. Assessement of fat cover
(Source: http://www.dpi.vic.gov.au)
Ultrasound imaging has so far been used for the measurement of subcutaneous fat cover and eye muscle area
and muscle depth, as well as the intramuscular fat percent in the longissimus dorsi. Intramuscular fat percent or
marbling is an important meat quality characteristic in certain high priced markets, since consumer ulink it with
outstanding eating quality.
After slaughter measured traits are: back fat, loin muscle depth, carcass weight, carcass conformation and
fatness, pH24, pH48, meat colour. Derived traits are killing out percentage, lean meat percentage, meat bone ratio,
proportion of primary cuts. The primary cuts of beef are chuck steak, rib, brisket, plate, short loin, round and
flank.
2.7. ábra - Fig. 2.7. After slaughter conformation scale of beef carcass
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On farm and central performance testing
"A central performance test is where animals from different herds are brought to one central location where
performance is recorded. The rationale is that observed differences are more likely due to genetic differences,
which will be passed onto offspring, rather than environmental differences, which will not be passed onto
offspring. The goal of a central performance test is to identify genetic differences among animals." cited from
Dr. Dan Waldron, Texas A&M University. Central test stations were established in Western Europe, especially
in Denmark in the 19th century to provide uniform environment at that time, when herd sizes were relatively
low. The advantage of the station test apart from the abovementioned is the expertise and the developed
techniques, which allows many traits to measure. The disadvantage is the cost, the possible pre-test effects
influencing the test results, diseases carried from the farms, restricted number of animals tested and the possible
genotype-environment interactions. During the 20th century the herd sizes increased, so more animals could be
compared in the same environment, more and more techniques became available at relatively low cost.
Statistical techniques, such as BLUP also were developed, which allows the estimation of herd effect, but
randomness is assumed.
Genotype-environment interaction (GxE)
The genotype-environment interaction is a phenomenon where the rank of genotypes changes in different
environment or when the advantage to a particular genotype in one environment is smaller or greater than in
another. Different genes expressed in different environment, or different proteins produced in different
environment. The presence of genotype-environment interaction can be assessed by correlation, analysis of
variance as well. If the correlation of the given trait is lower than 0.8, a GxE effect is assumed, or the analysis of
variance shows a significant GxE effect.
2.8. ábra - Fig. 2.8. Examples for genotype x environment interactions (after Brandsch)
In Fig 2.8. in column I, there is no genotype environment is present, since the rank and the difference between
genotypes is the same. In column 2. GxE is present, the difference between phenotypes decreased in
environment B. In case 3, the rank of the genotypes changed. In case 4. extreme interaction is present. Both the
rank and the difference between genotypes changed. The question is from which environment do we buy
breeding animals? A rule of thumb is to buy from the environment which is the closest to ours. In traits of low
heritability (fitness traits) we observe GxE more frequently. Genotypes here refer to breed, strain, line or even
animals of the same line. Breeds developed in extensive environment have lower requirements for maintanence
and growth than larger breeds developed in intensive environments.
1. Questions
1. Please list the requirements for identification.
2. What is the role of the ICAR?
3. What is the use of conformation?
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4. What environmental factors influence the traits?
5. Please contrast the on-farm and central station performance test.
6. What forms of GxE occur?
2. Lierature cited and suggested
Bourdon M. R (1997): Understanding animal breeding. Prentice Hall, Inc,
Bruce W. (2006): Notes for a short course taught June 2006 at University of Aarhus
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3. fejezet - 3. estimation of Genetic
parameters
Questions
• What can genetic parameters can be used for?
• What are their values?
• How do we predict them?
• Are they related to each other?
• Do they change or stable?
• Are they population and trait specific?
Genetic parameters are used for setting up breeding objecives, choosing selection criterias, for breeding value
evaluation and predicting selection response. During this step of the course in a breeding program, we estimate
covariance components that are used for calculating heritability, repeatability and correlations. The pioneers in
this area were Charles Roy Henderson (1911-1989) and Lenoy Hazel (1911-1992). Methods used for
estimations are analysis of variance, maximum likelihood (ML), restricted maximum likelihood (REML),
derivative free maximum likelihood (DFREML) or Bayes based methods. In ML based estimations we
differentiate fix and random effects. If we want to draw conclusions from the levels of different effects, we treat
the effects as fixed factors. If the factors are the representatives of a population, we treat the effects as random
effects. Models containing both factors, are considered as mixed models. Since genetic parameters are the ratios
of covariance components, which are dependent on environmental changes, variance of the base population and
selection, the recalculation is imperative from time to time, ususally in every 3-5 years.
Heritability (h2)
Heritability expressses the resembelance between parents and offsprings in a given trait. Knowing the
heritability, we can predict the selection response. The heritability represents the correlation between phenotype
and genotype (according to Lerner, the heritability is the squared correlation (h) of the phenotype and genotype),
in another words, the regression of progeny peformance on parent average. The most comon expression, is the
genotypic and phenotypic variance ratio (h2= VG /VP). The total variance (VP) is the sum of the genetic variance
(VG) and the environmental variance (VE). The heritability is that part of the variation, which is controlled by
genetic variation. The genetic variance can be partioned into additíve, dominance (V D) and epistatic (VI)
variance. The total genetic variance then:
VG = V A + V D + V I
the total phenotypic variance is:
VP = V G + V K = V A + V D + V I + V K
(VP is referred to the sample, σ2p is referred to the population).
The value of heritability varies between 0 and 1, or between 0% and 100%. If the h2 of the lactation yield is 0.3,
than the total phenotypic variance is 30% of genetic, and 70% is of environmental origin. The heritability is
classified as: low (h2 < 0.15), moderate (h2=0.2-0.5) and high (0.5 < h2). If the h2 is zero, there is no genetic
variation in the population, e.g. in inbred line, if h2 is 1, the environment does not have an effect on the trait.
According to Wright, h, is the correlation between breeding value and phenotype:
rAP = σ(A,P)/σAσP = σ(A,A + D + E)/= σ(A,A)/σAσP = σA2/σAσP = σA/σP = h
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3. estimation of Genetic parameters
The heritability is trait and population specific. Since the h2 is a ratio, if some of the elements is changing, that
has an effect on the value. Taking a population to a different environment that will change the heritability.
Concluding from the mentioned, the breeding value of an individual can be calculated as: A = σ(P, A)/σ 2P(P - μP)
+ e = h2(P - μP) + e
where A= breeding value; P = phenotypic value; σ2P.= phenotypic variance; μP = phenotypic regression; e =
error. This relationship arises from the fact that, the regression line crosses the average of A and P. If the
breeding value, predicted from the P, and the prediction error is zero, then the error variance is: σ 2e.= (1- h2) σ2A
Higher the heritability, higher is the variation around the average breeding value, h 2(P - μP).
The selection affects allele frequency, that has got an effect on genetic variance. The parent-offspring regression
also changes during selection, so the heritability calculated in unselected population can only be used for some
generation. Two population which has got different phenotypic average, it can not be assumed, that the
difference is of genetic origin. High heritability in one population is not a sign of higher genetic variability
compared to a population of low heritability. The calculation of heritability is based on the resembalence
between relatives, so every formula that expresses the relationship can be used for calculating heritability.
Like:
• the proportion of below and above average parents and their offspring,
• the ratio of selection response and selection differential,
• regression (parent-offspring) between relatives,
• correlation between relatives,
• ratio of genetic and phenotypic variance.
The method of the proportion of below and above average parents and their offspring can be used, if both
parents and their offsprings are raised in the same environment, and their performance is known. h 2 = 2(PnPk)/(Dn-Dk)
where
Pn = the average production of offsprings produce above average,
Pk = the average production of offsprings produce below average,
Dn = the average production of parents produce above average,
Dk = the average production of parent produce below average.
Example: On a dairy farm Pn = 6600 kg, Pk = 6300 kg, Dn=7000 kg, Dk = 5000 kg
h2 = 2(6600-6300/(7000-5000) = 600/2000= 0.3
The ratio of selection responce (SR) and selection differential (SD) can be used if both parents and progeny
performance are known:
h2 = SR/SD
Example: In a beef herd the 205-day weight of the selected parents average is 230 kg, the average of the total
population is 210 kg, the progeny weight of the selected parents is 220 kg, the progeny weight of the total
progeny weight is 215 kg. SR = 220-215= 5 kg, SD = 230-210=20 kg
h2 = SR/SD = 5/20 = 0,25
If the performance of some progeny and that of their parents is known, we can predict heritability from offspingparent regression. We assume that the relationship between progeny and parent performance is linear and the
following equation can be used:
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y = a +b x
where y = offspring performance; x = the average performance of the two parents; b = regression coefficient, a =
intercept.
h2 = b
If only the performance of one parent is available and the performance of the other can not be known, (e.g. milk
production of the bull) then, x = is the performance of one parent, the heritability is
h2 = 2b
(the multiplication with 2, is to compensate the genes of the other parent).
To calculate heritability we organize offspring-parent average pairs in a table and calculate b value:
b = SP/SQ
SP = Σxz- ΣxΣz/n
SQ = Σx2- (Σx2)/n
Example: We know the backfat (mm) of sow, boars and their progeny, which is presented in table 3.1. below.
iI
A
B
1
31
30
X
30.
5
2
27
31
27
4
32
32
27
6
26
31
7
28
28
8
29
31
930.3
26
9
26
32
10
29
25
11
31
29
12
33
31
0
29
29.
0
27
.0
32.
0
.0
5
27
.0
28.
5
.0
0
27
.0
27.
5
29
27.
729.0
75
6.0
79
7.5
81
30
81
0.0
29
.0
85
2.0
.0
30.
0
76
841.0 5.0
1 024.0
102
9.5
28
.0
0
784.0
900.0
.0
78
3.0
812.3 4.0
756.3
30
28.
1 024.0
812.3
32
28.
81
841.0 2.0
.0
29.
31
94
784.0
0
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Xy
5.5
29
3
30
x2
.0
28.
5
y
87
0.0
3. estimation of Genetic parameters
32.
0
Sum
32
350.
0
1
.0
024.4
351 10 238.2
.0
10
258.5
i = rank of parent-offspring
Σxy = 12258.5
A = backfat of the boar
(ΣxΣy)/n = 350 x
351/12
=
10237.5
B = backfat of the sow
SP = 10258.510237.5 = 21
x = average backfat of the parents
(Σx2)/n
10208.3
y = backfat of the progeny
SQ=
10238.210208.3 7 29.9
=
h2 = b= SP/SQ= 21/29.9 = 0.70
Knowing the phenotypic and genetic (breeding) value of individuals, correlation can be calculated. The
heritability is the square of the correlation in this case (h2 = r2fp). Different type of correlations can be used, such
as sign, rank correlation or the ratio of covariance and variances. The difference in methods result in different
heritabilities.
The analysis of variance is suitable to calculate phenotypic, genetic and environmental variance. The following
example demonstrates three genotypes (A1A1, A1A2, A2A2) which are placed in three different environment
(three diet: K1, K2, K3). After the the experiment the phenotype is measured in kg.
3.1. ábra - Table 3.2. Phenotypic, genetic and environmental values of three genotypes
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3. estimation of Genetic parameters
The phenotypic average of the sample is 20 kg, so an individual of A1A1 genotype given K1 diet, performed 26
kg, its phenotypic value is +6. The genetic value is the average phenotypic value of the same genotype. The
average phenotypic value of A1A1 genotype animals 26+24+22, (or +6, +4, +2), is +4. which is the average
difference from the sample mean. Animals performing in environment K1 weighing 26, 22, 18 kg, their
phenotypic value +6,+2, -2, and average +6/3 = +2. We can see that the phenotypic value can be partitioned to
genetic and environmental value. In the case of , A1A1 and K1 is (+6) = (+4) + (+2). The variance is the
average of the sum of the squared diference from the mean. Let us calculate the variance for the example above.
The calculation is shown in table 3.3.
3.2. ábra - Table 3.3. The calculation of variance for data in Table 3.2.
The phenotypic variance is the sum of genetic and environmental variance:
VP = VG + VE , then 15 = 12 + 3
The heritability then.
h2 = VG /(VG +VE)
In the example:
h2 = VG /(VG +VE) = 12/15 = 0.8.
The heritability can be calculated from full-sibs data. Let us have N group of full-sibs (e.g. piglets of N sows),
and in each full-sib groups their are n piglets. In this case the following one-way linear model can be used:
zij = μ +fi + wij
where
zij
= phenotype of the j-th individual born to az i-th family,
fi
= the effect of the i-th family,
wij
= error, which consists of segregation, dominance and environmental factors.
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We assume that wij are not related, there is variance within family (σ 2w), and there is variance between families
(σ2f, or σ2b, or σ2a). We assume furthermore that the variance within and between families are not related σ 2(fi , wi)
= 0, from which it concludes that the phenotypic variance is the sum of the between family and within family
variance.
σ2x = σ2f+ σ2w(FS)
An another important aspect is that the covariance between the individuals belonging to the same group is equal
to the variance between the groups. If we look at the four sibs below, belonging to the same group represent the
family effect and different individual effects.
The covariance of fullsibs
= σ(zij, zik)
= σ[(μ + fi + wij),( μ + fi + wjk)]
= σ(fi, fi j) + σ(fi, wjk) + σ(wij, fi) + σ(wij, wijk)
= σ2f
The equity of the covariance within families and the variance between families makes the connection of the
estimated between family variances
σ2f = σ2A/2 + σ2D /4 + σ2Ec
where Ec = the common family environmental effect, because σ 2P = σ2f + σ2D(FS), and the within family (fullsib
variance) is σ2w(FS) is the following:
σ2w(FS) = σ2P – (σ2A/2 + σ2D/4 + σ2Ec)
= σ2A + σ2D + σ2E - (σ2A/2 + σ2D/4 + σ2Ec)
=1/2σ2A + 3/4σ2 + σ2E - σ2Ec
3.3. ábra - Table 3.4. Variance table for a fullsib design, N families and n individuals in
each family
T
= Nn = total number of animals
df
= degree of freedom
SS
= sum of squares
E(MS) = estimated mean square
The (co)variance components and the heritability can be calculated as
Var(f) = (MSf-MSw/n
Var(w) = MSw
Var(z) = Var(f) + Var(w)
The equation is:
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2σ2f = σ2A + σ2D/2 + σ2D/4 + 2σ2Ec
tFS= Var(f)/Var(z) = 1/2 + (σ2D/4+ σ2Ec)/σ2z
h2 = 2tFS
(The genetic variance is multiplied by 2, since the resembelance between fullsibs is 0.5).
Example: 10 families, 5 fullsibs in each family
Var(f) = (45 – 20)/5 =5
Var(w) = MSw = 20
Var(z) = Var(f) + Var(w) = 25
h2 = 2tFS= 2x 5/25 = 0.4
If halfsibs data are available the heritability is estimated as:
h2 = 4tPHS
(Since the resembalence between halfsibs is 0.25, the genetic variance is multiplied by 4). e.g.
If different paternal halfsib groups performance are available, belonging to the same generation, the variance
between groups is genetic variance (VG or σ2g), the variance within halfsib groups is environmental variance (V E,
or σ2E), the sum of the two is the phenotypic variance (VP = VG + VE, or σ2p = σ2G + σ2E).
Then
h2 = 4VG/VP = 4VG/(VG + VE,)
or
h2 = 4σ2G/σ2p = 4σ2G/σ2G + σ2E)
Example: In an analysis of variance conducted on egg data, the variance between groups was
(Vb or Va) 215, the variance within groups was (V w) 5518.
The heritability is:
h2 = 4 x 215/(215+5518)=0.15
3.1. táblázat - Table 3.5. Examples of heritabilities of some livestock traits (after M.B.
Willis, 1991)
Cattle
Sheep
calving interval 0-0.15
lambs born
0-0.15
litter size 0-0.10
calves born
lambs weaned
0-0.10
pigs
weaned
0-0.15
Pig
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milk yield
0.30-0.40
weaning weight 0.10-0.40
weaning
weight
fat yield
0.25-0.45
fleece weight
0.30-0.40
daily gain 0.21-0.40
fat %
0.32-0.87
staple length
0.30-0.60
feed
0.20-0.48
efficiency
SNF %
0.53-0.83
fibre diameter
0.40-0.70
killing out 0.26-0.40
protein %
0.48-0.88
crimps/cm
0.35-0.50
fat depth 0.62-0.65
C
lactose %
0.28-0.62
medullation
0.34-0.80
fat depth 0.42-0.73
K
feed efficiency 0.40
birth coat
0.59-0.80
carcass
length
0.40-0.87
birth weight
face cover
0.36-0.56
EM area
0.35-0.49
wrinkle
0.20-0.50
leg length 0.46-0.50
0.38
weaning weight 0.20-0.50
eye muscle area 0.40-0.70
daily gain
0.40
carcass lean
0.39
fillet
weight
0-0.08
0.31-0.54
Fitness traits usually have got low heritabilities, production traits have got moderate heritabilities, and traits
associated with product quality have got high heritability.
Repeatability (R)
The heritability and repeatability have got a common background, which is the genetic variance. There are traits
which are repeatedly expressed in different, succesive production cycles, such as milk production numbers of
piglets born, greece fleece weight.
Individual
Milk production in different lactations (l)
1.
2.
3.
average
A
5200
6000
6800
6000
B
4800
6100
5900
5600
C
6000
5600
6100
5900
Examining the performances of an individual in different production cycles, we can observe differences which
are caused by genetic and permanent environmental effects. The permanent environmental effect if the same
effect persists for a long period during the animal’s life. For example an animal is kept in a building during its
life, what is different to the other’s animal building. One effect can be present in one building, but not in the
other. The difference between production cycles is assumed to be caused by temporary environmental effects.
This effect is present only during the given lactation or calving which can be a diseases or nutritional effect or
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worker. The breeder is interested in, how the animal’s performance changes during different production cycles.
This change is expressed by the repeatabilty which can take values between 0 and 1. The permanent variance is
VPE, the temporary variance is VTE. The formula of R is (VG + VPE)/ (VG + VPE + VTE ). The repeatability sets up
the upper value of the heritability, and can be used of no information is available for relatives, only successive
performances are known. If the repeatabilty is high, the correlation between performances in different cycles are
also high, and selection can be carried out in the first cycle, since the difference between animals will hardly
change. From recording point of view, we can save money on recording in later production cycles, because no
recording is necessary.
3.2. táblázat - Table 3.6. The repeatability of some livestock trait
Cattle
Sheep
Pig
milk yield
0.40-0.55
fleece weight
0.50-0.65
litter size
0.05-0.15
fat yield
0.40-0.50
staple length
0.60-0.65
weaning weight
0.15-0.20
fat %
0.50-0.65
lambs born
0.10-0.15
calving interval 0-0.15
birth weight
0.20-0.30
weaning weight 0.40-0.45
Correlation (r)
The correlation is a measure of the relationship between two variables, how the change in one variable causes
changes in another variable. The question is to what extent and in what direction? Linear correlation can be
calculated if the relationship between the two variables is linear. If linearity is not hold, transformation is used
(logarithmic ususally).
The formula is
The correlation has no dimension, and more easly explained than the covariance. The correlation of 0.8 means
that 1 standard deviation unit change in one trait, causes 0.8 standard deviation unit in the other trait. The
correlation varies between -1 and +1. If the covaiance is 0, the correlation is 0.
The classification of the correlation is the following:
low
r < |0,4|,
moderate
|0,4| < r < |0,7|,
strong
|0,7| < r < |0,9|,
very strong
r > |0,9|.
As the phenotype of a the trait can be partitioned into genetic and environmental value, correlations can be
calculated between the phenotypic values of the two trait, the genetic values of the two traits and the
environmental of the two traits. These results in phenotypic (r P), genetic (rG) and environmental (rE) correlations.
The genetic basis of the correlation is the ulinkage and pleiotropy. If the correlation is close to 1, then one unit
standard deviation change in one trait results in one unit standard deviation change in the other trait, meaning
that almost the same genes control the two traits. If the correlation is close to zero, very few common genes
control the two traits. From the environmental correlation we can conclude if the change in the environment
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affects the two trait on the same, or different way. If it is close to 1, means that the change in the environment
affect the two trait on the same way.
The phenotypic and genetic correlations between two traits are different. It is known as a Smith’s rule that
rG=1,2 * rP . We can use as a general rule, that if the heritability of a trait is high, the two correlations are close.
The correlation is used prediction of correlated response and in selection indices. The phenotypic correlation is
important to the farmer, and the genetic correlation is important to the breeder. The genetic correlation is the
heritable relationship between the two traits.
3.3. táblázat - Table 3.7. Genetic correlations between some livestock traits (according
to Legates, J.E and Warwick, E.J., 1990)
Trait
Correlation
Every species
Growth rate between growth stages
0.30 – 0.50
Food conversion rate/growth rate
-0.40 - -0.70
Cattle
Milk yield/Milk fat%
-0.10 - -0.60
Milk fat%%/Milk protein%
0.50 – 0.60
Birth weight/weaning weight
0.20 – 0.40
Lean meat/slaughter weight
0.20 – 0.40
Pig
Weaning weight/growth rate in fattening
0.10 – 0.25
Growth rate/backfat
-0.10 – 0.10
Feed conversion rate/backfat
0.25 – 0.35
Lean meat/backfat
-0.60 - -0.80
Sheep
Grease fleece weight/clean fleece weight
0.65 – 0.75
Clean fleece weight/fibre diameter
0.30 – 0.40
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Poultry
Egg weight/body weight
0.25 – 0.50
Egg number/body weight
-0.20 - -0.60
Egg number/egg weight
-0.25 – -0.50
We can see, similarly to the heritabilty, the correlation between two traits is not stable. Since the correlation is a
ratio, change in any component, will change the correlation. This is why, correlation needs to be recalculated
periodically. Amongst the three types of correlations, the environmental correlation is the most sensitive to
changes, while the phenotypic, then the genetic correlation is less sensitive. We can not say that, positive
correlation is favourable, and negative is unfavourable. The economical importance explaines the usefullness of
the sign of the correlation. Like, the positive correlation between milk yield and protein yield is favourable,
while the positive correlation between dystocia and birth weight is unfavourable.
3.4. táblázat - Table 3.8. The phenotypic, genetic and environmental correlations for
some traits (According to Legates, J.E and Warwick, E.J., 1990)
rP
rG
rE
Milk yield/fat%
-0.26
-0.38
-0.18
Milk yield 1st /2nd lactation
0.40
0.75
0.26
Growth/backfat
0.0
0.13
-0.18
Growth/food conversion
-0.66
-0.69
-0.64
Body weight/egg weight
0.33
0.42
0.23
Body weight/egg production
0.01
-0.17
0.08
Cattle
Pig
Poultry
In a population there can be some individuals, for which the relationship calculated for the population does not
hold. These individuals the so-called correlation-breakers. which is the result of crossing-over. More of these
individuals can be found if the traits are loosly correlated. If this phenomena is favourable. we keep the
individual for breeding. For example a large weight beef cow with easy calving.
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In a breeding program the correlation is first used to set up the breeding objective. If the traits choosen are
unfavourable correlated. we need to form specialised lines. like dam lines and sire lines. or we need to be
satisfied with moderate improvement of the two traits. Specialised lines then crossed to exploit heterosis. Fitness
traits are usually unfavourable correlated with production traits and production traits unfavourable correlated
with product quality traits. These are related to conflict in resource allocation.
1. Questions
1. Please list the methods of calculating heritability.
2. What classification can be made for the magnitude of the correlation? Is there a relationship between the
strength of the correlation and the correlation breakers?
3. Is there a relationship between the direction of correlation and specialised line selection?
4. What deceision can be made regarding data recording in the kwonledge of repeatability?
5. How the magnitude of the heritabilty effects your choice in breeding objective?
2. Suggested literature
Bourdon M. R: (1997): Understanding animal breeding. Prentice Hall. Inc.
Bruce W. (2006): Notes for a short course taught June 2006 at University of Aarhus
FALCONER. D. S. (1990): Introduction to Quantitative genetics. Third ed. Longman Group (FE) Ltd.
WILLIS. M. B. (1991): Dalton’s Introduction to Practical Animal Breeding. Blackwell Scientific Publication.
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4. fejezet - 4. breeding value
evaluation – BLUP
Questions
• What is breeding value?
• How can we predict?
• What information we need for prediction?
• How reliable is it?
In purebreeding. the improvement of quantitative traits is based on additive gene effects. which are predicted in
breeding value. This breeding value is always compared to a base or average, so its magnitude and sign is
relative to the base. The dominance and epistatic effects are utilised in crossings. The aim of the improvement of
evaluation models to access the genes expressed at a certain age, and to separate environmental effects from
genetic effects. For example in milk production we used lactation model in the past, now we use test-day model,
which makes a better separation of environmental effects from the genetic effect. The application of linear
models for separation the genetic and environmental effects is first applied by C.R. Henderson, which is named
BLUP (Best Linear Unbiased Prediction) The models require covariances as inputs, which are also estimated by
the same linear model. The model requires the knowledge of significant environmental effects and the
knowledge of relatives. More relatives and more significant environmental effect is known, the precision of
prediction is higher.
Best Linear Unbiased Prediction – Variance structure
The model used for prediction can be described in several forms. The polinome form can also be used. For
example:
Non-linear predictions can be transformed into linear forms such as:
The linear models have the following advantages:
• Lower order coefficients are more important than higher order coefficients
• The model has not not necessary got a biological background
• Even higher order polinomes can be approximated with lower order linear models
• Purely desciptive
• Makes the hypothesis testing of model factors possible
• Restricted prediction can be applied
Linear models
The characteristics of linear models:
• Can be used to approximate highly nonadditive genetic systems, including dominance and epistasis
• Predictive ability is fairly good, even if underlying mode of gene action is nonadditive
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• Linear models extensively used in animal breeding
The general form of linear model:
Where Y stand for the trait. X stands for the independent (environmental) effects. b stands for the coefficients of
the independent effects. ε is the random error not explained by the environmental effects. The equation above
applied for every individual in the estimation:
These equations can be written in matrix form:
which can also be written in a short version Y = XB + ε form.
The Ordinary Least Squares. OLS method is used for the solution of the system. For the independent (X) effects
the solution is a value without error. The residual error values are random, independently and identically
distributed with the average of 0, and variance of σ2. If the error follows the mentioned criteria, the error
distribution from which each observation is
sampled is the same, the values in the variance matrix above and below the diagonal is zero, that means no
environmental correlation exists.
The solution for the least squares means is the following:
Take the residual sum of squares belonging to the predictions.
The residual is the difference between the individual observation and the prediction made with the linear
equation.
Since the predicted value can be calculated with the following formula
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this substituted into the previous equation:
The squared error in matrix form with equation substituted:
We need to find a solution where the residual least squres is the smallest. To get the solution we take the
derivate of the equation and we get the following form:
Take all the elements of this equation to zero and solve the equation. The normal equations for the equations
above are:
that is:
The B vector can be calculated. if both sides of the equation are multiplied with X’X matrix, so we get:
The variance of B vector:
By the coefficients calculated it is possible to estimate the dependent variables and their variances:
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The method of Generalized Least Squares (GLS)
The difference betwen the OLS and GLS is that, the residuals are not independent, their variance is (V(ε)) and
the values around the diagonal can be different from zero. Environmental correlation can exists.
The solution of the generalized least square:
The maximum-likelihood method
The maximum-likelihood method treats the independent variable in the same way as the OLS or GLS. The
difference is in the calculation of residuals. The variance of residuals is as before (V(ε)), V matrix, with zero
mean, altough the distribution of residuals is normal. The maximum-likelihood value can be calculated with the
following equation:
The task is to maximise „b”, so taking the derivative to zero, then solve the equation. In equation it follows:
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Example: By using the values below, let us calculate the coefficients by least squares means and generalised
least squares. Let us compare the estimations and their standard errors.
After using the appropriate equations we get the following predicted values:
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The t value obtained by least sqaures means (OLS):
The results obtained by general least squares means (GLS):
The following conclusion can be drawn: using the inappropriate error structure inadequate conclusions could
result in drift. To overcome the bias, we need to include the proportional drift variance as F and the additive
genetic variance. The BLUP will give partial solution to the probelem.
Best Linear Unbiased Prediction – The prediction
Let us consider the error structure from a different point of view. We can calculate the error variance with a
matrix
and the elements of the matrix are the following:
It can be seen that the distribution of the error from which the sample is drawn is the same:
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This distribution is altered by inbreeding. Furthermore only the diagonal containes values different from zero so
these residuals are independent. If individuals are relatives, these values will be different from zero. The general
least squares means method solves the problem by changing the variance and the correlation between the
residuals. The following questions need to be answered:
How can we correct for
• environmental effects that are not controlled.
• the effect of herd.
• the effect of year.
• the effect of litter.
Summarizing: we need to answer the problem regarding the correction for fixed effects.
The effect of herd is not a problem in a balanced design. Every families need to be present in every herds. A
previous solution to the problem was the contemporary comparison. A problem arises, if the better herds also
have better genetic background.
The fix effects needs to be corrected for genetic differences and the random effects needs to be corrected for
fixed effects. To simultaneously correct for fixed and random effect the independent variables were separated.
The fixed factors is marked as Xb, while the random variables marked as Zu. The relationship matrix is included
in the random effects.
The characteristics of fixed factors are that those express their effects only on the given level. Classical
examples are herd, year, season, parity and sex. The random effects can be considered as random samples of a
distribution, and express their effect in the population where the samples were drawn from.
The mixed model in matrix form: Y = Xb + Zu +e
The variances of the mixed model:
The working out of BLUP by Maximum-likelihood derivation
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The error vector from equation Y = XB + Zu + e is: e = Y - XB - Zu
To substitute it into equation ln(L):
The solution of the equation is:
The derivative of this solution according to b:
What follows:
The derivative of this solution according to u:
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Furthermore:
After these solutions the mixed model equations can be written as:
In matrix form:
It is important to note that it is not necessary for Y (the measurement) to be normally distributed. It can be
shown by alternative BLUE (Best Linear Unbiased Estimation) prediction techniques, the same solution can be
obtained without the assumption of normality.
Further simplification can be made in mixed models. Assuming additive gene effects
Take the following example: The five relatives have got their performances in brackets:
The mixed model matrix is as follows:
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To fit into mixed model matrix form:
To relationship matrix with the relatives before:
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To include the parts into the original equations, we get:
By solving the equations the estimations are:
b = μ = 8.3018868, the solution for individuals in the A matrix (the breeding value),
If only
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We can calculate the variance of estimations using the mixed model equations. The inverse can be partitioned
into part matrices:
The prediction error variances for the example above:
We meet missing values several times in breeding value evaluation. For example in sex-ulinked trait. We
modify the example above:
As we see animals 2 and 5 have missing values, they are males. Irrespective of the sex-ulinked trait, we want to
predict their breeding value. The mixed model equations will change:
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After solving the equations we get the following solution:
b = μ = 7.6153846, for the individuals.
The limitation of the BLUP model
• It is assumed that the traits are controlled by several genes and several alleles.
• It can not be applied for traits controlled by few genes.
• It is assumed that the variance is stable.
• The models have to be correct. Incorrect models cause more harms. In this case mass selection should be
applied. False data cause false result. Tipical animal model assumes the additivity and independence of the
residuals.
1. SELECTION AND SELECTION RESPONSE
Questions
How selection change the population mean?
How the change can be expressed?
Does selection in one generation affect the next generation?
In quantitative genetics we differentiate short term and long term selection. If we want to predict the response in
some generations the genetic variance and the intensity of selection is usually enough for making the prediction.
During selection the initial gene frequency will significantly change, so the initial genetic variance will also
change and longterm prediction can not be made. We need to differentiate the effects caused by selection within
generation and between generation. The change within generation, is the difference in the state of the population
before selection and after selection. This called the selection differential, while the between generation change is
the selection response. Selection can change the distribution of phenotypes, and we typically measure this by
changes in mean. This is a within-generation change. Selection can also change the distribution of breeding
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values. This is the response to selection, the change in the trait in the next generation (the between-generation
change).
The selection differential S measures the within-generation change in the mean
S = m* - m
The response R is the between-generation change in the mean
R(t) = m(t+1) - m(t)
4.1. ábra - Fig. 4.1. The presentation of within and between generation change
The selection differential is a function of selection intensity and phenotypic standard deviation. The selection
intensity
is the ratio of selection differential and the phenotypic standard deviation. The intensity is a direct function of
the proportion selected (Fig. 4.2.).
4.2. ábra - Fig. 4.2. The selection differential and the proportion selected
To ulink the selection differential and the selection response we use the parent-offspring regression:
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This regression equation holds for every parent-offspring pair. The expected difference for selected and
unselected parent average is:
Similarly to the progeny of selected parents: E[yI]=mI. After averaging we get:
This shows that the heritabilty is the ulink between selection differential (within generation change) and
selection response (between generation change). If heritability is close to zero, the selection response will also
be close to zero, irrespective of the magnitude of selection differential. There are situation, where the selection
intensity is different in the two sexes. Since both parents equally contribute to the genotype of the offspring the
selection differential can be written as:
This relationship holds for prediction of one generation selection response. To extrapolate it to more
generations, its validy depends on:
• the accuracy of h2
• the similarity of environments over generations
• the genetic similarity of the population, where the heritabilty was estimated and the population, where the
selection takes place.
The last point usually can not be hold, since selection changes gene frequancy, that will change heritability, so
response can be predicted for only one generation in practice.
We can give a general form to selection response:
So SR=h2S can be written as
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form.
Since h is the correlation of phenotype and estimated breeding value h=r PA. This shows that how accurately can
we predict the breeding value from the phenotype, and this can also be used as a measure of accuracy of
selection. The selection response then can be expressed with the function of accuracy:
So the selection (or genetic) response can be explained as a product of selection intensity, accuracy and genetic
standard deviation.
Selection response = Selection intensity * Accuracy * Genetic standard deviation
The selection response what we presented so far is achieved during one generation of selection. In livestock
breeding many generation live together for many years and produce progenies. To calculate genetic response per
year, the generation interval needs to be considered. The generation interval is the average age of parents at the
birth of progenies (GI).
Example: Let us calculate the generation interval for the population age structure below (GI m. GIf)
Age (years)
2
3
4
5
Total
Number of sire
60
30
0
0
90
600
100
40
1140
Number of dam 400
Incorporating the generation interval into the formula:
A possible increament of selection response is to decrease the generation interval by breeding young animals.
The only problem is the relationship between generation interval and selection intensity. In unipara species if we
replace old females intensively with young ones, the generation interval will increase, on the other hand
selection intensity will decrease. The aim then to optimise the ratio for each situation. A breeder can intervene
into selection intensity, generation interval and accuracy. If we keep an animal in the herd for a long time, the
accuracy of selection will increase, since more information will be available about the animal. on the other hand,
the generation interval will increase. By the use of reproduction technology (artificial insemination, multiple
ovulation and embryo transfer) the selection intensity can be increased. The application of these techniques on
the other hand may increase inbreeding and decrease genetic variance.
The most used selection method in plant and animal breeding is directional selection. In directional selection
only those individuals are kept whose performance are above the threshold, in positive selection, or below, in
negative selection (Fig. 4.3.).
4.3. ábra - Fig. 4.3. Directional selection
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In directional selection we can either choose the replacement according to the proportion selected or above (or
below) the truncation level (T). To calculate selection differential in both cases we need to know the average of
the unselected population (µ) and the selected population (µ*). The selection differential can be expressed as:
where T is the truncation point, p is proportion selected for breeding, Φ(x) is the density function of normal
distribution at the value of „x”.
If we transform
according to normal distribution and substitute it into the selection intensity formula we get the the following:
To approximate the selection intensity formula there are several mathematical solutions. Assuming the
normality of the trait:
This approximation works appropriately within 0.0004 and 0.75 proportion. Outside this interval a different
solution is suggested. The most precise approximation is:
If only small proportion is selected the previous equations overestimate the selection differential (i). For traits
which take discrete values continuous underlying model is used (on a liability scale). which fits to the trait (Fig.
4.4.). If the value of the background variable is below the threshold the trait is not present. Let μ t is the average
of the underlying variable, qt is the frequency of the individuals expressing the trait in the t-th generation. If
linear parent-offspring regression can be fitted to the underlying variable, there is no epistasis, genotypeenvironment interaction and correlation, then μt+1=μt+h2St. The selection differential here holds only for one
generation, since selection differential will change in the next generation. The problem is to estimate μt from the
observed frequency.
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4.4. ábra - Fig 4.4. Seletion for threshold trait with T threshold level (after Lynch and
Walsh).
If the underlying variable follows normal distribution we can choose a scale, where the threshold value is T = 0
and its variance is 1. In this case we get the average of the underlying variable as
where z[p] is the standardised normal value. If 5% of a large population express the threshold trait then μ = -z[0.95].
The critical values belonging to this from the normality table are P(U < 1.645) = 0.95, then -z[0.95]=1.645, and μ =
-1.645. The selection differential for threshold traits will be positive if frequency of underlying variable of the
threshold trait is higher than in the unselected base population. The maximum response can be obtained only if
those individuals are selected which phenotypically express the trait.
4.5. ábra - Fig. 4.5. Selection differential and frequency of liability in thershold traits
(after Lynch and Walsh. ). The intitial frequency is 0.05. the heritabilty is 0.25.
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The parent-offspring regression is affected by epistasis, genotype-environment interaction. Altough the parentoffspring regression is linear, it’s value can significantly differ from h 2/2, influencing the predicted response. For
example in case of epistasis and parent-offsping environmental correlation we get the following equation:
Assuming linear parent-offspring regression and both parents’ performances are known, the selection response
in the next generation is:
which can significantly differ from h2S. So what is the reason we pay so much attention to the heritability? The
reason is that the breeder is interested in the stable part of the selection response. The epistasis and the common
environment (parent and offspring) increases the variable part of the selection response, but when selection is
ceased, their effects are diminished. The gene frequency remains stable supposing the the drift and mutation is
negligible in the population, not taking acccount on inbreeding. So the permanent part of the selection response
is h2S. During inbreeding
and other non-additive variance components are also influencing the selection response.
In additive-additiv epistasis. assuming normal distribution of phenotypic values. the selection response is:
It seems to be logical. assuming that after n generation of selection the cumulative selection response is n times
the equation above. Although any increase is only temporary. since it is ulinked to genetic ulinkage that breaks
after recombination. In the experiment of Griffing (1960) where two ulinked loci were assumed (recombination
rate c) the selection response after one generation of selection then τ generation without selection is:
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which converges to h2S. The formula shows that the probability that favourable alleles will be present after one
generation of selection remains unchanged. So after τ generation we choose in (1-c)τ proportion favourable
alleles. If τ=0 the recombination will be unchanged. Concluding from the previous relationship the cumulative
selection response after t generation of selection, assuming stable selection differential:
where RAA(t) stands for the additive-additive epistatic part of the selection response. In case of selection after t
generations followed by a τ generation ceased selection, the selection response is:
which converges to SR=th2S after many τ generations, which agrees to the equations of the selection response.
The presence of epistasis results in a curvilinear response in the first generations if
is large enough. It needs to be emphasized that to predict the stable part of the selection response we need the
precise estimation of heritability. Using parent-offspring regression we usually overestimate the cumulative
response since heritability in includes
The maternal effect can distort the calculated response. It can result in opposite response. According to Falconer
the maternal effect is the linear function of the mother’s phenotype (z mo), so M=mzmo and the phenotype of the
individual is
The model also called as the diluting model since the effect of the mother is dimishing in some generations.
Parameter m is the regression of the mother’s phenotype on progenies phenotype, which can be estimated as a
difference of mother-progeny and father-progeny equations. The value of m can be negative, which results in
opposite response. Let us assume that the distribution of parents’ and progenies’ phenotype and breeding value
are multivariate normal. Furthermore the epistasis is absent and the phenotype of the progeny of which mother
is zmo.
where Amo and Afa are the breeding values of the parents. Let us take the selected parents’ average, then t+1
generation average is:
where A*fa(t) and A*mo(t) are the average breeding value of the selected parents, μ*mo(t) is the average phenotype
of the selected mothers in generation t. Using the equation of breeding value related to phenotype:
from which the breeding value (A) of an individual phenotype z can be predicted. The expected breeding value
of the mother can be written A*mo(t):
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where Es() is the expected value of the selected parents. We can predict the value of the father A *fa(t). If the
maternal effect is missing, bAz = h2. Furthermore, the dilution model generates a magnitude of
covariance between the maternal effect (M) and the breeding (A) which modifies the covariance between the
individual (z) and its breeding value (A). The regression equation changes to
Starting from an unselected population the selection response after one generation selection is:
Selection changes gene frequency. In a two-allele system (A1 and A2) the genotypes and their relative fitness:
Genotype
A1A1
A1A2
A2A2
Fitness
1
1+s
1+2s
This is an example for additive fitness. With this fitness value for every A1A1 genotype progeny there is 1+2s
A2A2 progeny. If q stands for the frequency of A2 allele before selection, the change in q after selection is:
So with the fitness values above the changes of favourable allele frequency is proportional to s. In finite
population the effect of drift is larger than the effect of selection. When
the changes in allele frequency rather depends on genetic drift than selection. In this cases the favourable allele
could easely disappear due to drift. Let us take an example where the locus has an effect on z trait and assuming
that the genotypes contribute to the trait on the following manner:
Genotype
A1A1
A1A2
A2A2
Contribution
0
a
2a
In the trait with phenotypic variance of
where the the intensity of selection is i the additive fitness values are the following:
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According to this relationship the change in allele frequency depends on i selection intensity and the relative
effect of
on the trait. As expected, the loci which has got a large effect on the trait, is exposed to more selection pressure
and changes in frequency than loci with small effect. Furthermore we need to consider if
then the effect of selection is smaller than the effect of drift. So some favourable QTL allele can disappear due
to drift if their effect
and selection intensity (i) and effective population size (Ne) are relatively small. Generally if the loci
dominantely influence the trait the changes in fitness is:
Genotype
A1A1
A1A2
A2A2
Contribution
0
a(1+k)
2a
Replaced fitness
1
1+s(1+h)
1+2s
where the replaced fitness
and h=k.
The selection changes genetic variance so as the heritability and selection response. Firstly it changes allele
frequency. If the effect of loci on the trait is very small the effect of selection on allele freqency after some
generation is negligeble. Altough during selection ulinkage could be created between loci (correlation) that
quickly result in changing of variance. Let us assume the change in variance within generation is
After one generation of selection the change is:
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Every change in variance is ulinked to additive genetic variance. If V a stands for the additive genetic variance
before selection the change after one generation of selection:
where VP is the phenotypic variance before selection. The heritability then changes to:
The directional selection decreases the variance the heritability slowing down the response. This phenomena is
called the Bulmer effect.
In directional selection the largest decrease in variance happens in the first generations before reaching an
equlibrium state. In disruptive selection though the variance increases before reaching an equlibrium state. In
multitrait selection the response depends on the correlation between the traits. We differentiate between
phenotypic correlation (correlation between phenotypic value –that is measured) genetic correlation (correlation
between breeding values of the traits) and phenotypic values (the difference caused by environment on the two
traits). The correlations can be calculated as
The relationship between correlations is shown in Fig. 4.6. The phenotypic correlation is r P . the genetic
correlation is rA and the environmental correlation is rE.
4.6. ábra - Fig. 4.6. The relationship between correlations.
Correlated response
When genetic correlation exists between two traits, selection for one trait will change the other trait. In these
cases we can say about correlated selection response. We calculate the selection response using regression
equation. If we select for X trait the response in Y trait is the regression coefficient of breeding value in Y trait
on breeding value in X trait. The calculation of the regression coefficient:
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If phenotypic correlation exists between the two traits selecting fot trait X and obtaining selection differential
we can also observe selection differential in trait Y within generation.
The mean of a trait can be changed in two ways:
• either by direct selection (RX).
• either by indirect selection as a result of correlated response (CRX).
The magnitude of the change in mean can be calculated with the following formula:
From the equation it can be concluded that correlated response is larger, if i Y*rA*hY > iX*hX or
• the heritability of trait Y then that of trait X and the correlation between the two traits is high. This becames
important if data recording for trait X is difficult comapared to trait Y.
• if trait Y can be measured in both traits and larger selection intensity can be achieved while trait X can be
measured in one sex only.
In multitrait selection. selection responses and all correlated responses need to be considered by using
phenotypic and genetic correlations. Let us take n traits for which selection is applied, the selection differential
vector for the traits is:
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Determine the phenotypic and genetic correlation matrices P and G, where element ij is the covariance of trait i
and j. The main diagonals are the variances. In case of two traits:
Let R is the column vector of the selection responses, where the i-th element of the vector is the response in trait
i Ri .
The equation of the selection response then:
R*G*P-1*S
This equation is often named as multidimensional selection response equation. We can remember that the
response in single trait selection can be calculated as
In multidimensional case (co)variances replace the respective phenotypic and genetic variances applying inverse
matrices and multiplication.
2. Questions
1. What is the difference between OLS. GLS and ML?
2. What are the fixed and random factors?
3. What is the advantage of BLUP?
4. What are the limitations?
5.
Calculate selection response for the two traits. if
a. we select for trait 2. and S2=10
b. we select for trait 1. and S1=10
c. S1=5. S2=5 (applying the multitrait equation).
3. Suggested literature
MRODE, R.A., THOMPSON, R. (2005): Linear models for the prediction of animal breeding values. CABI.
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5. fejezet - 5. Quantitative traits of the
Poultry
Questions
• What type of melanins can be differentiated?
• What sort of genes have got action on feathers?
• Why single inheritance is important?
Poultry, when compared to other livestock have unique anatomical and physiological characteristics such as:
high body temperature (40.5°C to 41.5°C) high pulse rate (300 beats/minute while at rest), high respiration rate
(14 to 22 exchanges per minute while at rest), high rate of food passage (2.5 hours for an egg-laying hen), fusion
of certain bones to provide rigidity for flight and adaptation of forelimbs into wings.
The functions of the integumentary system (skin and its appen-dages) are protection, regulation of body
temperature, flight and development of secondary sex characteristics. Two general type of pigments can be
differentiated: the melanins and carotenoids. Melanins are responsible for feather coloration and the dark
pigments of the skin and connective tissue. Eumelanin is the pigment of black and blue feathers, eye, skin and
connective tissue. Pheomelanins is the pigment of red-brown and buff-colored feathers. Melanin is produced by
melanocytes, which arise from the retinal and iridial pigment epithelia. The carotenoid (fat soluable xantophyll)
provides the yellow coloration of the skin, egg yolk, body fat, shanks and beak. Xantophyll is not synthesized by
the poultry and must be provided in feed as yellow corn or alfalfa leaf meal. Males and non-lying females
deposit the xantophyll into body reserves but laying hens transfer the ingested xantophyll into egg yolks.
Feather
The polymorphism of the E locus determines the zonal distribution of the black melanin. Adult phenotypes
associated with the alleles: E – extended black. ER – birchen. eWh – dominant wheaten, e+ - wild-type, eb – brown,
es – speckled, ebc – buttercup, ey – recessive wheaten. The approximate order of dominance is
E>ER>e+>eb>es>ebc>ey. In addition to these alleles feather eumelanizing melanotic gene (Ml) gene also plays an
important role. Several genes exist such as eumelanin restriction (inhibitor) factor, such as Columbian (Co),
dark brown (Db), mahogany (Mh).
The silver (S) and gold (s+) color alleles are sex-ulinked alleles are useful for commercial crosses to determine
chick sex at hatching of brown egg layers in the world. The degree of dominance of S seems to differ in
different matings. S is unable to suppress pheomelanin. Genes such as blue (Bl), lavender (lav), pinkeye (pk),
red-splashed white (rs) have a general dilution effect on the plumage and their effect are incomplete dominant or
recessive.
White plumage may be accompanied by different degrees of melanisation of other tissues, which are
economically desirable to the meat industry since they leave no residual melanin in the follicle after feather
removal. Genes that result in white plumage color are dominant white (I), dun (ID), recessive white (c), redeyed white (cre), recessive albino (ca), imperfect albino (sal).
Feather distribution is also affected by different genes. The naked neck (Na) is autosomal gene with incomplete
dominance. The apterylosis (Ap) caused by an also autosomal dominant gene. The Ap gene is largerly lethal
before 15 days of age. The recessive scaleless (sc) gene also causes nakedness. Variation in feather length are
caused by genes such as crest (Cr). muffs and beard (Mb), vulture hocks (v), long tail (Gt. mt).
The structure of the feather can be altered by different genes, such as feather structure (Ha – hard and soft
feather), frizzling (F. mf). silkiness (h), abnormal feathering (af), flightless (Fl), fray (fr), wolly (wo).
Also the growth rate of feathers, although the normal growth is under control of environmental and polygenic
factors, some genes have got dedicated influence. The slow feather growth (Kn. Ks. K) is sex-ulinked and
dominant to the wild-type raid growth feather. Among stocks of rapid feathering (k +/k+ and k+/-) socalled
retarted-tardy feathered (ts. t) birds occour.
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Comb
Redness and size of comb are important indicators for sex maturity. Pullets with bright red, upright and big
comb are considered first-class quality chickens
Single comb (+) is the wild type. Within single comb category three sub-categories are known. Spike blade
comb ends in a single spike instead of the usual broad oblong blade (sb. Sb +). Side springs are extra spkies
laterally. Multiplex combs are several (three-five) combs along the head. The single comb is a characteristics of
three junglefowl species (Gallus gallus. Gallus sonnerati and Gallus lafayettei).
Rose comb is inherited completely dominant is a breed characteristic of a dozen breeds. R/R males are poorly
fertile. Within the rose comb category rugged and smooth comb (He +, hel) can be distinguished. These traits can
be recognized on even day-old chicks.
Pea comb (P) is also a breed characteristic. It is sometimes referred to as triple comb. This comb type is under
the control of an incompletely dominant autosomal gene.
The walnut comb (R + P) is a complementary interaction of the rose and pea genes. The walnut comb is smaller
than either the rose or pea comb.
Body size
There exists a dominant sex-ulinked dwarfism (Z), a recessive sex-ulinked dwarfism (rg) and a sex-ulinked
dwarfism (dw, dwM, dwB). This last gene has got a much greater dwarfing effect than the previous ones. Dwarfs
are healthy, viable and their fertility and hatchability is as good as normal birds. Autosomal dwarfism (adw) is
also present in poultry.
Lethal mutation
Several chicken mutant loci have shown to have lethal effects. Lethality can be inevitable (obligate) or
dependent upon environmental factors (facultative). Early embryonic lethals for example the recessive white
lethal (l), blood ring (blr), early sex-ulinked lethal-Bernier (sex), prenatal lethal (pn) and ladykiller (lk). These
later three are sex-ulinked. Polydactylous embryonic lethals are diplopodia-1, -2, -3, -4, -5, splitfoot, eudiplodia,
talpid-1, -2, -3. Hypodactylous embryonic lethals are wingles (wg), wingless-2 (wg-2), limbless (ll), stumpy
(stu), coloboma (cm). Facial embryonic lethals are duck beak and Donald duck (dck, dd-2, dd-3), missing
maxillae (mx), missing mandible (md), missing upper beak (mub), perocephaly (per).
1. Questions
1. How would you detect. or avoid lethal genes?
2. Why its knowledge is important?
2. Literature consulted
CRAWFORD. R.D. (2003): Poultry Breeding and Genetics. Elsevier.
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6. fejezet - 6. QUANTITATIVE
POULTRY TRAITS. PARAMETERS
AND HERITABILITY
Questions
• What is the importance of the poultry industry?
• What has the industry achieved?
• In what circumstances can we apply molecular techniques?
• How poultry traits are heritable?
• How poultry traits are correlated?
Importance of the poultry industry
Consumption of poultry meat and eggs is continuously increasing. The reason is that, it provides cheap and
easily digestible protein. The poultry convert feedstuff to food efficiently. As indicated below, boilers have the
most favourable feed conversion ratio.
6.1. táblázat - Table 6.1. The feed conversion ratio of different species
Species
Feed/ Grain
Cattle
6.5 – 7.9
Sheep
6.3 – 7.1
Pig
3.1 – 3.9
Broilers
1.8 – 2.2
Turkeys
2.5 – 3.2
Chicken has the most favourable grain/weight conversion factor, followed by turkey, pork and beef. The poultry
industry is dynamic, short period is required for growth and marketing, it can adjust rapidly to changing
economic factors. A strong feeding industry supports the poultry industry, the grain can intensively be grown.
Because of the short production cycle the industry can shortly recover. Other livestock industries require longer
length of time from birth to market (e.g. cattle). Meat animals must be fed for a long period of time before a
usable product is obtained. Products from meat animals are restricted to final market weight. By-product feeds
fed to poultry: distillers grains, which is not used for human consumption. Layers provide a continuous source
of food and produce several times its weight in eggs. Vegetarians consume eggs. In some countries meat eaters
are the minority either because of financial or religious reason and egg consumption is affordable and
acceptable. Poultry products are relatively inexpensive. Poultry meats are one of the best meat buys in the
supermarket. The poultry manure used as fertilizer in organic farming, even at premium price, and rich in
Nitrogen and organic material. Poultry producers have a global perspective, although there are many potential
competitors. but there is a huge potential market. Of all muscle meats, chicken remains the most affordable and
its versatility makes it an appealing option for food service operations. The overall perception of chicken is a
healthier protein option and it is perceived as a sustainable industry. Chicken versatility in terms of flavouring is
a major plus: using marinades and seasonings can be used to manipulate flavour that easily can be adapted to
consumer preferences. Global chicken meat output increased by 27.5 million tonnes between 2000 and 2010,
equivalent to an average annual growth rate of almost four per cent 2012 by the Food and Agriculture
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TRAITS. PARAMETERS AND
HERITABILITY
Organisation (FAO) at 103.5 million tonnes represents a poultry’s share of global meat production (excluding
fish) to a record near 34 per cent. The largest producers in the world are China the countries of the former Soviet
Union and the United States. Major players for broiler breeders are the Aviangen (Arbor Acres. Ross), CobbVantress (Avian, Cobb 500), others (Hubbard, Indian River). Dominating Layer Breeders are Hyline ( ~ 40%)
(Hyline Brown, Hyline W36), Lohmann (Lohmann Brown), others (ISA Brown, Hisex).
Pedigree selection in broilers are for growth rate, feed conversion, livability, ascites resistance, heat resistance,
eviscerated yield, part and meat yield, carcass fat, leg and skeletal strength, breast conformation, degree of
feathering, feather and skin color. Since the early 1990s the meat output per breeder is a dominant indicator of
broiler breeding succes. The majority of feed is consumed by the slaughter generation (95%), so selection goals
favour growth, feed conversion efficiency and carcass quality in the slaughter generation with less emphasis on
reproductive traits in the breeder generation. It is known that selection for two negatively correlated traits will
reduce fitness.
Growth is a dynamic process that exists from conception until maturity and described by a sygmoid curve.
Tissue growth priority and nutrient allocation follows as such: nervous, reproductive, skeletal, muscular and
adipose tissues. The level of nutrition not only influences the development of various tissues, but also causes
variability in the development of some tissues than others influencing meat composition. As the animal matures,
the ratio of fat to protein increases. Energy contents of lean meat and fat are about 4.8 and 39 KJ/g respectively,
so the ratio of weight gain to retained energy declines thorought growth. Measures of growth are body weight at
a specific age, body weight gain during a given interval (which is highly correlated with other weights and gains
during growth) and growth curves. The growth curves can be characterised by four phases: an accelerated
growth phase after hatching, inflection point coincident with maximal growth rate, a deccelerating growth phase
and mature weight phase. Growth is moderately heritable, this is why selection for growth was so efficient.
Efficiency of meat production and of reproduction of broiler is enhanced by rapid juvenile growth in the broiler
but minimal body size in the parent. This required by the modification of the growth curve genetically and by
restricted feeding. Correlation of live weight with weights of carcass parts are usually high (0.9), and lower with
abdominal fat (0.2-0.5).
Fast-growth issues
Pros: is the high efficiency and yield and capacity to eat and good carcass conformation. Cons: metabolic
consequences ascites, the body grows faster than organs, mortality increasing, leg disorders occur like lameness
and tibia dyscondroplasia that arises behavioral and animal welfare issues.
Slowing down fast broilers
The methods to slow down breeder generation growth are to restrict feed, under-formulate feed, with lighting
programs, perhaps raising on pasture, or raising only females, but ultimately raising slower strains such as
roaster lines.
Feed efficiency
Selection based on improved feed efficiency is an effective procedure to get lean broiler chicken, because of
high correlation between feed efficiency and fatness. Manipulation of the partition of retained energy between
protein and fat is an efficient way of improving feed conversion rate as well as energetic efficiency. The
combined selection of growth and feed conversion rate altered the proportion of white, fast-fatiguing muscle
fibers to red, slow-fatiguing muscle fibers. This had an impact on energy metabolism post mortem and meat
quality occurring PSE and DFD meat. This also leads to an exacerbation of the disproportion between the
cardiopulmonary system and muscle mass. This caused the retardation of vital oxygen-delivering tissues.
6.1. ábra - Fig. 6.1. Flow chart of typical broiler or turkey operation
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TRAITS. PARAMETERS AND
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(Source: http://www.ces.ncsu.edu/depts/poulsci/techinfo/4Pst39.htm)
Reproduction
A strong negative correlation exists betwen body weight and reproduction. Reproductive efficiency is
characterized by several traits, such as egg production (size and number), libido, sperm and oocyte quality,
sperm storage by the hen, gamete-gamete interactions, genetic compatibility and hatchability and survival.
During selection for growth these traits have been severely reduced. Feeding is restricted and lighting
programmes are introduced in broiler breeders to maximize egg and chick production. A minimum fat level is
needed to reach sexual maturity, this is related to the selection for growth and feed conversion, that reduces
fatness doing so, deleays maturity. It is known on the other hand that fat birds’s egg has got a lower hatchability.
In summary, selection for lean growth over to a point, may lead to the deterioration of meat quality and
reproduction.
Skeletal problems
Skeletal defects is associated with rapid growth, especially in the early growth period. Selection for increases
frame size and muscle produced birds with a posture that prevented them from walking or standing for long
period. The genetic correlation between leg disorders and body weight is positive 0.25. The weight stress
frequently resulted in leg disorders. High protein diets can also contribute to skeletal problems. Improper egg
storage (long, hot or cold) can also skeletal defects.
Carcass
Rapid growth was the major factor increasing yields of dressed carcasses. Meat production can be characterized
by yield and quality. Meat yield can expressed as carcass yield (dressing percentage), yield of specific tissue
(lean, fat, bone). Meat quality can be evaluated by carcass conformation, sensory evaluation, juiciness,
tenderness and chemical composition. Abdominal fat is detrimental to carcass quality. Weight gain tends to be
negatively correlated with abdominal fat. Genetic differences exist among strains and lines for yields and
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TRAITS. PARAMETERS AND
HERITABILITY
quality. During the selection for lean growth less attention has been paid to quality. Muscle characteristics
influencing the quality of the meat are ulinked to the quantitative (total number of muscle fibres and sizes) and
qualitative characteristics of the muscle fibres. Brest muscle is the most valuable part (white meat) of the
chicken carcass and attention has been paid to increase it. (h 2 = 0.5-0.6).
Because of animal welfare issues future natural/organic broiler can perform with: an all-vegetable diet (no
animal by-products), diets that do not include synthetic amino acids, non-optimized diets, more open housing,
uncontrolled environment, no coccidiostats, slower growth, stronger immunity. Disease-resistant birds will not
need drugs or vaccines, antibiotic-free chickens, fast feathering. Good feathering provides insulation, protection
from nicks. Meat quality traits gain importance and the genetics adapted to particular regions.
In certain parts of the World consumers have strong preference for quality chickens with specific appearance
(feather color, shanks, skin, comb) and more tasty meat. Consumers are willing to pay higher price for the socalled quality chickens.
6.2. táblázat - Table 6.2. The comparison broilers and quality chicken
Broilers
Quality chicken
Fast growth rate (40d)
Developed from native chickens
Better FCR (1.6)
Specific appearance
More meat (Breast 20%)
Slow-growing (70~120d)
Soft meat
Poor FCR (2.1~3)
Less flavor
Tasty and chewy
Need good facility
Better disease resistance
Hard to manage
Easy to manage
Reasonable cost
Higher production cost
6.2. ábra - Table 6.3. Heritabilities for growth and body composition in chicken
6.3. ábra - Table 6.4. Correlation between broiler traits
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TRAITS. PARAMETERS AND
HERITABILITY
Layer’s traits
The main selection goal with laying hens is a highly efficient egg output per hen per year. Four primary trait
groups are identified in an egg-type layer breeding enterprise: 1. value of saleable baby chicks per breeder hen,
2. value of saleable market eggs per hen, 3. carcass value of a spent hen, 4. cost of feed consumed per hen.
Age at Sexual Maturity:
It is the age of the bird at which it lays the first egg. Early maturing hens lay more number of eggs, but smaller
in size compared to late maturing ones. In order to prevent this problem lighting and feeding are to prevent this
problem lighting and feeding are monitored during growing period to delay sexual maturity.
Persistency:
It is the measure of the length of laying cycle. This factor is associated with eggproduction. The laying cycle of
a hen is terminated by molting. The longer the laying cycle before the hen enters her molting period, the better
she is for eggproduction. The laying cycle should be about 300 days.
Further traits:
Product quality traits: egg deformation, shell thickness, colour, porosity and shape, albumen quality,. blood
spots, female and male fertility.
Disease affects egg production thorough mortality and morbidity. Mortality reduces the number of layers
available to lay eggs and morbidity reduces the laying ability of affected hens.
6.4. ábra - Table 6.5. Heritabilities of layer traits
6.5. ábra - Table 6.6. Correlation between layers traits
Most of economic traits of poultry are low to medium in heritability. So. improvement is achieved by pure line
selection and then crossbreeding of the inbred line. The practise is the recurrent and reciprocal recurrent
selection which will be discussed in later chapter.
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HERITABILITY
Future of the industry
1. Increased biotechnology.
2. Increased mass production- year round availability of products.
3. More contract and integrated production. Larger integrators.
4. Increased labour- saving device.
5. Sustainable agriculture.
6. Increased attention to poultry behavior and welfare.
7. Increased food safety.
8. Increased quality of products.
9. Increased consumption.
10.
In future emphasis will be given to the welfare of poultry as well as poultry product consumers.
11.
Selection criteria of the broiler in 1960: liveweight.
12.
Selection criteria now: eggs, hatchability, weight, breast meat, meat quality, immune response, growth
profile, feed conversion, heart and lung fitness, skeletal integrity.
1. Questions
1. Why poultry industry is important?
2. What are the main traits in broiler and layer traits?
3. How heritable are these traits?
4. What is the genetic correlation between these traits?
5. What is the genetic background in supporting different lines?
2. Literature cited
Dr. Michael Smith. Poultry.ppt
Crawford. R. D. (2003): Poultry breeding and genetics. Elsevier.
Muir. W. M., Aggrey. S. E. (2003): Poultry genetics. breeding and biotechnology. CABI Publishing.
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7. fejezet - 7. Inbreeding and
crossbreeding
Both the inbreeding and crossbreeding change the population mean and variance.
Inbreeding
Inbreeding is a mating of relatives. Mating of relatives frequently changes the population mean when compared
to random mating. Inbreeding decreases fitness, which is unfavourable, and decreases the mean of the traits that
related to reproduction and fitness. Apart from this, we apply inbreeding from two reasons:
• to establish homozygous lines for laboratory experiments,
• to establish inbred line as a basis of crossbreeding and hybridisation.
The inbreeding can happen by chance in:
• small population.
• during selection.
The genetic drift. loosing alleles is a special case of inbreeding. Smaller the population, larger the chance for
inbreeding, since in small population the mating of relatives is more probable. In mass selection some groups of
animals, that are related, have got higher chance for selection, because theay are more similar in phenotype or
genotype.
Inbreeding coefficient
The scale of inbreeding is expressed by inbreeding coefficient F (f) after Wright. It’s value changes between 01, or 0-100%. The F is the probability of two alleles in a loci that are identical by decent. An individual has got
an inbreeding coefficient of F, if a randomly choosen locus has got F probability of being homozygote.
Calculation of F:
Fx= Σ[(1/2)n+n’+1(1+FA)]
where:
Fx
=is the inbreeding coefficient of individual X
n and n’ = the number of generation to the common ancestor thorough the dam and sire side.
FA
= the inbreeding coefficient of any common ancestor.
7.1. táblázat - Table 7.1. Inbreeding coefficient for some typical mating
generation
selffertilisation
full-sib mating parentoffspring
mating1
parentoffspring
mating2
halfsib mating
1
0.500
0.250
0.250
0.250
0.125
2
0.750
0.375
0.375
0.375
0.219
3
0.875
0.500
0.500
0.438
0.305
4
0.938
0.594
0.594
0.469
0.381
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7. Inbreeding and crossbreeding
5
0.969
0.672
0.672
0.474
0.449
…
…
…
…
…
…
∞
1.000
1.000
1.000
0.500
1.000
1 = mating with the younger parent
2 = mating with the same parent (F=0)
Change in allele frequency after inbreeding
Judging the effect of inbreeding, we start from a randomly selected locus. Let us assume that, the frequency of
allele A1 is p, and the frequency of A2 is q. The probability of two alleles in a loci are identical by decent is F,
than the loci is homozygote A1A1, the frequency is = p, the frequency of A2A2 is = q. Then q = 1- p. If the alleles
are not identical by decent, their genetic variance can be described by Hardy-Weinberg equilibrium. During
inbreeding the expected genotype frequency is the following:
Genotype
Common alleles
Non common alleles
Frequency
A1A1
F.p
(1-F)p2
p2+ Fpq
A2A1
10
(1-F)2pq
(1 - F)2pq
A2A2
F.q
(1-F)q2
q2+ Fqq
If genotypes A1A1. A1A2. A2A2 have got a value of a, d, -a. Than the average value of traits after inbreeding are
the following:
µF = a(p2+ Fpq) + d(1-F)2pq – a(q2+ Fqq)
= a(2p -1) + 2(1-F)pqd
In random mating (F = 0). and µF = a(2p -1) + 2pqd
In inbreeding, µF = µ0.- 2Fpqd
Generally if the number of loci is k, µF = µ0 - 2F∑p1q1d1 = µ0- BF
where B = 2∑p1q1d1 p is the decrease of average at full inbreeding (F = 1).
It arises from the above that
• the population average changes only, if d≠ 0,
• if d > 0, than the inbreeding decrease the average,
• if d < 0, than the inbreeding increase the average,
• in case of several loci the decrease (inbreeding depression) depends on the dominance,
• the scale of change depends on the allele frequency. and is the largest, when p + q = 0.5.
Inbreeding depression, B
The inbreeding depression coefficient B. express the the scale of depression due to inbreeding. which derives
from:
µF = µ0.- BF
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where
µ is the population average in random mating population, µ F is the average in inbreeding,
F is the inbreeding coefficient, B is the inbreeding depression coefficient.
If no epistasis occours, the depression is non-linear, in case of epistasis the depression is linear.
Two theories exist for the explanation of depression:
• According to the superdominance (overdominance) theory heterozygotes the fitness, the prolificacy is higher
than in homozygotes. Since inbreeding decreases the frequency of heterozygotes and increases the frequency
of homozygotes the genotypes that do not express dominance. There are cases, when the fitness of inbred
lines are the same as the base population, in these cases the theory can not be justified.
• According to the theory of dominance there are lethal or sublethal alleles, which have got unfavourable
effects on reproduction. If those are in heterozygote forms their effects are not expressed, since the normal
dominant alleles supress their effect. During inbreeding more and more are expressed in homozygotes.
Effective population size, Ne
Animal breeders try to minimize the inbreeding, or its effects. In small, distinct population the drift is
unavoidable. In large population there is more chance to avoid the mating of relatives. The effective population
size (Ne) is ulinked to inbreeding. According to a definition the maximal effective size of a population is such
that all individuals have an equal chance to contribute to the next generation. According to an another definition,
the effective population size is maximum, when males and females produce the same number of progenies. The
effective population size can be viewed from a male/female ratio. The population size is effective, if one male is
mated to r females and all males have got at least one son and r number of daughters and all females have got at
least 1/r number of son.
Generally the effective population size is such large which is not at risk, sustainable, effective and
reproducable.
Ne = 4(Nm x Nf)/(Nm + Nf)
where:
Ne = effective population size
Nm = number of males (sires)
Nf = number of females (dams)
The change of variance during inbreeding
Inbreeding will change the variance within lines and between lines. We assume that the genetic variance is
additive variance.
if F=1
Variance
Generally
if F = 0
Between lines
2Fσ2A
2σ2A
0
Within lines
(1 – F)σ2A
0
σ2A
Total
(1 + F)σ2A
2σ2A
σ2A
Inbreeding increases variance between lines and decreases it within the lines. When dominance is present this
can be modified by allele frequency. If the variance changes, heritability will also change compared to random
breeding population.
h2t = (1-Ft) σ2A/(1-Ft)σ2A + σ2E) = h20 (1-Ft)/(1- h20Ft)
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where
h2t = the heritability in inbreeding population (line)
h20 = heritability in the base population
Ft = the inbreeding coefficient of the line
σ2A = additive genetic variance
σ2E = environmental variance
Hybridization and crossing
Crossing is mating animals from different breeds, or even species. The hybridisation is mating individuals from
two or more lines or populations. The hybridisation differs from crossbreeding in such that, the parental lines are
selected for combination ability to produce the best progenies utilising not only the additive effects but
dominance and epistatic effects as well.
Crossbreeding is used for two main reasons. One of the reason is to combine the advantages of the breeds. This
is not always successful, since disadvantegous of the breeds will also combine. (For example if we want to
combine the high milk yield of the Holstein with the high fat yield of the Jersey by crossing, we also get
individuals with low milk yield and low fat yield.). The second reason is to utilize the hybrid vigor or heterosis.
The heterosis is the superiority of crossbred animals compared to the average of the parents in some traits.
We can expect heterosis even mating similar lines. In this case the aim of hybridisation is not to combine
different traits, but reveal favourable alleles which either showing dominance or epistatic effects. On the other
hand larger the distance between lines or breeds, the larger the number of loci in which different alleles are
present and by crossing, heterozigosity can be observed in many loci. In the F 1 generation we can observ larger
heterosis than in F2. since according to the Mendelian low segregation happens in the second generation, the
proportion of heterozyoges will be halfed. The heterosis is the mirror of the inbreeding depression, recovering
from inbreeding. The average of the inbred lines µF = µ0 - BF. If all inbred lines are mated randomly to get F=0,
the average of crossbred will be again the same as was in the base population (µ0).
Heterosis happens not only by crossing of inbred lines, but by crossing unrelated population, but the magnitude
will usually be smaller.
Types of crossings
We can classify the crossings from several aspects. In this part we classify from heterozigosity of the endproduct.
Single cross (SC) in which the F1 is produced from two lines (breeds). The genetic proportion of the two lines
are 50-50%.
If there are several lines, how we choose the best combination? One possibility is a diallel mating, or diallelic
design, when each lines are mated to each. If n lines are mated the number of mating is n(n-1)/2. If we have 20
lines we need to have 190 crossing. This can be simplified by determining the general combining ability (GCA)
of each line then the specific combing ability (SCA) in each crossings. But how can we predict GCA, without
carrying out all mating? One possibility is topcross design (mating), when we select a test sire (common sire)
from a given line then we use that sire for mating in every lines. The other possibility is the polycross design
(mating) when we let females randomly mate from any sire of any lines. In all cases we evaluate the
performance of the F1 generation and we choose elit lines which produced the best progeny performance.
Animal breeders frequently produce more complex hybrids then F1-s. In triple or tree-way cross (3W) we
cross the F1 with a further breed or line A x (B x C). In the terminal product 50% of the genes originate from
breed A, 25% from breed B, and 25% from breed C. In a four-way cross (4W) or double cross (DC) two F1 are
crossed (AB x CD = (A x B) x (C x D). The proportion of genes are 25-25% of each lines.
Brown egg layer crosses are for example: New Hampshire x Barred Rock, Columbian Rock x Red, R.I. Red x
Columbian Rock. Turkey hybrids are for example: Hybrid Converter, Hybrid Diamond White Medium, Hybrid
Grade Maker, Hybrid XL. A duck hybrid for example is a White Pekin.
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7. Inbreeding and crossbreeding
The size of heterosis, its change during crossing
Let us assume a mating of parents (P1 és P2) from two different breeds or lines. The heterosis experienced in the
crossbred progenies depends on the difference of gene frequency of the parents. The heterosis in F 1:
HF1 = µF1 - (µP1 + µP2)/2
where
HF1 = heterosis in F1
µF1 = the average performance of F1
µP1 and µ P2 = the average performance of the parents.
Heterosis of the F2:
HF2 = µF2 - (µP1 + µP2)/2 = HF1/2.
so in F2 the heterosis is half of the one that observed in F2.
We can differentiate between individual and maternal heterosis. The individual heterosis is the superiority of a
crossbred individual compared to the average of the parents. the maternal heterosis is the superiority of a
crossbred dam in maternal performance (prolificacy, upraising ability). In traits with lower heritability, such as
maternal performance, we observe higher heterosis, than in individual traits. This could be the result of the
higher incidence of dominance in low heritable traits. In table 7.2. the effect of heterosis is shown.
7.2. táblázat - Table 7.2 The effect of heterosis in some sheep traits
Trait
individual heterosis
maternal heterosis
Birth weight
3.2
5.1
Weaning weight
5.0
6.3
Body gain before weaning
5.3
Body gain after weaning
6.6
Yearling weight
5.2
Ovulation rate
2.0
Fertility
2.6
8.7
Weaning rate
9.8
2.7
Number of lambs born
5.3
11.5
Number of lambs weaned
15.2
14.7
Total weight of lambs weaned
17.8
18.0
Maternal heterosis can be combined in 3-way or 4-way crosses. In these crosses we utilize both the maternal
heterosi of F1 dams and the individual heterosis of the terminal products.
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7. Inbreeding and crossbreeding
If the sire is crossed. paternal heterosis in semen fertility can be observed.
1. Questions
1. How the effective population size and inbreeding connected?
2. Is there a relationship between inbreeding depression and heterosis?
3. What type of crossings do you know?
4. How does the variance change during inbreeding?
5. Is there a relationship between inbreeding depression and dominance?
2. Literature
Bourdon M. R. (1997): Understanding animal breeding. Prentice Hall. Inc
Bruce W (2006): Notes for a short course taught June 2006 at University of Aarhus
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8. fejezet - 8. GENOTYPE-GENOTYPE
INTERACTION
In the past, the selection was aimed at to improve mainly production traits, without considering welfare traits.
The consequences of neglecting the welfare traits can be summarised in three points: 1. the larger animals are
more competitive, so selection indirectly increased competitiveness, which indirectly decrease animal welfare,
2. larger competition decrease the performance of less competitive animals, doing so, decrease the group
performance, 3. the genotype-genotype intercation, competition, influence the effectiveness of BLUP-based
selection. This chapter outlines the selection of individual performance and group performance.
The welfare traits were not important for breeders, since inclusion of a new trait in the selection goal, would
have decreased the response in performance traits. The selection traits need to have economic value, so breeders
need to be convinced about the economic value of welfare traits. The last 20 years proved that it is possible to
select for welfare traits and performance traits without measuring a new trait. Application of the method, is a byproduct of the welfare, so indirect selection can be practised.
Group selection
The group selection is an indirect selection method which is advantegous for the group. The group selection
improves the viability of the group members. During group selection we choose animals which are favourable
for the group. Griffing (1967) draw attention for the relationship between the individual and group performance
using the competitive elements in his model. Competition exists in a group if feeding, space, water, rank, or any
resource is limited. According to Griffing (1967) in case of interrelated animals the change of population mean
(Δμ) at selection intensity of i, and phenotypic standard error σ:
where
is the additive variance of direct effects,
is the covariance of direct and indirect effects. If the covariance is negative, when the resources are limited, the
selection for high individual performance decrease the group performace. There are genes which are favourable
for the individual, but unfavourable for their group behaviour. This can be eliminated if we consider the group
as a selection unit.
where
is the additive variance of the behaviour within the group. In this case, since all the elements of the model is
positive, Δμ is always positive. So instead of selecting for individual performance, selection for group
performance it will increase the population mean. Griffing (1967) also proved that, by group selection, selection
for traits which are negatively correlated, but have got a positive group effect, is possible, these are shown in
altruistic, self sacrifying traits. Increasing the size of a group, these „group genes” have got an increasing role.
In management systems, where the group size is large, larger selection response can be achieved by decreasing
the frequency of competitive genes, than increasing the frequency of individual performance genes. If the group
members are relatives, their agressivity is smaller, collaborative willingness is higher, especially in large groups.
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INTERACTION
Group selection in poultry breeding
In a layer-breeding experiment, selection for group group performance, the loss till 72 weeks of 68%, decreased
to 8.8% by the 6th generation. Beak treatment was not practised in the selection group, control was placed in
individual cages, where loss was 9.1%. It was proved, than, group selection makes the beak treatment
unnecessary.
Group selection has got indirect physiological and behavioural effects. The group selected birds have got
healthier feather, and showed less agressive behaviour. Antisocial behaviour can be pushed into background. To
show the effectiveness of a selection, we often parctice divergent selection and after some generation of
selection we compare them. Cheng et al (2001) compared high and low group selected lines, their results are
shown in table 8.1.
8.1. táblázat - Table 8.1. Layers selected for high and low group performance
Trait
Lines selected for high group Lines selected for low group
performance
performance
Loss (%)
1.3 ± 0.1
8.6 ± 0.5
Length of life (days)
363 ± 0.4
193 ± 21
Number of eggs/hen
295 ± 11
108 ± 12
Egg weight/hen (g/day)
48 ± 2
17 ± 1.8
Egg weight (g)
59.4 ± 0.6
58.9 ± 0.8
Birds selected for high group performance showed higher performance, better viability than birds selected to
low group performance. The effect of selection on the immunological parameters is shown in table 8.2.
8.2. táblázat - Table 8.2. The effect of group selection on immunological parameters
Lines
Heterofil(H) Limfocita(L H:L (x100)
)
Monocita
Eosinofil
Basofil
High group 10.7 ± 1.13
performanc
e (H)
83.4 ± 1.3
13.0
2.6 ± 0.4
1.7 ± 0.2
1.6 ± 1.1
Low group 20.4 ± 1.8
performanc
e (A)
72.3 ± 1.8
29.4
2.1 ± 0.4
3.8 ± 0.4
1.4 ± 0.2
M:A
115 %
44 %
124 %
45%
114 %
53 %
Birds selected for higher group performance showed lower heterofil:limfocita ratio during transport, treatments,
which shows lower stress. The monocytes were also in larger proportion, the plasma immunglobulin
concentration was also higher. This proves that, group selection improves immunological background as well.
The individuals selected for high group performance, are quite, shows passive behaviour, easily adapted to
changing environment and to stress.
1. Questions
1. In what circumstances is necessary the research in genotype-genotype interaction?
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INTERACTION
2. What is the advantage of group selection?
3. How individual and group selection can be contrasted? Is there any relevance to a human society?
2. Literature
Cheng, H.W., Eicher, S.D., Chen, Y., Singleton, P., Muir, W.M. (2001): Effect of genetic selection for group
productivity and longevity on immunological and hematological parameters of chickens. Poultry Science. 80,
1079-1086.
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9. fejezet - 9. Marker assisted
selection in poultry breeding
Questions
• What is the difference between MAS and GAS?
• How can we apply molecular markers in breeding programs?
• Can markers be used for monitoring the success of crossing?
• How does MAS effect genetic variability?
Most traits of economic importance are quantitative traits that most likely are controlled by a large number of
genes. For a long time we assumed that traits are controlled by an infinite number of genes, that have minor and
equal effects. New research indicates that, however, a finite number of genes and their interactions control the
trait. Some of these genes might have a larger effect. Such genes can be called major genes located at
Quantitative Trait Loci (QTL). Knowledge of the close regions to the QTL can increase the accuracy of the
breeding value. Genetic markers are marking poles near to the QTL in the genome. Most QTL known today can
only be targeted by genetic markers. We cannot actually observe inheritance at the QTL itself, but we can
observe inheritance at the marker, which is close to the QTL. When making selection decisions based on marker
genotypes, it is important to know what information can be deducted from the marker genotypes.
Efficient breeding programs are characterised by selecting animals at a young age, which leads to a short
generation intervals and faster genetic progress per year. For selecting at younger ages knowledge about the
existence of potentially coding genes could be very beneficial. In practice we rarely know the genotype at actual
QTL.
Definition of markers. Markers are nucleotid variates. it’s location is identified on the chromosome. and
follows Mendelian inheritance. Markers are neutral alleles without contribution to the formation of phenotype.
Ideal markers have large DNA polimorphism, codominant inheritance, easy detectability and reproducibility.
There are chromosome segments, where DNA sequences differences between individuals within breed can be
detected. Markers are in coding and non-coding regions.
The main types of molecular markers are VNTRs. RFLPs and RAPDs. AFLPs and SNPs.
VNTR’s
DNA sequence called Variable Number Tandem Repeat, scattered at various locations in the genome are
regions that are highly variable. Tandem repeats are multiple copies of a sequence of base pairs. A frequently
found tandem repeat is CA, and one strand containing this type of repeat reads CACACA….. . notated as (CA)n.
The other strand would read GTGTGT… In this example, the number of repeating basepairs is two but it can be
more. When the repeating unit is less than four, the VNTR is called a microsatellite and when the repeating unit
is longer it is a minisatellite.
Microsatellites
Microsatellites are DNA regions with variable numbers of short tandem repeats flanked by a unique sequence.
Microsatellites are good genetic markers because they each have many different 'alleles' - ie. there can be many
different lengths of the repeat region. An allele is defined by the number of repeats there are at the same
location. With many alleles, there is larger chance for individuals to be heterozygous and there is larger chance
for finding different genotypes. Microsatellites are used for parentage testing in so called parentage kits. Usually
9-11 microsatellites loci are suitable for parentage exclusion. Microsatellite markers can favourable be ulinked
to QTL allele.
Restriction Fragment Length Polymorhisms (RFLP's).
Restriction enzymes enzymes cut DNA wherever they find the appropriate nucleotide sequence. If there is a
mutation at this sequence, no cut is made and the resulting DNA fragment is longer. Also mutation to give a
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new recognition sequence gives a pair of shorter fragments. Genetic differences (polymorphisms) of this type
are known as Restriction Fragment Length Polymorphisms.
RAPD’s
Random Amplified Polymorphic DNA (RAPD) markers are DNA fragments generated in PCR (Polymerase
Chain Reaction) reactions that use a single short primer (in normal PCR a primer-pair is used). The primer must
be complementary to sequences that are on opposite strands within a small number of base pairs (e.g. 2500). The
DNA strand between these two sites is amplified in a PCR. Polymorphism is determined by individuals who
have mutations at those sites. and therefore will not show a product on the gel. The advantage of RAPD’s is that
we do not need to know the DNA sequence of the species studied. The disadvantage is that RAPDs either give
or do not give a product and therefore we can not distinguish between homo- and heterozygotes.
AFLPs
Amplified Fragment Length Polymorphism (AFLP) is based on PCR amplification of selected restriction
fragments. Like RAPDs, AFLPs require no prior knowledge of DNA sequences (unlike microsatellites). The
advantage of AFLPs over RAPDs is that they are more reliable and reproducable. Also, the number of
polymorhpic loci (molucular markers) that can be detected is 10-100 times greater with AFLPs than with
microsatellites or RAPDs.
SNPs
Single Nucleotide Polymorphisms are based on single base pair polymorphisms. A SNP is a position at which
two alternate bases occur at appreciable frequency. In animals they may number greater than one in a thousand
base pairs. SNPs can be detected by a number of methods, however a relatively new technology, using DNA
chips, can be used for large scale screening of numerous samples in a minimal amount of time.
All molecular markers need to be mapped based on ulinkage analysis. Their position on the genetic map needs
to be determined. Two genes are assumed to be ulinked if they are located on the same chromosome. We
assume that different chromosomes segregate independently during meiosis. Therefore, for two genes located at
different chromosomes, we may say that their alleles also segregate independently. The chance that an allele at
one locus co-inherits with an allele at another locus of the same parental origin is then 0.5 and such genes are
unulinked. ulinkage equilibrium and its opposite: ulinkage disequilibrium, are terms used for the chance of coinheritance of alleles at different loci. Alleles that are in random association are said to be in ulinkage
equilibrium. The chance of finding one allele at one locus is independent of finding another allele at another
locus. We may expect full disequilibrium between ulinked genes within a family, as the number of recombinants
is the result of one meiosis event. Similarly, the same disequilibrium exists between a cross of inbred lines.
Population-wide ulinkage disequilibrium exist in the case of selection. or with ulinked loci short after crossing
or migration, or when two genes are so close that hardly any recombinations occur. Among agriculturaly
important animals, chickens provide opportunities to generate excellent families for genetic experimentation. A
variety of inbred (homozygous or nearly so) lines are now available, and large families can be generated and
tested efficiently. ulinkage diequlibrium is expressed by
D = ru – st.
where r and s, are the frequencies of A1 and A2 gametes, t and u, are the frequencies of B 1 and B2 gametes. D
expresses the difference from the equilibrium, ru is the frequency of cis, st is the frequency of trans
heterozygotes. In genetic equlibrium the frequency of the two heterozygotes are equal.
The recombination can cause a problem. Because of recombination we cannot be sure which marker variant is
associated with each gene variant in an animal. Lower the recombination rate is said to have a close ulink
between the marker and the QTL. This is the case for indirect markers. If a marker is located within a major
gene, then recombination is no longer the problem. In this case the marker is the QTL. We only need to measure
the trait involved in selection. This is called direct marker, no recombination occurs. However. there are
currently only a few direct genetic markers for economically important traits. Examples are: the Halothane gene
double muscling gene in cattle (increased muscle mass). This gene is the myostatin gene. The BLAD (Bovine
Leukocite Adhesion Deficiency) is a recessive mutant gene of the CD18 gene causing immune supression in
calf. The leptin (obesity) gene occurs in mammals, causing obesity and sterility. The B variant of the oestrogene
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receptor gene (ER) increases prolificacy in pigs. Using direct markers for selection is called Gene Assisted
Selection (GAS).
Possible risks with using direct markers are: there can be more than one mutation causing the desired genetic
effect. An example of this case was the myostatin gene for double muscling, where several mutations within the
gene caused the same desired effect. If only some of the single direct markers had been adopted, there could
have been false negatives in diagnostic tests. There is also some potential to incorrectly identify a candidate
gene as a major gene directly affecting the trait of interest, because it is only near the true causative gene. In that
case there is a risk of false positives: we pick the ‘positive gene’ but it turns out to be an indirect marker and
recombination might have made it ulinked to the ‘negative allele’.
ulinked markers are only near QTL on the genome and not the causitive mutation in the gene concerned. For a
randomly chosen animal in the population, we have no clue whether one or another maker allele is associated
with a preferable QTL allele. If we observe within the progeny of one sire a difference in performance between
different marker alleles we can determine which of the marker alleles is associated with the preferred QTLallele. But this information is only useful for this particular sire and its family. Known. so called indirect. or type
II. markers available for the FecB gene (Booroola sheep). callipyge gene (in sheep). weaver disease (in cattle).
polledness (in cattle and in sheep). Several designs are used to test associations between marker and the QTL.
These are the daughter design, grand-daughter design, generating full-sib and half-sib families, backcrossing,
generating F2 generation.
Marker assisted selection (MAS)
Several scientists proved the advantage of MAS in short term in poligenic traits. The advantage in the long term
is diminishing. In the first generations the QTL allele frequency increasing. reaching 0.5 frequency. The
increament of frequency decreases the proportion of variance responsible for the QTL effect, so the efficiency of
MAS is decreasing. The advantage very much depends on the genetic model used for the evaluation. Larger the
QTL effect, larger the number of QTL alleles, larger the number of known generations of QTL genotype, higher
of the intensity of selection. larger is the efficiency of MAS selection. Genes with large effect became fixed
shorthly. The proportion of within family variance due to the QTL is responsible for the efficiency. Only 10%
QTL variance increase the response by 20% compared to traditional selection. But identifying the 10%
proportion we need around 500 grand-daughters per grand-sires. In the first generations the selection is intensive
for the QTL-trait and the selection for poligenic genes is less intensive, favourable epistatic effects might
breake. The QTL effect needs to be recalculated after each generations. A possible use of QTL information is to
select amongst young fullsib bulls with the same pedigree index.
Marker assisted selection is advantegous in the following cases:
a. Where heritability is low, the value of information on individual QTL tends to be higher because accuracy of
breeding values is increased by a relatively larger amount.
b. Where the trait(s) of interest cannot be measured on one sex, marker information gives a basis to rank
animals of that sex (e.g. egg laying. prolificacy. milk production). This is particularly useful when to
determine which males should be progeny tested.
c. If the trait is not measurable before sexual maturity marker information can be used to select at a juvenile
stage. Molecular markers can be detected even in embryo.
d. If a trait is difficult to measure or costly or difficult (e.g. resistance) or requires sacrifice (as with many
carcass traits: meat pH, softness, colour) marker information can be used instead. All the facts above
increases accuracy of breeding value and shorthens generation interval.
MAS/GAS is more advantegous to traditional selection. if:
• The trait has a low heritability (fitness trait),
• The QTL has got a large effect,
• The desirable allel is in low frequency,
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• The marker-QTL association is strong,
• The gene effect is non-additive.
Markers can be included in breeding program markers are considered as knew selection criterias. According to
the selection index theory the phenotypic and genetic relationship between markers and others selection criterias
should be known. The allel frequency changes during selection that requires recalculation of its effect.
Lei et al (2007) reviewed and demonstrates that chicken QTL studies have been successful in identifying QTL
underlying variation in economically important traits. In combination. the results of the primary QTL studies
enabled identification of basic information on the genetic architecture underling complex traits in the chicken.
http://www.animalgenome.org/QTLdb/chicken.html)
9.1. ábra - Table 9.1. Gene effects on chicken fatness and mucle fiber traits (Lei et
al..2007)
MAS can be used in introgression strategies to select both for the trait to be introgressed and against undesirable
background traits. Continuous backcrossing and monitoring the desired QTL hepls to achieve faster result. the
local breed with the favourable gene (M) present (Fig. 9.1.)
9.2. ábra - Fig. 9.1. Marker assisted introgression
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Genomic selection (GS)
Genomic selection is a form of marker-assisted selection in which genetic markers covering the whole genome
are used so that all quantitative trait loci (QTL) are in ulinkage disequilibrium with at least one marker. This
approach has become available due to the large number of single nucleotide polymorphisms (SNP) discovered.
The Beijing Genome Institute identified and released 2.8 million SNP to the public domain. Recently a large
resequencing project was funded by the government of the United Kingdom (Biotechnology and Biological
Sciences Research Council. Swindon. UK;
http://www.foodsecurity.ac.uk/research/current/gains-in-grains.html). Limited experimental results suggest that
breeding values can be predicted with high accuracy using genetic markers alone but more validation is required
especially in samples of the population (so called reference population) different from that in which the effect of
the markers was estimated. Implementation of genomic selection is likely to have major implications for genetic
evaluation systems and for genetic improvement programmes generally and these are discussed. Genomic
prediction combines marker data with phenotypic and pedigree data (when available) in an attempt to increase
the accuracy of the prediction of breeding and genotypic values. What has been hold for MAS is also applicable
for GS. Namely larger the reference population and the genetic similarity and environment with the population
where prediction takes place, larger the precision, SNP effects needs to be recalculated in every at least 5th
years of selection. Lower the recombination rate between the nucleotide and the gene, the selection is more
effective.
1. Questions
1. Please choose a breed from any species and define the breeding objective!
2. Classify the breeding objectives according to the gain in efficiency of MAS to traditional selection!
3. Please mention some DNA markers.
4. What is the difference between MAS and GAS?
5. What is the genomic challange?
2. Literature cited
Abasht. B.. Dekkers. J. C. M.. Lamont. S. J. (2006): Review of Quantitative Trait Loci Identified in the Chicken.
Poultry Science. 85:2079–2096.
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Lei. M. Luo. C.. Peng. X.. Fang. M.. Nie. Q.. Zhang. D.. Yang. G.. Zhang. X. (2007): Polymorphism of GrowthCorrelated Genes Associated with Fatness and Muscle Fiber Traits in Chickens. Poultry Science. 86:835–842.
Kinghorn. B.. Werf. J.van der (2000): Identifying and incorporating genetic markers and major genes in animal
breeding programs. QTL course: June 2000. Belo Horizonte. Brasil.
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10. fejezet - 10. BREEDING FOR
RESISTANCE
Questions:
• What is the difference between disease resistance and tolerance?
• What models exists for resistance?
• How the immune system can be altered?
• How to breed for resistance?
Disease controls include the barriers of biosecurity, vaccination, the use of antibiotics and other pharmaceuticals
and genetic selection.
Animal diseases hinders animal production and increase cost of production. Diseases require physical and
chemical intervention. Physical intervention causes stress for the animals. Chemical treatments might have
residues in animal product which relates to food safety, external treatments might have environmental impact.
These have implications to human health. Consumer preferenced increased for residue-free animal products.
Ethical concerns exist about continuing to treat animals with drugs and to minimize the suffering experienced by
diseased animals. The maintanence of disease monitoring system also costs money. Cost of production diseases
estimated between 10% and 20%. The evolution of parasite resistance to the treatments applied is a real
problem. For example the resistance of nematode parasites to anthelmintic drugs, bacterial resistance to
antibiotics, the evolution of virus resistance to vaccines for diseases such as Marek’s disease. For many
livestock diseases, evidence has been found for genetic variation in the extent to which host animals are
susceptible.
Disease resistance refers to the ability of the host to resist infection. Disease resistance is a genetically
controlled, physiological response of a host animal to a pathogen that limits disease severity or incidence.
Resistance may be divided into resistance to infections and resistance to disease development. Resistance to
infections reduces or prevents infections and usually specific to an individual pathogenes and to single gene.
Disease tolerance (resistance to disease development) refers to a situation where the host is infected by the
pathogen, but suffers little adverse effect.
There two views regarding resistance and tolerance. The first is the best producing animals are the most healthy
anyway and no need to consider in the breeding objectives, hoping that the healthy animals will be amongs
those selected. Some forms of avian leucosis virus infection in egg layers will result in mortality during lay.
There is also a negative correlation between egg weight and mortality. Egg production per hen housed can be
considered as the ultimate fitness trait in laying hens. The second, health traits should be included in the
breeding objective. Breeding objectives are incomplete without disease traits. In dairy cattle clinical mastitis
incidence somatic cell count are direct indicators of health, while other fitness traits, such as longevity, fertility
can be considered as indirect indicators.
Strategies may include choosing the appropriate breed for the production environment. The selection for
breeding purposes of individuals that have high levels of disease resistance or tolerance (either by conventional
breeding using phenotypic traits or by marker sor genes), cross-breeding to introduce genes into breeds that are
otherwise well adapted to the environment.
Some local breeds are characterised by resistant to different diseases. The most trypanotolerant breeds include
N’Dama and West African Shorthorn cattle. as well as Djallonke sheep and goats. N’Dama cattle show a higher
resistance than Zebu animals to ticks. The Red Maasai sheep breed is noted for its resistance to gastrointestinal
worms.
There is evidence that some breeds are more resistant to foot rot than others. The British breeds Romney Marsh.
Dorset Horn and Border Leicester showed less susceptibility to foot rot than did Peppin and Saxon Merinos
which were bred for a long time in Australia. Outbreaks of Newcastle disease and gumboro frequently destroy
chicken flocks. Outbreaks of Newcastle disease have been reported for at least a century. Gumboro was first
described in 1962 and epidemic outbreaks have been reported since the seventies. The Egyptian Mandarah
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chickens showed less susceptibility than the other breeds to both diseases. There is evidence for genetic
resistance to Marek’s disease. White Leghorn chickens showed great resistance to the development of tumours.
Selection can be assisted by molecular genetic markers ulinked to the desired traits. Selection for resistance
based on specific B alleles within the major histocompatability complex (MHC) has been used to assist in the
management of the Marek’s disease. In dairy, markers for somatic cell count, candidate gene for bloat
susceptibility. In sheep marker for susceptibility to copper deficiency has been identified. Opportinities for
marker-assisted-selection depend on how the particular trait is affected by the disease in that particular
population.
Selective breeding to take advantage of withinbreed variation in disease resistance is an important strategy in
the control of a number of diseases. For endemic diseases, which are a continuously present in the relevant
production systems selection based on phenotypic response to disease challenge is possible. Many dairy cattle
breeding programmes therefore. include increasing resistance to mastitis as an objective. Selective breeding of
sheep on the basis of FEC (faeces egg count) has been shown to be an effective means of reducing the need for
treatment with anthelmintics and of reducing the contamination of pastures with the eggs of nematode parasites.
Selecting for resistance can be assisted by natural and artificial challange. Many single-trait selection studies
have been conducted in New-Zealand and Australia. The mean heritability estimates of susceptibility was 0.28,
the range was between 0.13 and 0.45 in experimental studies. Overall fitness is a composite (multiplicative)
trait. Selection for maximal fitness leads to an optimum levels of each component traits, which leads to negative
genetic correlation among these when environmental resources become limiting. In this situation direct selection
for a single trait will lead to a negative correlated response in another component trait. In egg production for
example: percentage survival x number of eggs per hen x average egg weight. In environmental limiting
situation there is a competition for resources among production and fitness traits. In natural environment
natural selection is for fitness, in artificial environment is for production traits mainly. This is why fitness trait
deteriorated especially from the 1950’s when intensive selection started.
Genetic diversity is a key issue in breeding for health. If genetic resources are eroded, potentially important
means of combating disease may be lost. Simulation results show that populations that are diverse in terms of
the number of distinct genotypes conferring disease resistance are less susceptible to disease epidemics.
The Immune System
The immune system is the key for adaptation in the physiological and evolutionary sence. Maladaptation is the
expression of overactivity that can lead to pathological inflammation or autoimmunity. The immune system is
functioning at three interactive levels, and we differentiate general and specific disease resiatance. The three
levels are: non-specific phagocytic activity with no-memory ability, and cell-mediated immunity with memory
and antibody production with memory. The innate immune system known as non-specific immune system
include barriers to penetration, the first line of defence, that defend the host from infection. The cells of the
innate system recognize and respond to pahogens in a generic way, it doest not protect immunity to the host.
Anatomical barriers are the skin, gastrointestinal tract, respiratory airways and lungs, nasopharynx and eyes.
Inflammation is one of the first response of the immune system to infection, that is simulated by chemical
factors released by the injured cells. White blood cells (leukocytes) include natural killer cells.,must cells,
eosinophils, basophils and phagocytic cells. These are responsible for identifying and eliminating pathogens.
Natural Killer Cell (NK) is regarded as an intermediary between the innate and adaptive immunity. NK cells are
lymphoid cells that can kill a variety of virus-infected and tumour cells in vitro without the cell previously
having been infected by the virus or tumour antigenes. The adaptive immune system known as the acquired
immune system or specific immune system. The function of adaptive imune system includes the recognition of
specific antigens in the presence of self. The generation of responses which is the elimination of specific
pathogenes and the development of immunological memory. Parts of the system are the lymphocytes, 4 T
lymphocytes, 5 B lymphocytes. The Multi Histocompatibility Complex (MHC) molecules are invcolved in
antigen recognition. High rate of polymorphism of MHC molecules provide protection against pahtogens in
terms of resisting or reducing the severity of infection.
There is a great similarity among the MHC genes of many species. The MHC of the pig is called the swine
leucocyte antigen (SLA) complex, mapped to chromosome 7. Different SLA genotype pigs (aa. cc vs. dd. gg)
responded differently to pathogen challenge and the complex is also associated with pig production traits. The
Bovine Lymphocyte Antigen (BoLA) complex is located in chromosome 23 in two clusters. Diseases associated
with the bovine MHC, like posterior spinal paresis, haemochromatosis. Genetic resistance to persistent
lymphocytosis is inherited as a dominant trait associated with the BoLa A14 haplotype. On the other hand this
haplotype is accociated with increased milk production. Different BoLA haplotypes also known to be ulinked
with susceptibility of clinical mastitis, viral and bacterial infections. bovine leucosis.
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The chicken MHC containes ample classes of highly polymorphic genes found in microchromosomes 16. The
chicken MHC is the most studied complex, which shows association to different disease resistance like
neoplastic diseases (Marek’s disease neoplasia. and transient paralysis), parasitic diseases (Eimeria tenella.
Eimeria acervulina) and bacterial diseases (Staphylococcus aereus. Pasteurella multocida. Salmonella
enteridis). The chicken MHC is relatively small and compact compared to mammals.
10.1. ábra - Fig. 10.1. Chromosomal map location of the MHC
Epidemiological Models
These models are computer simulation models. Deterministic (where after a series of equations the results is
always the same, the elements of the equations can be tested for a variety of circumstances) and stochastic
models (where some of the elements of the equations are random – either normal or any type of distributions can
be used – and the results will vary, so several runs are required to get a confidence interval with a mean).
Models in cattle include tick-borne diseases, host-parasite interactions, transmittable diseases. In pigs the
Aujeszky’s virus models are the most commonly studied. Epidemiological models incorporate host and parasite
genetics.
Rodent models
Many parasitic infections can be modelled in laboratory using rodent hosts. Useful rodent models are mouse and
rat for studying Protozoa, Platyhelmintes, Nematoda.
1. Questions
1. What is the role of the MHC?
2. What disease control models are exist?
3. Please mention some main chicken diseases.
4. Please mention some main cattle diseases.
5. What models exist?
2. Literature cited
Axford. R.F.E.. Bishop. S.C.. Nicholas. F.W.. Owen. J.B. (2000): Breeding for Disease Resistance in Farm
Animals. 2nd edition. CABI International.
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11. fejezet - 11. Animal behaviour,
animal welfare
Behaviour is the response to different environment stimuli that may be from other birds, their environment,
people or any other thing or occurrence. Maximisation of production efficiency require knowledge on stock
behaviour, and the application of this knowledge. Studying poultry behaviour is important to ensure the welfare
of the birds and production efficiency. Recently, as commercial poultry production systems are intensified
animal liberation groups pay increased attention to the management of the domestic fowls.
Factors affecting the choice of technology
Production Policy (i.e. harmonization between species/hybrid, technology and feeding) in animal husbandry is
the key to profitability. In order to meet the needs of controlled production, and to ensure the continuous and
high quality poultry producers need to intensify. This require improvement and harmonization of the breed, feed
and feeding / keeping technology. With this in mind the optimum combination of elements will satisfy the
animals requirements and ensure profitable production.
Taking into consideration the animal needs is to harmonise ethology and the available technology, which
sometimes require changes in both sides. Moreover, certain limitations exist is this field due to the prevailing
animal protection legislation and welfare issues.
There are a wide range of environmental requirements in production can influence the effectiveness and welfare
issues. Naturally, intensification can lead to more and more controlled environment, while extensive production
is done in semi-natural keeping technology, often with pastures and feed lot (mass feeding) involved. This can
be considered to have effect on product quality. For sustainable production one need to change the technological
components within the biological and legal boundaries to meet the environmental regulations.
Behaviour responses are influenced by a number of factors:
• Genetic- the bird’s genetics has an important influence on its reaction to any stimuli. Some strains are more
sensitive than others. In a similar way, the fowl responds to selection for a number of behavioural
characteristics.
• Experience- chickens know how to eat, but usually the hen teaches them what to eat and where to find it.
• Age- certain behaviour is not expressed until the chickens reach appropriate ages (e.g. development of the
peck order, reproduction behaviour).
• Environment- high light intensity increases activity, which is encouraging to seek food and water, but, in
case older birds it can increase cannibalism.
Role of ethology in choosing the keeping technology
Poultry have inherited, typical behaviour types, that have specialities by species and breeds. These differences in
the life process are utilised by human intervention to improve profitability. It is important that the technological
tolerance of the breeds is to be utilised, as it regards adaptation, experience, learning. The optimisation has to be
made from two directions – animal and technology side – so the expectations of the animal and the farmer
towards technology has to meet somewhere in between. These regard animal, personnel/human and architectural
and engineering requirements with the view on authority regulations and epidemic and safety requirements. It is
important to compromise all of them and yet to be successful.
11.1. ábra - Fig. 11.1. White Hungarian Chicken, female and male
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(Hungarian Poultry Gene Bank, ÁTK, Gödöllő) Photo: Brém Zsolt
Main individual behavioural features:
Food Intake: social factors influencing feeding, even in cages. Hens tend to feed as a group, probably because
the sight or sound of one bird feeding triggers feeding in others. It is important to provide space for all birds to
feed at the same time, because at certain times of day a combination of diurnal rhythms and social effects is
likely to influence that.
Drinking Behaviour: Poultry access water though drinkers. Because drinking from these apparatus is not a
natural behaviour, birds develop strategies for obtaining water.
Comfort Behaviours: preening wing flapping, feather ruffling and stretching, are important for keeping the
plumage well groomed in both natural and artificial conditions.
Dust Bathing and Water Bathing: helps birds to maintain their plumage condition in either water or dust.
These behaviours require either loose material or water.
Rest and Sleep: poultry are generally inactive at night, diurnal rhythm is strengthened in enclosed houses. The
pattern of rest and sleep is set by the light, so it is an important factor in production.
Social Recognition and Communication: communication (signals) in poultry is provided by postures, displays
and vocalizations, because then have good colour vision and acute hearing
Social behaviour - flocking
Maintenance behaviours are those behaviours through which animals sustain their physiological equilibrium.
They include feeding, drinking, resting, comfort behaviours, such as those involved with care of the plumage,
and the patterns of activity associated with these behaviours. Poultry form flocks which size can vary from 5 to
30. Chicken flocks have strict social order, the oldest and largest birds with the largest comb dominate. Young
chicks find their place in the pecking order in 1-2 weeks. Chickens can recognize up to 80 other members of the
flock. When the flock size is larger the pecking order is not stable.
11.2. ábra - Fig. 11.2. Bronze and Copper Turkey flock
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Behavioural problems in the production environment
Chickens in production plants live in cages or in flocks of several thousand birds. Social and self-sustaining
behaviour is not possible due to lack of space so it might have a negative effect on their production features.
This disruptive behaviour can often lead to pecking one another, feathers tearing and causing wounds. Eggs are
collected daily in laying henhouses, so they continue to lay eggs permanently. When chickens are kept on
bedding they have opportunity to exercise, bath and search food. In this case flock sizes can be too large thus
fight, cannibalism, feather pecking and injuries can occur more often. This can also increase the risk of sickness.
Methods to reduce negative behaviour:
• Red light prevents the chickens from seeing blood, so decrease to peck an already injured bird.
• Less visibility (dim light) can calm the flock
• Removal of those who peck others
• Promote ‘normal’ behaviour: make is possible to access to roosts, bathing material and to search for food.
Harmony between the technology and the animal has to be ensured for economically sustainable production.
First the biological needs of the target breed/hybrid must be surveyed. After this, the technological
compartments can be tested and the effect on the life process can be monitored, taking into consideration of the
life patterns. The design of production process is to be adapted for this. In some cases the variety of the
optimized environment is to be based on genotype-environment interaction, relying also on the definition of
adaptability of the target species. There are possibilities to choose from several keeping technologies after
comparing them to find the best. Ethology is also used to monitor behavioural characteristics and is defined for
disease detection.
Ethological methods of technology control include:
• Observation - description of the full life process, which last long and can be labour intensive
• Recording physiological parameters
• Hormonal analysis of blood plasma for detection of stress (e.g.: adrenalin but with stress-free blood
sampling)
• Examination of genetic background for selection against bad habits
The importance of well-being, the possibility of its measurement
Welfare and well-being are considered to be synonyms. A stereotype complaint about battery cages, or broiler
houses with no windows, or the fact that turkeys cannot mate on their own, is not completely covered by ideas
of either physical or mental well-being: the complaint that ‘it’s not natural’. Poultry welfare is a controversial
topic in modern animal husbandry because of the discrepancy of opinions regarding how animals should be
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treated and maintained. Part of this controversy is related to an apparent conflict of interest, as it is viewed (by
many) that any improvements in animal welfare will necessarily lead to a reduction in economic profit.
Health and welfare can also be interrelated: a healthy animal can and able to grow and/or produce in the
required way.
Features of the healthy poultry:
• The healthy poultry’s rowel, chine and ear flap are well developed, vermilion.
• Eyes are clear, bright-eyed.
• The optimal egg laying hen is relatively small body, lively temperament, fine-boned, cloaca is big, moist,
pink.
• The optimal broiler chicken is larger, calmer temperament, stronger bones, breast and thigh muscular,
feathering is dense, shiny.
Behaviour and welfare issues in poultry production
Broiler production
Broilers are hybrid birds produce the maximum amount of meat in a short period of time (few weeks). Leg
injuries, heart and circulatory problems can occur because of the fast growth rate and high density. Gathering
and transportation can also lead to broken legs and wings besides stress and fear.
11.1. táblázat - Table 11.1. Factors affecting the animal behaviour
Abiotic environment:
Biotic environment:
temperature
humans
light
conspecific
air
foreign/exotic species
ground/floor
parasites
machine
pathogens
building
apparatus
chemicals
11.3. ábra - Fig. 11.3. Broiler stock on deep litter
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Behaviour of laying hens in cages
Feed consumption may vary if the animal is outside the comfort zone, it can result in decreased feeding intensity
or extra consumption –up to 50 %. Drinking water consumption quantity can be 5-10 times higher than feed,
although it is different at various breeds/hybrids and determined largely by genetics. Low consumption is
favourable because it will result is dry manure.
11.2. táblázat - Table 11.2. Distribution of different behaviour forms of laying hens in
cages at 13 hour long illuminating period
Behaviour form
% of the full illuminating period
cage-pecking
9,8
feather-pecking
<1
eating
40
drinking
14
movement
21,3
preening
10,8
resting (sitting)
2,7
agressive pecking
<1
faecal occult
<1
egg laying
<1
(Bessei, 1980, cit. Scholtyssek, 1987)
11.4. ábra - Fig. 11.4: Caged laying hens
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There are symptoms of social stress that have negative effect on production, although laying hens have good
toleration of the small place and/or crowded housing (3-5 ind/cage). Due to the larger flock size more problems
can occur if kept on floor, the social problems will result social stress and lower feed intake. The forms of the
behaviour can be: comfort is not changing; slapping, head-shaking, wing-lowering; hysterical symptoms &
escaping.
Behaviour specialities of geese
Behaviour specialties, which have an effect on keeping technology in case of geese:
• Imprinting – in the early life stage
• Huddling together – as a result of stress– suffocation
• Social structure – harmful habits in high stock density
• Mating characteristic (evolving harems, genital injury and penis inflammation
11.5. ábra - Fig. 11.5. Geese farm
Animal welfare standards for poultry species
Animals should be managed to meet several requirements so that the best performance is achieved, and, at the
same time to be acceptable in the field of animal rights. These are the keys to good management and may be
used to test the management of a farm. These requirements may be called principles. The rights of the animals
are influence social demands, ethics, civil movements, but it can be abused in campaigns e.g. by extreme animal
right activists causing negative market effects. However, laws and legislation now are dealing with this issue in
developed countries to the adequate level. The principles of animal rights:
1. Every animal is subordinated to humans
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2. Different judgement of the animals eg. farm animals, Hobby-animals
3. The same rights for the humans and the animals – impossible
The animals have to right to:
• Hunger-free, thirst-free life
• Painless, injury-free, disease-free life & healing
• Protection against extreme environmental conditions and resting
• Natural behaviour
• Stress-free and fear-free life
The interest and awareness of the society’s in the welfare of farm animals is continuously increasing, especially
in case of intensive animal production. Consumer and public attitudes to animal welfare are likely to be
influential in determining decisions in legislation.
Malaise or well-being and stress
Performance is indicator of the well-being of a farm animal. Malaise/well-being doesn’t always show – eg. cage
keeping, but may be a problem despite high production, in order to provide basic conditions (feed intake,
drinking, climate). But the small space, minimal movement, group size are factors of stress. Adaptation to the
environment requires time and energy, it is especially important that technical conditions and biological needs
should be concise, however effective technology sometimes non-animal-friendly. Possibilities to solve this
controversy are selection for technological tolerance and change of species. In either way the aim is to decrease
the occurring loads of stressors and the induced status causing stress. Because the body protects itself, a startle
response and successful resistance against negative effects can easily lead to depletion. Consequently, malaise
or well-being can’t be measured exactly – is relative.
11.3. táblázat - Table 11.3. Measurement/estimation of malaise or well-being
Ethology
Production physiology
time & frequency of life processes
production data
posture
reproduction data
movements
injury
aversion, preference
disease
abnormal/bad habits
Possibilities to control well-being
From observation one can detect the mayor influencing factors, or can conduct preference tests of different
keeping methods to identify an measure the key elements of the technology. The behaviour types, such as
vacuum behaviour can be idle, or non-specific to the species (apathy). Stress conditions can also be observed or
measured my recording main physiological parameters. The physical features of the stress can be even severe,
starting from injury caused by technological elements, disease connected to keeping/farming mode or, in serious
cases mortality.
Way of measure/estimation:
• Personal observation – measure of life processes
• Instrumental measurement – heat, vapour, pollution, etc.
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• Photo, video recording – analysis
• Photocells – registering movements
• Instrumental control of the animals – respiration, heart, feed intake
General rules for the protection of animals say, that animals should be provided adequate living conditions
according to species, variety and age. If the animals could threaten / bother or disquiet each other than
separation is necessary. Animals kept in closed conditions are to be handled properly. Animal-friendly
technology should be preferred including professional care, preventing escape and a control at least once a day.
Beyond the above mentioned principles Animal Protection Act prescribe regular monitoring, undisturbed rest,
injury-free movement, protection from the harmful effects of weather. Animal-friendly technology should get
preference which prohibits cruelty to animals, including they should not be force-fed or not to be forced to
excessive effort, and not to set an animal against someone/something, and can’t be trained for animal fights
Basic animal welfare rules at specific technologies
Animal welfare rules at feather tear
• Completely mature feather – in 6 weeks
• Try-tear
• Warm and dry weather, or after keep in a warm, dry place
• Bathing before tear, and fresh litter
• A week before tear and 2 week after tear ad libitum feeding
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• Tear in the direction of the least resistance – wing, tail forbidden
• Vitamins against stress, feed supplement
• Average temperature at least 15 ºC and none 6 °C colder
• Keeping prescribed tear technique – process, clothing, person
• Injury management – separate
• Register – be kept for 5 years
Animal welfare rules for laying hens in cage farming
• 550 cm2 cage area
• Height 65 % up to 40 cm, but not less than 35 cm
• Floor is suitable for supporting claws of both feet
• Slope max. 14 %
• Feeding and watering 10-10 cm/hen, cage with 2 valves
• Two, or more level, if control is possible
• Beak-trimming up to 10 day old animal – direction of medical management
• At the end of lay do not completely deprive the light, the water and the feed at moulting
11.6. ábra - Fig. 11.7. Combined deep litter & battery floor technology
11.7. ábra - Fig. 11.8. New “EU conform” cage
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11. Animal behaviour, animal
welfare
Animal welfare rules at fattening for liver
• Only, who have appropriate experience and competence
• Feed delivery pipe is max. 22 mm, material is flexible
• 12-hour rest before the first cramming
• May be deep litter floors and slatted floors as well
• Transport in the best time of day – considering the season and the weather
11.8. ábra - Fig. 11.9. Fattening for liver
Signs of good and bad health in poultry
Important indications of poultry health include:
• alertness
• clear, bright eyes
• good posture
• vigorous movements if unduly disturbed
• active feeding and drinking
• clean, healthy skin, shanks and feet
Early signs of ill-health may include changes in:
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welfare
• feed and water intake
• preening
• chatter
• activity
• egg production is reduced
• defects in the quality of egg shell
Injured, dead or individual sick birds should be removed promptly. All dead birds are known as fallen stock and
must be disposed of by following certain guidelines and rules.
1. Questions:
1. What is the importance of ethology in the choice of the keeping technology?
2. What are the most typical forms of normal and abnormal behaviour in poultry?
3. What factors and how influencing the well-being of a poultry?
4. Are any breed specific/significant welfare concerns in poultry production?
5. What are the signs of good and bad health in poultry?
2. Annex 1.
Animal Protection Act since 1998
1998. XXVIII. Act on the Protection and Welfare of Animals
The animals to be able to feel, suffer and be happy, therefore respect for them and providing their well- being is
moral obligation.
Expand:
• Farm animals
• Research, experiment animals
• Race, sports
• Shepherd, guardian, saving, therapeutic
• Used for hunting
• Showman, used for presentation
• Hobby
• Hunting wild game
European Union law:
• 78/923. Decision of the Council on the protection of animals and farm animals
• 88/306. Decision of the Council on the protection of slaughter animals
• 88/166. Directive of the Council on caged hens
• 91/028. Directive of the Council on the protection during transport
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11. Animal behaviour, animal
welfare
• 91/029. Directive of the Council on the protection of calves, minimum requirements
• 91/630. Directive of the Council on the protection of pigs, minimum requirements
• 93/119. Directive of the Council on the protection of animal slaughter
• 98/58. Directive of the Council on the protection of farm animals
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12. fejezet - 12. Feeds - nutritional
value and use
Animals require a balance of nutrients for maintenance, growth, egg production, etc. that meets the requirements
at least cost. It is difficult and expensive to supply all nutrients at the exact needs of the poultry. Except water,
nutrients are provided in the diet via ingredients, such as cereals, animal & vegetables proteins, vegetable &
animal fats, macro & micro minerals and vitamin premixes. The following nutrients are considered both for the
birds needs and for the composition of the various ingredients:
Protein (crude protein), and its component amino acids are the important. There are essential amino acids
(methionine, lysine, tryptophan & threonine). Protein and amino acids are supplied by ingredients such as
soybean, canola or cottonseed meal. Protein sources from animals have limited use due to restrictions in the EU
(meat and poultry by-product meal), only fish meal can be used freely. Energy is another expensive nutrient in a
diet, and important because it affects feed intake: high energy results is low feed intake and vica-versa. The
sources are: corn, soybean meal, fat, wheat, meat meal, barley. Vitamins are supplied as synthetics, have two
types: fat soluble (A, D3, E, K) and water soluble (B vitamins eg. Riboflavin, biotin). Minerals are macro
(calcium, phosphorus), micro (copper, zinc, manganese, iron, iodine, selenium) and salt (sodium, chloride)
1. Nutritional Requirements of Poultry
More than 40 nutrients required by the poultry. These are arranged into six groups: water, carbohydrates, fats,
proteins, vitamins and minerals. The carbohydrates and fats are "energy feed", as they supply energy for the
maintenance, growth and production.
Feedstuffs are classed as primary source of energy or protein, and are more efficient if they are available in the
proper ratio, because excess is used as energy with increased excretion. Chickens should have 16-24% protein;
turkeys, 24-28% protein; for egg production 15-17% protein; for maintenance 10-12% protein. The highest
requirement is in the first 2 to 3 weeks. Overall protein level can be lower if the essential amino acids are all
present at the proper level.
The growth rate in young birds or egg production in adults is controlled by a) the genetic potential (broilers /
layers) b) the amount of energy and protein (and protein quality) available above the basic metabolic rate
(BMR).
2. Energy in Poultry Diets
Energy is a property that a nutrient possesses. Carbohydrates and fats are the main energy sources, which is
required for normal growth and activity. The energy ingested is stored as body fat. The diet should contain
energy proportional to other nutrients for the desired growth, production of eggs. It has been estimated that the
net energy value of the diet of the chicken ranges between 70% to 90% of the total energy.
Dietary nutrients that yield energy are protein, fat and carbohydrates. If fat and carbohydrate are in short supply,
protein is used by the animal as source of energy. Diets with high levels of energy and protein are called ing
„higher nutrient density” or „concentrated” feeds. This means that the diet is more dense, the bird will have to
eat less of it to obtain the required nutrients, feed:gain or feed:egg mass ratios are reduced, thus it results in
improved feed efficiency or feed utilization. Dietary energy level influence feed intake, as birds first eat to
satisfy their energy needs. Dietary energy is the main factor influencing feed cost but the protein level, essential
amino acids balance or other dietary nutrients can affect cost, too. So, the higher the energy level the higher the
diet cost and the lower is the feed consumption related to gain. The energy content is given in kilocalories per
kilogram of diet.
There are factors which interact to influence energy utilization (e.g. pen temperature). The energy utilization of
ingredients can be improved by:
• The addition of extra fat, which slows down the food passage and allows more time for digestive enzymes.
• Steam pelleting and conditioning to improve the utilization of certain nutrients.
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• Use of dietary enzymes help to break down dietary components.
• Properly proportioned saturated and unsaturated fats enhance fatty acid absorption.
• Addition of essential amino acids balance lower protein diet and reduce nitrogen excretion.
• Precision grinding allows more efficient enzyme action and enhanced nutrient availability.
3. Energy feeds
Energy sources are the major component, amounting to 50-70% of the diet, manly cereal grains, agro-industrial
by-products, but can be complemented by fats (both vegetable and animal origin) in the ration up to a level of 12
per cent, because fat utilization of poultry is very efficient.
Maize is the most often used grain in poultry rations, high in energy and a rich source of carotene and
xanthophyll pigment deposited in broilers and egg yolk. It can be mixed up to 60% poultry ration, and good for
fattening broilers, when mixed with wheat.
Wheat has a better feeding value then barley and oats. It is a good source of B-vitamins complex. Broken
wheat, wheat flour meal can be used up to a level of 50% in the broiler diet, but for the layers about 10-15%
mixed with other grains will be beneficial. Wheat bran is the coarse outer covering of the wheat kernel. It is an
excellent source of manganese, iron and a good source of riboflavin, pantothenic acid, choline, niacin and
thiamine.
Barley contains more fibre and less energy maize, higher fibre content, low in lysine, threonine, histidine
content and contains gluconate. It can be included in the diet at 20-40 %
Oats have high fibre, lower energy content in comparison to maize and wheat. It can be used up to 10 - 20% for
low energy feeds (e.g. pullet feeds) and broiler breeder replacement
Sorghum has lower energy and higher protein content as maize, it can be included at a level of 25-40% in the
diet.
Rice (broken rice), if available at economic cost can be used. Rice bran is the pericarp of the grain and good
quality rice polishing is rich in energy. These are excellent sources for many vitamins particularly, thaiamine
and niacin.
Millet (common millet) can be 50% and 100% replacement of maize in chick ration. First, it reduces the cost of
feeding in the starter ration and secondly the body weight gain in the chicken is faster than when fed only with a
maize included-diet
12.1. ábra - Fig. 12.1. Grains used in feeds
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12. Feeds - nutritional value and use
4. Protein in poultry diets
Proteins are main constituents of the muscles. Adequate supply of protein is essential for growth and egg
production. Proteins are made up of amino-acids, and these must be provided through dietary proteins. The
essential amino-acids are: arginine, lysine, histidine, leucine, isoleucine, valine, methionine, threonine,
tryptophan and phenylalanine. Glycine is essential for growing chicken but not for adult birds.
Soybean cake is an excellent source of vegetable protein, rich in lysine but deficient in methionine. It can be
used to the extent of 40% in the poultry diet, but it has an anti-nutritional factor called trypsin inhibitor.
Sunflower cake has slightly lower protein content than groundnut meal, but with good quality protein. It is a
good source of arginine and methionine than soybean, but is poor in other essential amino-acids.
Groundnut cake is one of the richest vegetable protein concentrates, highly palatable and used extensively (up
to 40%) in the rations. It is low in lysine, methionine and cystine but high in like arginine.
Cottonseed cake has a high protein content but is deficient in lysine. It is used up to 5%, because of the
presence of free gossypol (growth depression causing in young chicken and produce discoloured yolks in stored
eggs), so it has to be de-gossypolized before use.
12.2. ábra - Fig. 12.2. Oil cakes (soybean, sunflower, groundnut & cottonseed)
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12. Feeds - nutritional value and use
Protein sources are animal derived protein meals (meat and bone meal, hydrolyzed feather meal, blood meal,
and fish meal). Because of the perceptions, interpretations and actions established in connection with bovine
spongiform encephalopathy (BSE) commonly referred to as “mad cow disease”, a zoonosis (i.e. disease that can
be transferred from animals to humans) use of protein meal of animal origin for feeding farm animals is
controlled/restricted in Europe (except for fish meal).
Animal protein sources are superior in terms of protein quality to vegetable proteins. They contain higher levels
of limiting amino-acids (lysine and methionine) than vegetable protein sources and are employed to make up
balanced amino-acids.
Fish meal is manufactured from clean dried and ground tissues of undecomposed whole fish, with or without
extraction of part of the oil, and contains not more than.3% common salt Fish meal is the is the best of source of
high quality protein. It is highest in all the required amino-acids and is a good source of calcium, phosphorus
and certain vitamins. It can be used at a maximum level of 10 per cent.
Meat meal is a good source of high quality protein and important source of calcium and phosporus. It can
constitute 5-10% of the diet.
Blood meal is an animal protein source with high lysine content, but imbalanced amino-acid composition so it
can be used up to. 1-2%.
12.3. ábra - Fig. 12.3. Protein meals (fish, meat & blood meal)
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12. Feeds - nutritional value and use
5. Minerals
The body of the chicken and the egg (excl. the shell) contain nearly 4% and 1 % of mineral matter, respectively.
Vegetable protein ingredients are poor in minerals compared with those of animal proteins. The common
mineral supplements are: limestone, bonemeal, oyster shell, common salt, dicalcium phosphate, manganese
sulphate, potassium iodide, and superphosphate. Chicken need minerals for their proper nourishment, these are:
calcium, phosphorus, sodium, potassium, chlorine, magnesium, manganese, zinc, iron, copper, molybdenum,
selenium and iodine.
Calcium and phosphorus constitute over 70% of the body ash, mostly in combination with each other, so
deficiency of either limits the nutritive value of the other. Calcium is necessary for the formation of the skeletal
system. In the layers, it is utilized for the formation of egg shells, phosphorus is important in the metabolism of
carbohydrates and fats. Therir the ratio should be of 1-2.2 : 1 for optimum results. Out of this range (3.3: 1) is
produces leg abnormalities and rickets.
6. Vitamins
Leaf-meals either fresh or dehydrated can be employed to provide certain vitamins. Yeast can be used to provide
some of the B-complex group of vitamins. Fish oils provide vitamin A & D. Now-a-days, the vitamins in pure
form are being used to increase; the nutritional levels of vitamins which may be deficient in diets.
7. Water
Water is an essential nutrient, so the supply of good quality water is indispensable for better growth and
reproductive performance in poultry, and there is a need for complete examination of water before it is supplied
to the birds.
Animals can tolerate a loss of 98% body fat and 50% body protein but not more than 20% body water. A young
growing chicken amd hens will consume water at about 20% and 14% of their body weight at 20 ºC and double
that amount at 35 ºC, respectively. If water consumption is restricted, growing chickens will grow more slowly.
Deficiency of water limit growth rate and production, and may even lead to death. This is called water
intoxication as it has an adverse effect on the metabolic function.
Dry feed contains only 10-15% water, consequently poultry need about twice as much water as feed, plus water
should be easily available free-choice. If water is not freely and easily available adults will lay fewer eggs and
may suffer from kidney disease. Layers that go without water for a day or two will stop laying and may take 2-3
weeks to recover. Newly hatched chicks should have water before or at the same time as they receive their first
feed. It must not be in an open pan or trough that the chicks can get into. Wet chicks lose body heat quickly and
may die.
12.1. táblázat - Table 12.1. Factors limiting the use of alternative feed ingredients in
poultry feed formulations
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12. Feeds - nutritional value and use
Nutritional aspects
Technical aspects
• Variability
(or
lack
of •
consistency) in nutrient quality
•
• Limited information on the
availability of nutrients
•
• High fibre content
Socio-economic aspects
Seasonal and unreliable supply
Bulkiness,
characteristics
• Competition with use as human
food
physical
• Poor prices relative to other arable
crops (farmer)
Need for de-hulling and/or
processing
(drying, • Cost per unit of energy or limiting
detoxification)
amino acids, relative to traditional
• Presence
of
anti-nutritional
feedstuffs (feed manufacturer)
factor(s)
• Limited
research
and
development
facilities
for • Cost of processing
• Need
for
nutrient determining nutrient composition
supplementation (added cost)
and inclusion levels in poultry
diets
8. Feed formulation – formulated feeds
Nutrient requirements of poultry raised in controlled environment is supplied by single uniform mixture (diet)
containing all feed ingredients. Careful manufacturing is the central issue in the poultry industry because it has a
mayor role in ensuring good nutrition, moreover, feed costs account for more than 70% of the total production
costs for most types of poultry. Feed formulation should ensure that feed ingredients are economically used for
optimum growth of chickens, so that returns are maximised through use of adequate diets. Large-scale farmers
depend on commercial feed mills for their feeds, thus it is therefore essential that formulations are accurate.
In order to meet the dietary requirements of poultry, the needs are to carefully be identified and precisely met
using a single uniform feed. This is also necessary for large scale and continuous production of modern poultry
farms, so that the quality of the product (meat or eggs) remains stable over relatively long periods of time. The
product quality can also be easily predicted if the same diet formula is used and all other factors remain
unchanged (which is the situation in controlled environment).
Pelleting is widely practiced in feed manufacturing, and feeding a pelleted diet usually leads to an improvement
in performance. Pelleting may increase nutrient digestibility in some constituent feedstuffs; however, the
primary result is improved use of the nutrients already available apparently because of reduced physical activity
by the bird. Generally, pelleting facilitates feed intake, increases net energy of production from metabolizable
energy (ME), and reduces overall feed wastage. These benefits are accentuated as feed nutrient level decreases
and as birds become progressively older, provided the feed remains in pelleted form.
9. Factors affecting the quality
Kramer (1951) defined quality as “the sum of characteristics of a given food item which influence the
acceptability or preference for that food by the consumer”.
Factors affecting meat quality
There are several factors that are affecting product quality. These are described as follows.
Effect of rearing conditions: differences in meat quality may be due to strain, age and nutritional regime, but
there are interactions to this by temperature, ventilation rate and nutrition on quality as well as on biological
efficiency.
Handling and slaughtering conditions: financial loss are mostly caused by inhumane slaughter and bleeding
of the carcass, moreower it has important consequences for aesthetic and physical quality and a matter of animal
welfare. Poultry has to be handled to avoid bruising and broken bones and later to have been properly
slaughtered so as to avoid redness, red wings, broken wings, blood specks and toughness in the meat.
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Quality maintenance after slaughtering: low temperature around 0 °C extends shelf-life, and that of -18 °C
are used to maintain colour and minimise freezer burn for frozen poultry. Controlled atmosphere packaging
using gas flushing, vacuum packing and modern laminated films barrier bags, etc. are also effective ways of
quality control.
Factors affecting egg quality
Eggs are classed as either Class A or Class B in the EU, and only eggs graded Class A can be sold for direct
human consumption.
Egg shell quality is affected by egg size, age of bird, stress, elevated environmental temperature nutrition and
water quality, mycotoxicosis and genetics. Internal egg quality declines immediately after the egg is laid, so egg
handling and storage practices do have a significant impact on it.
Yolk quality is determined by the colour, texture, firmness and smell of the yolk.
Albumin quality is related to the consistency, appearance and the functional properties.
Overall quality include blood spots (associated with the yolk) and meat spots (small pieces of body tissue)
bacterial or fungal contamination, off odours / flavours.
12.4. ábra - Fig. 12.4. Egg structure & quality
10. Questions:
1. What are the most important sources of energy in poultry?
2. What are the most important sources of protein in poultry?
3. What are the most important feed components other than energy and protein?
4. Factors affecting the meat and egg quality?
5. What are formulated feeds and why are they important in poultry production?
11. Annex 1.
12.2. táblázat - Alternative energy sources that can replace maize in poultry diets
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12. Feeds - nutritional value and use
Feedstuff
Comments
Wheat
Can be used when cost-competitive Limitation: high non-starch polysaccharide contents
result in intestinal digesta viscosity problems; can be used without restriction when
exogenous carbohydrases are added
Sorghum
Limitation: tannins lower protein and energy digestibility; low-tannin sorghum can
completely replace maize
Millets
Can replace 50–65% of maize, depending on millet type; Limitations: high fibre
contents, presence of tannins
Rice bran/polishing
Limitations: high fibre, phytic acid, rancidity; good-quality material can be used at levels
of 5–10% in broiler diets and up to 40% in layer diets
Wheat bran/pollard
Limitation: high fibre; can be used at levels less than 5% in broiler diets and up to 15%
in layer diets
Cassava root meal
High in starch, excellent energy source Limitations: low protein, powdery texture, needs
detoxification to remove the cyanogenic glucosides; can be used at levels of 30–40% in
nutritionally balanced, pelleted diets
Cassava peel meal
Limitations: high fibre, very high levels of cyanogenic glucosides, needs processing;
carefully prepared meal may be used at 5% level
Sweet potato tuber High in starch, good energy source Limitation: powdery texture; can be used at levels up
meal
to 50% in nutritionally balanced, pelleted diets
Taro
Limitations: poor palatability caused by calcium oxalate, needs processing; processed
meal can be used at up to 10%
Banana and plantain Limitation: low palatability due to tannins in the peel; removal of peels improves
meal
nutritive value; inclusion must be limited to 10–20% Breadfruit meal Good energy
source; can be included at up to 30%
Jack seed meal
Limitations: lectins in raw seeds, needs processing; processed meal can be included at up
to 30%
Mango seed kernel Limitation: high levels of tannins; processed meal can be used at levels of 5–10% Date
meal
waste Limitation: high sugar content; use must be restricted to 30% of the diet
Animal fat
Tallow, lard and poultry fat; high-density energy sources that enable the use of
lowenergy feedstuffs in formulations; can be used at up to 5–8%
Distillers
dried High fat content (10%), good energy source; can be used at up to 25%
grains with solubles
(DDGS)
12. Annex 2.
12.3. táblázat - Alternative protein sources that can replace soybean meal in poultry
diets
Feedstuff
Comments
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12. Feeds - nutritional value and use
Oilseed meals1
Cottonseed meal
Limitations: high fibre, presence of gossypol; low-gossypol meal can be used at
levels of 10–15% in broiler diets; limit use in layer diets because of effects on
internal quality of eggs
Canola meal
Limitation: glucosinolates; low-glucosinolate meals can be used at up to 30%
Groundnut meal Limitations: tannins, aflatoxin; good-quality meal can be used at
up to 15% Sunflower meal Limitation: high fibre Rich in methionine; can be used
at up to 15%
Sesame meal
Limitation: high phytate content Good source of methionine; can be used at up to
15%
Palm kernel meal
Limitations: high fibre, poor texture, low palatability; good-quality meal can be
used at levels of 5–10% in broiler diets and up to 30% in layer diets
Copra (coconut) meal
Limitations: low protein, mycotoxins; can be used at up to 20%
Rubber seed meal
Limitations: low protein, presence of cyanogenic glucosides, requires processing;
can be used at up to 10%
Grain legumes2 (lupins, Limitations: presence of anti-nutrients, low in methionine; can be used at up to 20–
field peas, chick peas, 30% when processed and supplemented with methionine; current cultivars contain
cowpeas, pigeon peas, low levels of anti-nutrients
faba beans, etc.)
Green meals (leaf meals, Rich in minerals, moderate levels of protein Limitations: high fibre, high moisture
aquatic plant meals)
content and requires drying; most green meals can be used at levels less than 5%;
some, such as duckweed, can be included at higher levels
Distillery
(DGGS)
co-products Good source of protein, amino acids and available energy Limitation: variable
amino acid availability; good-quality meals can be used at up to 25%
1 Compared with soybean meal, other oilseed meals have lower contents of available energy, protein and
essential amino acids, and require supplementation with synthetic amino acids and energy sources. Suggested
inclusion levels are for nutritionally balanced diets.
2 A range of grain legumes are grown in developing countries. Only selected species are identified here. It must
be noted that all raw legumes contain a number of anti-nutritive factors, but most of these can be eliminated by
processing.
13. Annex 3.
12.4. táblázat - Alternative animal protein sources for use in poultry diets
Feedstuff
Comments
Dried fish silage
A way of turning waste fish into quality animal protein supplement; can
completely replace fishmeal Limitation: requires drying Blood meal High protein
content Limitations: extremely deficient in isoleucine, poor palatability; can be
included at no more than 5%
Blood meal
High protein content Limitations: extremely deficient in isoleucine, poor
palatability; can be included at no more than 5%
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Hydrolysed feather meal
High protein content Limitations: deficient in several essential amino acids, low
availability of amino acids; can be included at no more than 5%
Poultry by-product meal
Feeding value similar to that of meat meal; recommended inclusion level of 5%
Skimmed milk powder
Reject milk powder; good-quality protein; can be included at up to 5%
Novel sources: insects, fly Good protein sources; can replace 50% of fishmeal in formulations; useful
larvae,
earthworms, supplements for family poultry Limitation: no commercial production and
termites, bees, snails, etc. harvesting systems
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13. fejezet - 13. Nutrition by genotype
(species/variety/hybrid)
Both poultry meat and egg industries are thriving today, because of the image of ‘healthy product’, containing
less fat than beef or pork products, and, because of closed production environment and uniformed production
consumers are aware of the quality and composition of the products. Poultry nutrition plays a significant role in
quality production having effect on quality issues such as enrichment of fatty acids that are useful in human
nutrition.
The success (profitability) mostly depends on the type, source and quality of feed, which accounts for 70% of
the total cost of egg production and 55% of the cost of broiler production. Availability of feeds and their
ingredients contributed significantly to the increased poultry production. Nutrient requirements for many
poultries are known and standards are available for the dietary energy, amino-acids and other nutrients
necessary for the birds. Feed ingredients from different sources must be put together in a balanced and available
form, so the ingredients can supply all the nutrients required for growth and production. The proper mixture
takes into consideration the genetics (breed/hybrid), environment management practices, health status, the
relative cost of ingredients and their changes, etc.
Poultry industry is the most significant user of animal protein, accounting for 37% of the annual production.
valuable economic, biosecurity and environmental resources for the animal industries. Resources and a
synergism that has allowed for the sustainable and the most efficient, safest meat producing system in the world.
As the result of the genetic improvement and advanced feeding technology the growth rate and feed conversion
of the birds have been maximised.
Nutrition should follow the biological specifics of the species/variety/hybrid. Adequate protein supply is needed
to enable intensive protein incorporation, but one have to keep in mind that protein incorporation is followed by
fat production, which decreases economic sustainability of the production. In intensive poultry growing or in
egg production frequent (even bi-weekly) changing of nutrient requirements must be met, moreover, there are
some differences observed in the requirement of the sexes. In order to meet this, nutritionists have developed the
method called “phase feeding” where the composition of the feed is set to best meet the given age group being
raised.
1. Nutrient requirements of meat chickens (broilers)
The combination of the nutrient levels in the diet and the amount of feed eaten results determine the intake of
nutrients. Several factors influencing feed intake of modern broiler chickens: bodyweight, age and sex, nutrient
levels of diets, etc.
Feeding strategies for broiler chickens depending on the genetics, available technology and – most importantly –
the market for the product. Strategies for “whole bird” market is different from those broilers destined to be sold
as pieces. Moreover, the nutrient intake of fast growing ones must be well controlled to avoid metabolic diseases
such as ascites and leg weakness. Table 13.1. shows data on typical levels of selected nutrients for broiler diets.
13.1. táblázat - Table 13.1. Bodyweight and cumulative feed consumption for male and
female broilers (g)
Age(weeks Male Bodyweight
)
Male Cumulative Feed Female Bodyweight
Intake
Female
Cumulative
Feed Intake
0
40
0
40
0
1
170
150
165
145
2
450
480
420
460
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13. Nutrition by genotype
(species/variety/hybrid)
3
865
1120
780
1030
4
1410
2020
1250
1825
5
2250
3200
1750
2830
6
2700
4500
2300
4020
7
3350
6000
2800
5400
8
3900
7400
3300
6800
9
4400
8800
3700
8200
Source: Poultry CRC
13.2. táblázat - Table 13.2. Examples of broiler diets
Nutrients
Starter
Grower
Finisher
Nutrients
Age fed
0-10
11-24
25-
Digestible M 0.94
ethionine
+Cystine
(%)
0.84
0.72
Crude protein (%)
22-25
21-23
19-21
Total
Threonine
(%)
0.93
0.82
0.71
ME (MJ/kg)
12.60
13.30
13.50
Digestible
Threonine
(%)
0.80
0.70
0.61
ME (kcal/kg)
3010
3175
3225
Total
Trypophan
(%)
0.25
0.22
0.19
Total Arginine (%)
1.48
131
1.11
Digestible
Tryptophan
(%)
0.22
0.19
0.17
Digestible Arginine 1.33
(%)
1.18
1.00
Total Valine 1.09
(%)
0.96
0.81
Total Lysine (%)
1.44
1.25
1.05
Digestible
Valine (%)
0.83
0.70
Lysine 1.27
1.10
0.92
Calcium (%) 1.0
0.90
0.85
Methionine 0.51
0.45
0.39
Available
0.50
phosphorous
(%)
0.45
0.42
Digestible
(%)
Total
(%)
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Starter Grower Finisher
0.94
13. Nutrition by genotype
(species/variety/hybrid)
Digestible
Methionine (%)
0.47
0.42
0.36
Total
Methionine 1.09
+Cystine (%)
0.97
0.83
Sodium (%) 0.16
Source: Ross
Manual 2009
0.16
Broiler
0.16
Management
13.1. ábra - Fig. 13.1. The Broiler growth curve
(Source: http://www.ihc-poultry.com)
2. Nutrient requirements of egg laying chickens/hens
There are a number of factors that influence voluntary feed intake. Typical feed consumption for modern brownegg laying hens in relation to target body weight is shown in Table 13.3, laying period start from Week 18, hens
reaching peak around week 32, and maintain production until 65-68 weeks of age. Feed intake will increase to
100-105g per day while the body weight of the hen will reach 1700-1800g.
13.3. táblázat - Table 13.3. Body weights and associated feed consumption for a brownegg laying breed during the growing period
Age(wk)
Body weight(g)
Feed
consumption
Age(wk)
Body weight(g)
(g/bird/day)
Feed
consumption
(g/bird/day)
1
70
13
10
870-970
56
2
115
20
11
960-1080
61
3
190
25
12
1050-1117
66
4
280
29
13
1130-1250
70
5
380-390
33
14
1210-1310
73
6
480-500
37
15
1290-1370
75
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13. Nutrition by genotype
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7
580-620
41
16
1360-1430
77
8
680-750
46
17
1500-1540
80
9
770-860
51
Source: Hy-Line Variety Brown Commercial Management Guide 2009
13.2. ábra - Fig. 13.2. The phases of egg production
Chicks require relatively high levels of energy, protein and the vitamins and minerals for the start to provide the
nutrients needed for rapid growth and feather development. Energy and other nutrient requirement are reduced
as soon as the chicks are feathered fully. In order to reach maturity at optimum age and to avoid obesity. The
aim of feed management to maintain a growth rate that will lead to the pullet reaching sexual maturation. The
time at which a pullet will start laying eggs is affected by age, bodyweight and day length (illumination). Layer
pullet diets have lower energy and protein concentration than chick diets, ad it vary by breeds/hybrids and
phases of maturation/growth. It is common to use so-called ‘pre-lay’ diet to increase key nutrient levels (e.g.
calcium for laying eggs).
Energy demand of the chickens can be calculated following the rule of thumb:
• Synthetizing 1g protein requires 55 KJ ME energy
• 1g grease building-in requires 42 KJ ME energy
It is also important to consider the energy required for production, which is the “residue” after the energy
demand required for maintenance (sustaining/supporting life) is met. As a natural process, animals satisfy their
maintenance energy before using the feed for production, so if it is underestimated the production performance
is suboptimal due to the lacking energy. The maintenance energy requirement can be calculated with the
following equation:
ME=418 KJ x live weight (kg)0,75
e.g.: 40 g live weight poult 40 KJ/day, 2000 g live weight broiler 700 KJ/day
As described above, protein demand is made up of several parts:
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13. Nutrition by genotype
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Daily maintenance protein demand is equivalent to 250 mg of endogenous N loss, i.e. 1,6 g/body weight kg.
The daily protein gain is 17-25 % of the weight gain, can be calculated as: daily weigth gain x (0,17-0,25)
The feather growth is 4-7% of the daily weight gain : daily weigth gain x (0,04-0,07) x 0,82
In equation:
Daily protein demand={(live weight, kg x 1,6) + (daily weight gain x 0,17-0,25) + (daily weight gain x 0,040,07) x 0,82} x 1,66
The protein utilization is 60%, and therefore should be multiply by 1,66
Table 13.4. shows data on typical nutrient levels for layer diets for the growing period.
13.4. táblázat - Table 13.4. Nutrient levels in animal protein meals
Nutrient
Meat & Bone
Blood
Feather
Poultry
Metabolisable
Energy (MJ/kg)
11.2
15.2
13.7
13.1
Crude Protein %
50.4
88.9
81.0
60.0
Fat %
10.0
1.0
7.0
13.0
Calcium %
10.3
0.4
0.3
3.0
Phosphorus %
5.1
0.3
0.5
1.7
Lysine %
2.6
7.1
2.3
3.1
Methionine %
0.7
0.6
0.6
1.0
Cystine %
0.7
0.5
4.3
1.0
Source: adapted from Hamilton (2002)
Feed intake increases to 100-105 g per day, the diets optimise egg production (in terms of egg numbers, egg size
or egg mass) and provide the nutrition required to maintain the desired bodyweight. Different feeding strategies
are recommended by breeds/hybrids, including the stages/number of diets fed during laying. Calcium is
increased in the ration for egg shell formation. Table 13.5. provides data on typical nutrient levels for layer
diets.
13.5. táblázat - Table 13.5. Growing period nutrition recommendations
Product
Weeks
Age
in
Starter
Grower
Developer Pre-Layer
0-6
6-12
12-15
15-1 %Prod.
Nutrient
Protein (min.)
%
20.0
17.50
15.50
16.50
Metabolisable
Mj/Kg
11.5-12.4
11.5-12.6
11.3-12.4
11.4-12.4
Energy
Kcal/Kg
2750-2970
2750-3025
2700–
2725-2980
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13. Nutrition by genotype
(species/variety/hybrid)
2970
Lysine (min.)
%
1.10
0.90
0.66
0.80
Methionine (min.)
%
0.48
0.41
0.32
0.38
+ %
0.82
0.71
0.58
0.65
Tryptophan (min.)
%
0.20
0.19
0.18
0.19
Threonine (min.)
%
0.73
0.55
0.52
0.55
Calcium (min.)
%
1.00
1.00
1.00
2.75*
Phosphorus %
0.45
0.43
0.42
0.40
Methionine
Cystine (min.)
Av
(min.)
Sodium (min.)
%
0.18
0.18
0.18
0.18
Chloride (min.)
%
0.18
0.18
0.18
0.18
Source: Hy-Line Variety Brown Commercial Management Guide 2009
13.6. táblázat - Table 13.6. Examples of layer diets (at 100g per day intake level)
Nutrients
Units
1%-32 weeks 32-44 weeks
44-55 weeks
+55 weeks
ME
MJ/kg
11.60-11.97
11.41-11.97
11.20-11.97
10.68-11.83
ME
kcal/kg
2770-2860
2725-2860
2675-2860
2550-2825
Crude protein
%
19.80
17.50
17.00
16.00
Lysine
%
1.02
0.93
0.89
0.83
Methionine
%
0.51
0.46
0.41
0.38
Linoleic acid
%
1.10
1.60
1.60
1.60
Calcium
%
4.40
4.25
4.50
4.75
Availablephos %
phorous
0.48
0.40
0.36
0.35
Source: Hy-Line Variety Brown Commercial Management Guide 2009
3. Feeding chickens/hens
Rations
Age groups of poultry (i.e. body size) determine the quantity of the ration to be fed. Started diet of fine texture
containing finely broken rice, small grains, bread crumbs etc. are given to young chicks as the first feed with
vitamins, minerals, antibiotic feed supplements and coccidiostat. Chick feed is increased gradually after 2
weeks, the quantity varying from 10 g to 50 g per chick according to their age (0-8 weeks). Enriched Grower
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13. Nutrition by genotype
(species/variety/hybrid)
mash (with vitamins, minerals - essential nutrients) is gradually substituted chick mash after 8 weeks, the
quantity varies from 50 to 80 g per day per individual, according to age (8-20 weeks). Fully vitaminised and
mineralised layer mash is introduced after week 18. In case of high numbers of hens and intensive production
pellets are used instead of mash being more economical and easy-to-use. The rations are 80-200 g per bird per
day, depending on the bodyweight and production level.
Time of feeding
The birds will learn and expect their feed in punctual times, so the regularity of feeding is important to maintain
optimum growth, production and good health. At the first phase (up to 8 weeks of age) chicks are fed 5 to 6
times a day in small quantities. One can modify timings if the management of the farm requires so to suit the
current needs, but regularity is important in order to train the birds to adjust to these timings.
13.7. táblázat - Table 13.7. Requirement of other minerals for poultry
No
Mineral (g/kg)
Pullets
Layers
1-6 weeks
7-12 weeks
13-20
weeks
broilers
1-3 weeks
4-8 weeks
1
Phosphorus
4.00
3.50
3.00
3.00
4.00
3.50
2
Magnesium
0.45
0.30
0.30
0.40
0.45
0.45
3
Sodium
1.20
1.00
1.00
1.30
1.45
1.30
4
Potassium
1.50
1.45
1.30
1.50
2.00
2.00
5
Chloride
1.10
0.90
0.90
1.20
1.35
1.35
13.8. táblázat - Table 13.8. Specifications in diet for chicken
N
o
Broiler
Broiler
Chick (0-8 Grower (8- Layer (20- Breeder (20starter (0-6 finisher (6-9 weeks)
20 weeks) 80 weeks
80 weeks)
weeks)
weeks)
1 Metab. energy (kcal/kg), 2,900
min.
3,000
2,700
2,700
2,00
2,800
2 Crude
protein
minimum
17
22
16
18
18
3 Crude fibre % maximum 6
6
7
8
8
8
4 Acid-insoluble
max.
3
4
4
4
4
tot. 0.90
0.90
1
0.70
0.50
0.50
6 Aminoacids % minimum 0.75
0.75
0.75
0.50
0.50
0.50
7 Methionine % minimum
0.35
0.35
0.35
0.25
0.25
0.25
8 Vitamin A, IU/kg
6,000
6,000
4,000
4,000
8,000
8,000
5 Lysine %
sulphur
ash
min.
% 22
% 3
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13. Nutrition by genotype
(species/variety/hybrid)
9 Vitamin D,IV/kg
600
600
600
600
1,200
1,200
1 Thiamine, mg/kg
0
2
2
6
6
6
6
1 Riboflavin, mg/kg
1
5
5
5
5
5
8
1 Pantothenic acid, mg/kg
2
12
12
10
10
15
15
1 Nicotinic acid, mg/kg
3
40
40
30
20
20
20
1 Biotin, mg/kg
4
0.10
0.10
0.10
0.10
0.15
0.15
1 Vitamin B12, mg/kg
5
8
8
15
15
15
30
1 Alpha tocopherol, mg/kg 20
6
20
10
10
10
20
1 Choline chloride, mg/kg
7
1,400
1,300
-
-
1,300
1,400
1 Linoleic
8 minimum
acid
%, 1
1
1
1
1
1
1 Salt (as
9 maximum
NaCl)
%, 0.60
0.60
0.60
0.60
0.60
0.60
1
1
1
2.75
2.75
0.50
0.50
0.50
0.50
0.50
2 Calcium %, minimum
0
2 Avail.
1 min.
phosphorus
1
%, 0.50
2 Manganese, mg/kg
2
60
60
55
55
55
55
2 Iodine, mg/kg
3
1
1
1
1
1
1
2 Copper, mg/kg
4
4
4
2
2
2
2
2 Zinc, mg/kg
5
50
50
-
-
-
-
2 Moisture %, maximum
6
10
10
10
10
10
10
13.3. ábra - Table 13.9. Requirement of other minerals for domestic fowls
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13. Nutrition by genotype
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4. Feeding Turkeys
Breeders (birds for reproduction) and broilers (birds for growth & meat production) require different nutrients,
especially in the proportion of nutrients. They require feed in phases (starter, grower and finisher), however
turkey poults have a much higher protein requirement than chickens. It starts at 22 – 24% protein content until
5-8 weeks of age, than reduces to app. 20% in the finisher ration. Breeder turkeys require 16% protein. Mediumand small-type turkeys finish earlier than the large, due to the different growth rates, but to reach this energy and
protein levels are to be set to supply near-maximum growth rate, i.e. meeting the biologically possible limit.
Starting poults have high protein requirement (28%).
13.9. táblázat - Table 13.10. Examples of turkey diets
Nutrien Starter1
ts
Starter2
Grower3 Grower4 Developer5 Finisher6
Crude 28
protein
(%)
26
23
21.5
18
16
ME
2900
(kcal/kg
)
3000
3050
3100
3200
3300
Lysine
(%)
1.70
1.60
1.50
1.30
1.15
1.00
Methio 0.62
nine
(%)
0.55
0.50
0.47
0.42
0.34
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Calciu
m (%)
1.4
1.3
1.2
1.3
1.0
0.90
Availab 0.7
le
phosph
orous
(%)
0.6
0.5
0.6
0.5
0.40
Sodium 0.18
(%)
0.18
0.17
0.17
0.17
0.17
Source: Commercial Poultry Nutrition, 2nd Ed. S. Leeson and J. D. Summers. Pub University Books, Canada,
1997
13.10. táblázat - Table 13.11. Body Weights and Feed Consumption of Large-Type
Turkeys during the Holding and Breeding Periods
Females
Males
Age (weeks)
Weight (kg)
Egg Production Feed
(%)
Turkey
(g)
per Weight (kg)
Daily
Feed per Turkey
Daily (g)
20
8,4
0
260
14,3
500
25
9,8
0
320
16,4
570
30
11,1
0
310
19,1
630
35
11,1
68
280
20,7
620
40
10,8
64
280
21,8
570
45
10,5
58
280
22,5
550
50
10,5
52
290
23,2
560
55
10,5
45
290
23,9
570
60
10,6
38
290
24,5
580
13.11. táblázat - Table 13.12. Growth Rate and Feed and Energy Consumption of
Large-Type Turkeys
Age
(weeks)
Body Weight (kg)
Feed
Consumption Cumulative
Feed ME Consumption per
per Week (kg)
Consumption (kg)
Week (Mcal)
Male
Female
Male
Female
Male
Female
Male
Female
1
0,12
0,12
0,1
0,1
0,1
0,1
0,28
0,28
2
0,25
0,24
0,19
0,18
0,29
0,28
0,53
0,5
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13. Nutrition by genotype
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3
0,5
0,46
0,37
0,34
0,66
0,62
1
1
4
1
0,9
0,7
0,59
1,36
1,21
2
1,7
5
1,6
1,4
0,85
0,64
2,21
1,85
2,5
1,9
6
2,2
1,8
1,1
0,8
3,31
2,65
3,2
2,3
7
3,1
2,3
1,4
0,98
4,71
3,63
4,1
2,8
8
4
3
1,73
1,21
6,44
4,84
5
3,5
9
5
3,7
2
1,42
8,44
6,26
6
4,3
10
6
4,4
2,34
1,7
10,78
7,96
7
5,1
11
7,1
5,2
2,67
1,98
13,45
9,94
8
5,9
12
8,2
6
2,99
2,18
16,44
12,12
9
6,8
13
9,3
6,8
3,2
2,44
19,64
14,56
9,9
7,6
14
10,5
7,5
3,47
2,69
23,11
17,25
10,8
8,4
15
11,5
8,3
3,73
2,81
26,84
20,06
11,6
9
16
12,6
8,9
3,97
3
30,81
23,06
12,3
9,6
17
13,5
9,6
4,08
3,14
34,89
26,2
13,1
10,1
18
14,4
10,2
4,3
3,18
39,19
29,38
13,8
10,5
19
15,2
10,9
4,52
3,31
43,71
32,69
14,5
10,9
20
16,1
11,5
4,74
3,4
48,45
36,09
15,2
11,2
21
17
4,81
53,26
15,9
22
17,9
5
58,26
16,5
23
18,6
5,15
63,41
17,1
24
19,4
5,28
68,69
17,4
13.12. táblázat - Table 13.13. Nutrient Requirements of Turkeys (Males and Females) as
Percentages or Units per Kilogram of Diet (90% dry matter)
Nutrient
Protein
Unit
%
weeks
Breeders
0-4
4-8
8-12 12-16 16-20 20-24 Holding Laying
28
26
22
19
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16,5
14
12
14
13. Nutrition by genotype
(species/variety/hybrid)
Arginine
Glycine
serine
%
+ %
1,6
1,4
1,1
0,9
0,75
0,6
0,5
0,6
1
0,9
0,8
0,7
0,6
0,5
0,4
0,5
Histidine
%
0,58
0,5
0,4
0,3
0,25
0,2
0,2
0,3
Isoleucine
%
1,1
1
0,8
0,6
0,5
0,45
0,4
0,5
Leucine
%
1,9
1,75
1,5
1,25
1
0,8
0,5
0,5
Lysine
%
1,6
1,5
1,3
1
0,8
0,65
0,5
0,6
Methionine %
0,55
0,45
0,4
0,35
0,25
0,25
0,2
0,2
Methionine %
+ cystine
1,05
0,95
0,8
0,65
0,55
0,45
0,4
0,4
Phenylalani %
ne
1
0,9
0,8
0,7
0,6
0,5
0,4
0,55
Phenylalani %
ne
+
tyrosine
1,8
1,6
1,2
1
0,9
0,9
0,8
1
Threonine
1
0,95
0,8
0,75
0,6
0,5
0,4
0,45
Tryptophan %
0,26
0,24
0,2
0,18
0,15
0,13
0,1
0,13
Valine
%
1,2
1,1
0,9
0,8
0,7
0,6
0,5
0,58
Linoleic
acid
%
1
1
0,8
0,8
0,8
0,8
0,8
1,1
Calcium
%
1,2
1
0,85
0,75
0,65
0,55
0,5
2,25
Nonphytate %
phosphorus
0,6
0,5
0,42
0,38
0,32
0,28
0,25
0,35
Potassium
%
0,7
0,6
0,5
0,5
0,4
0,4
0,4
0,6
Sodium
%
0,17
0,15
0,12
0,12
0,12
0,12
0,12
0,12
Chlorine
%
0,15
0,14
0,14
0,12
0,12
0,12
0,12
0,12
Magnesium mg
500
500
500
500
500
500
500
500
Manganese mg
60
60
60
60
60
60
60
60
Zinc
mg
70
65
50
40
40
40
40
65
Iron
mg
80
60
60
60
50
50
50
60
Copper
mg
8
8
6
6
6
6
6
8
%
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13. Nutrition by genotype
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Iodine
mg
0,4
0,4
0,4
0,4
0,4
0,4
0,4
0,4
Selenium
mg
0,2
0,2
0,2
0,2
0,2
0,2
0,2
0,2
A
IU
5
5
5
5
5
5
5
5
D3
ICU
1,1
1,1
1,1
1,1
1,1
1,1
1,1
1,1
E
IU
12
12
10
10
10
10
10
25
K
mg
1,75
1,5
1
0,75
0,75
0,5
0,5
1
B12
mg
0,003
0,003 0,003 0,003 0,003 0,003 0,003
0,003
Biotin
mg
0,25
0,2
0,125 0,125 0,1
0,1
0,1
0,2
Choline
mg
1,6
1,4
1,1
1,1
950
800
800
1
Folacine
mg
1
1
0,8
0,8
0,7
0,7
0,7
1
Niacin
mg
60
60
50
50
40
40
40
40
Pantothenic mg
acid
10
9
9
9
9
9
9
16
Pyridoxine mg
4,5
4,5
3,5
3,5
3
3
3
4
Riboflavin mg
4
3,6
3
3
2,5
2,5
2,5
4
Thiamine
2
2
2
2
2
2
2
2
mg
5. Feeding Geese
Several feeding programs are known in geese production.
1. After 2 weeks nursing with starter feed, goslings are put on pasture for foraging with complementary grain
feeds. This case they reach market size at about 18 weeks.
2. Just a limited amount of prepared feed is used for goslings, then considerable foraging and high-energy
finishing diet is applied. In this situation geese can be marketed around 14 weeks of age
3. Broiler or "junior" or "green geese" are fed ’ad libitum’ (as they like). They grow fast and can be marketed at
about 10 weeks age.
4. Goose livers (paté de foie gras) are the product form force-fed geese. They are pre-nursed for about 12 weeks
and then fed with a high-energy diet (maize) to produce high-fat content liver.
Commercial feeds are not used for goslings so they nursed on pelleted chick starter feed. Chick grower ration
used after and it is supplemented with a cracked grain after the first 2-3 weeks. Pre-nursed geese are foragers,
they grow on processed bulk feed (e.g. silage), or on rich pastures at 40-80 bird per hectare density. In case of
hot weather the birds should be provided with shade.
Usually geese are sold in holiday market (in November in Europe), when they are 5-6 months old, weighing 5-6
kg depending on the strain and breed. Full-fed, rapid growth young geese are marketed at 4-5 kg when they are
10-13 weeks old
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13. Nutrition by genotype
(species/variety/hybrid)
13.13. táblázat - Table 13.14. Nutrient Requirements of Geese as Percentages or Units
per Kilogram of Diet (90% dry matter)
Nutrients
Unit
0 to 4 Weeks
After 4 Weeks
Breeding
Protein
%
20
15
15
Lysine
%
1
0,85
0,6
Methionine + cystine
%
0,6
0,5
0,5
%
0,65
0,6
2,25
0,3
0,3
0,3
Protein and amino acids
Macrominerals
Calcium
Nonphytate phosphorus %
Fat soluble vitamins
A
IU
1,5
1,5
4
D3
IU
200
200
200
Choline
mg
1,5
1
?
Niacin
mg
65
35
20
Pantothenic acid
mg
15
10
10
Riboflavin
mg
3,8
2,5
4
Water soluble vitamins
13.14. táblázat - Table 13.15. Approximate Body Weights and Feed Consumption of
Commercially Reared Male and Female Geese to 10 Weeks of Age
Age (weeks)
Average Body Weight (kg)
Feed Consumption by 2- Cumulative
Week Period (kg)
Consumption (kg)
0
0,11
0
0
2
0,82
0,96
0,96
4
2,05
2,93
3,89
6
3,05
3,2
7,09
8
4,05
4,34
11,43
10
4,85
4,68
16,11
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Feed
13. Nutrition by genotype
(species/variety/hybrid)
6. Feeding Ducks
Commercially prepared duck feed, is available but on-farm mixing the feed would be less expensive. High
quality pelleted feed is important to maximize the growth rate and feed efficiency. Ducklings should be fed a
starter diet from hatch to 2 weeks of age. The starter diet should be fed as 3 mm diameter pellets or as crumbles.
After 2 weeks of age, feed a grower diet as 5 mm diameter pellets
13.15. táblázat - Table 13.16. Suggested Macronutrient Requirements of Ducks1
Nutrient
Metabolizable
(Kcal/lb.)3
Starter
Grower
Finisher
Breeder2
0-2 weeks
2-6 weeks
6-8 weeks
Developer Layer
1400
1400
1175
1300
energy 1400
% Protein
20
18
16
14,5
16
% Lysine
1,1
0,9
0,8
0,65
0,75
% Arginine
1,1
1
0,9
0,7
0,85
+ 0,9
0,8
0,7
0,6
0,65
0,9
0,8
0,8
0,7
2,9
0,4
0,4
0,35
0,35
1
1
0,8
1
%
Methionine
Cystine
% Calcium
%
Phosphorus
Available 0,45
% Linoleic Acid
1
1. Nutrients shown in this table apply only to the energy level specified.
2. Begin feeding breeder layer feed one month before the first egg is laid.
3. The energy concentration given is only an example. The energy concentration may vary from 1000 to 7500
Kcal/lb, provided the concentration of each nutrient per unit of energy remains the same.
13.16. táblázat - Table 13.16. Suggested Micronutrient Requirements of Ducks
Nutrient
1
2
3
0-2 wks
2
wks- Breeder
adult
Minerals
Nutrient
1
2
3
0-2 wks
2
wks- Breeder
adult
Vitamins
% Potassium2
0,7
0,6
0,6
Vitamin
(IU/lb.)
% Sodium
0,17
0,14
0,14
Vitamin
(ICU/lb.)
A 4000
D3 500
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2500
4000
400
400
13. Nutrition by genotype
(species/variety/hybrid)
% Chlorine
0,12
0,12
0,12
Vitamin
(IU/lb.)
E 10
5
10
Magnesium
(mg/lb.)
230
230
230
Vitamin
(mg/lb.)
K 1
0,5
1
Manganese
(mg/lb.)
25
25
25
Riboflavin
(mg/lb.)
3
1,5
3
Zinc (mg/lb.)
32
25
30
D-Pantoth. acid 6
(mg/lb.)
4
5
Iron (mg/lb.)
35
20
30
Niacin (mg/lb.)
20
25
Copper (mg/lb.) 4
3
3
Vitamin
(mcg/lb.)
2
4
Iodine (mg/lb.)
0,14
0,2
Choline (mg/lb.) 900
450
450
Cobalt (mcg/lb.) 90
90
90
Biotin (mg/lb.)
0,05
0,05
Selenium
(mcg/lb.)
70
70
Folic
(mg/lb.)
Acid 0,6
0,4
0,5
Thiamin
(mg.lb.)
1,6
1,5
1,4
Pyridoxine
(mg/lb.)
1,4
1,4
1,4
Ethoxyquin
(mg/lb.)
60
60
60
0,18
70
25
B12 4
0,05
1. Vitamin-Mineral Level(s) should provide the following levels/pound of complete feed.
2. Not needed in commercial Vitamin-Mineral premixes.
13.17. táblázat - Table 13.17. Example Rations for Ducks (% of complete ration)
Ingredient
Starter
Grower
Finisher
Developer Layer
Yellow corn, #2 dent
70
73,58
77,25
39,5
59
Barley
--
--
--
15
15,04
Oats
--
--
--
11,2
--
Soybean meal (48% protein)
18,18
19,7
16,13
12,4
13,95
Alfalfa meal (17% protein)
2
--
--
--
--
Fish meal (60% protein)
7,5
--
--
--
--
Meat & Bone meal (50% protein)
--
5
5
--
5
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13. Nutrition by genotype
(species/variety/hybrid)
Wheat Bran
--
--
--
10
--
Wheat Middlings
--
--
--
8
--
D,L-Methionine
0,17
0,22
0,16
0,15
0,14
Dicalcium Phosphate (18.5% protein)
0,55
0,28
0,15
1,3
0,18
Ground Limestone
0,75
0,77
0,86
2
6,24
Iodized salt
0,25
0,25
0,25
0,25
0,25
Vitamin-mineral package
0,202
0,203
0,203
0,203
0,204
Chlortetracycline-50
0,4
--
--
--
--
% Protein
20
18,3
17
15
16
Metabolizable energy (Kcal/lb.)
1400
1410
1426
1200
1312
% Calcium
0,9
0,85
0,8
0,75
2,9
% Available Phosphorus
0,45
0,4
0,35
0,38
0,35
% Lysine
1,12
0,9
0,8
0,7
0,75
% Methionine + Cystine
0,9
0,8
0,7
0,65
0,65
Calculated Analysis
7. Questions:
1. What are the most important features of broiler diets?
2. What are the most important features of layer hen diets?
3. Describe the characteristics of egg production and broiler growth?
4. What are the main elements of chicken & turkey feeding technology?
5. What are the main elements of geese & duck feeding technology?
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14. fejezet - 14. Poultry keeping
technologies
Poultry housing vary according to the species and the way (intensity) the poultry is raised. The basic principle is
to fulfil the essential biological needs of the animal in order to maintain good health, management, hygienic
conditions and air quality. The basic types of technologies are shown next.
1. Key elements of the keeping technology
Light
Birds in intensive systems often kept at low light intensities (e.g. less than 10 lux) to reduce negative effects
(feather pecking, cannibalism and vent-pecking) in battery cages (and other housing systems). Hens prefer to eat
in brightly lit environments and prefer these areas for active behaviour. Dimming the lights can also cause
problems when the intensity is then abruptly increased (e.g. at inspection) because the birds can become
frightened resulting in panic-type ("hysteria") reactions which can increase the risk of injury.
Artificial lighting is necessary if the available natural light is insufficient in buildings. Darkness prevent the
physiological needs of hens to see one another and be seen clearly, to investigate their surroundings visually and
to show normal levels of activity. All houses must have lighting with an intensity of at least 20 lux during the
lighting periods, measured at bird eye level and illuminating at least 80% of the usable area.
The lighting must follow a 24-hour rhythm and include periods of darkness lasting at least 6 hours in total, with
at least one uninterrupted period of darkness of at least 4 hours, excluding dimming periods.
Air conditions: ventilation, temperature, humidity, gases
Ventilation is crucial to keep optimum temperature, relative air humidity and gas concentrations, dust levels
below the limit harmful to the animals. It also helps to avoid heat and cold stress and protect confined birds from
draughts in cold conditions.
It also helps to reach and maintain the following criteria usually measured at the level of the chickens’ heads:
• NH3 concentration of not exceed 20 ppm;
• CO2 concentration does not exceed 3000 ppm
• Average relative humidity should not exceed 70%
14.1. ábra - Fig. 14.1. Elements of air exchange
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14. Poultry keeping technologies
Litter and noise
Poultry has to access to a littered area for pecking and scratching. The litter must easily be broken down, and
have an adequate depth for dust-bathing (approximately ten centimetres) over the first two months of use to
prevent health problems, in particular foot, leg and breast lesions. The level of sound is to be minimised, and the
farmer must protect the birds from constant or sudden noise caused often by ventilation fans, feeding machinery
or other equipment.
2. Management operations in poultry keeping
There are several operations commonly practiced:
Beak or bill trimming: it is practiced to avoid feather pecking, cannibalism and excessive feed intake. It may
only be carried out on conventionally reared meat chickens and laying hens which are less than 10 days old, and
at ducks or turkeys before they leave the brooder or rearing accommodation.
Dewinging: to clip the flight feathers of one wing necessary to prevent flight (pinioning, notching, tendon
severing). It may be used on ducks, because other birds used for domestic production have limited flight
capability.
Desnooding of turkeys: to be carried out as soon as possible after hatching or by a vet after the first 21 days of
its life.
Toe cutting of turkeys: In order to avoid injury to turkey hens during mating within the first 72 hours of life, or
carried out by a vet after.
3. Egg and meat production technologies
Caged layer hens
Cage production is still dominant method, providing the majority of eggs in the world: over 60% of the world’s
eggs are produced in industrial systems, mostly using battery cages, including over two thirds in the EU. From
January 2012 EU banned conventional battery cages so eggs produced from these systems are rapidly
decreasing. In some countries Battery cages are banned, e.g. in Switzerland which was the first country to do so.
14.2. ábra - Fig. 14.2. Cage laying technology
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14. Poultry keeping technologies
Batteries are lines of cages connected together by common divider walls and/or ceilings. The sloped floor allow
eggs to roll out of the cage, where they were easily collected, and the absence of the egg urges the hen to lay
another one. Conveyor belts under the cages installed to remove manure, which also helps providing better air
control quality.
Due to strengthening animal welfare concerns significant developments were taking place in cage production.
These called “furnished”, "enriched" or "modified" cages, which have been designed to overcome these
concerns whilst ensuring economic and husbandry advantages. Furnished cages retain several advantages of
battery cages:
• Separate the eggs from the faeces to keep the eggs clean,
• Protect the hens from predation
• Prevent egg-eating and floor-laying by automatic collection of the eggs
• Retain a small group size which reduces injurious pecking behaviour
Furnished cages have welfare benefits additional to battery cages by providing additional space and nesting,
claw shortening device, dust bath/litter substrate, perch and easier access for depopulation.
Council Directive 99/74/EC set out minimum standards for ‘enriched’ cages which include increased space,
claw shortening device, perch, nest boxes and litter for scratching and pecking. Conventional ‘battery’ cages are
not to be used from 1 January 2012 for producers with more than 350 laying hens.
Enriched systems require:
• 750 cm2 per bird minimum
• a nest and perching space of 15 cm per bird
• litter such that pecking and scratching are possible
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14. Poultry keeping technologies
• 12 cm of feeding trough per bird
• at least two nipple drinkers or two cups within easy reach of each hen
• incorporated damp-proof membranes to prevent insulation breakdown, and measures to stop easy access by
vermin to the insulation material
Council Directive 99/74/EC
14.3. ábra - Fig. 14.3. EU conform cages (interior & with hens)
Barn hens
Barn keeping is more accepted by consumers due to its more animal friendly feature. Barn and other non-cage
systems for keeping laying hens has to meet the following criteria:
• a maximum stocking density of nine birds/m2
• at least 250 cm2 of litter area per bird
• 15 cm of perch per hen
• 10 cm of feeder per bird and at least one drinker for every ten birds
• 1 nest for 7 birds or 1 m2 nest space for 120 birds
• water and feeding troughs should be raised so the food is not scattered
14.4. ábra - Fig. 14.4. Barn laying technology
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14. Poultry keeping technologies
Free range technology
Free-range eggs are produced using birds that are permitted to move freely within a designated area (farmyard,
shed or chicken coop). The term "free-range" may be used differently depending on the country and its laws.
There specific rules for free-range hens, in addition to the rules for keeping barn hens. These are:
• Protection from adverse weather conditions, predators (overhead cover) and health risks
• Access to a well-drained lying area
• Continuous daytime access to vegetation-covered open runs at maximum stocking density of 2,500 birds/ha.
• Outdoor scratch
• Whole grain feeding,
• Fresh water supply
• Sufficiently far from the house to encourage birds to range.
Pasture management is to be practiced well in free-range keeping. The most important issues are to avoid land
becoming churned up, prevent birds form ‘fowl sickness’ and to be infested with disease carrying organisms.
14.5. ábra - Fig. 14.5. Free range technology
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14. Poultry keeping technologies
4. Turkey farming technologies
An industrial turkey farm is very similar to an industrial chicken farm. Day-old poults are delivered from a
dedicated hatchery and placed in a shed, where they will spend their entire lives. The floor is a litter of sawdust
and straw for soaking up bird waste, and the lighting is kept low to reduce aggressive behaviour among the
birds. The beaks are cut for the same reason. They are fed cereals with added vitamin and artificial proteins.
Antibiotics are used to control health problems stemming from farm conditions. Turkeys are raised for
maximum weight gain, and then slaughtered in an abattoir on the farm at between 3 and 7 months of age.
The following features are common in intensive production:
• Stocking densities at rearing 3.0 – 3.5 females/m2 and 1-2 males/m2
• Laying females: nest box ratio, 5 – 6 birds/nest or for heavy strains 1.8 – 2.0 birds/m2 Males: 1 /m2
• Rearing in one house: 28 – 30 weeks of age (most common)
In the conventional technology 1-7 days old poults are placed into small (2.5m) circular brooding pens to ensure
they encounter food and water. Constant light for the first 48 hours applied to encourage feeding. Air
temperature is maintained at 35°C for the first three days with infra-red heaters, then lowered by approximately
3°C every two days to 18°C at 37 days of age. Then, the pens are removed, allowing the birds access to the
entire rearing shed, which may contain tens of thousands of birds. The birds remain there for several weeks,
after which they are transported to another unit.
Space allowance for commercially reared turkeys is often severely limited to enhance growth, and lighting
manipulations used to optimise production. They both can compromise welfare.
Feather pecking occurs frequently amongst commercially reared turkeys and can begin at 1 day of age, so they
are often beak-trimmed to reduce it.
Feather and head pecking has its own ethical concerns, which become more frequent as they sexually mature.
This can be avoided by frequent monitoring
14.6. ábra - Fig. 14.6. Barn technology for turkey
5. Goose farming technologies
Goose are farming practiced in significant level at only a few countries (China, Ukraine, Egypt and Hungary.
They are reared for meat, feathers and down and to produce fatty livers. The goslings grow very rapidly so that
they may reach 2 kg at 4 to 5 weeks of age but are not fully mature until two years old.
Geese is reared in free-range technology, because they need very little supervision and monitoring. They are
hardy, rarely affected by any disease or insect pests. After they are two weeks old all they need is plenty of
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14. Poultry keeping technologies
water and grass and a simple three-sided shed where they can keep dry in bad weather. At breeding time, geese
make their own nests and hatch their own eggs.
The growing facility need not be sophisticated since these birds are not demanding - a simple shelter should be
adequate. The most important factor is to ensure that the goslings are warm during the brooding period and
protected from sun, heavy rain and predators, especially during the night.
The growing of geese indoors (confinement) allow the control of the environment. Broiler type geese can go to
market at 8-9 weeks of age at a body weight of 4.0 kg and heavy type geese can go to market at 12-14 weeks of
age at a body weight of 6.0 kg. This means that geese produced under these systems are generally not plucked
during the growing period. Geese grown in confinement are generally raised on deep litter which is considered
the classical system of poultry production.
In feather and down production the most valuable product is the down, which is obtained from the breast area of
the goose, followed by the fine feathers. The harvesting is not harmful for the animals, because the mature down
feathers, together with the other soft feathers, moult naturally between 9-10 weeks of age. The yield at the first
plucking is app. 80 g and 100-120 g/plucking in the subsequent 2-3 times, with 15-20% down from the total
weight.
Fatty liver production is the process of force-feeding (cramming) geese, which are normally done between 9-25
weeks of age, for a period of 14-21 days. The weight of the liver will increase from 80g to a final weight of
between 600-1.000g. In this technology the birds are fed with high amount of grain (corn), up to 5-6 times per
day. Force-feeding is banned on welfare grounds in many countries particularly in the European Community.
14.7. ábra - Fig. 14.7. Geese farming technology
6. Duck farming technologies
Similarly to geese, ducks are usually kept free range combined with barns. They should have access to water,
and fed a grain diet. Ducklings are kept indoors for the first 3 weeks (pre-nursing) and then let out in open range
for 4 weeks outgrowing.
Raising ducks on fish ponds on a small scale is an old practice in Europe and Asia, especially in China, because
ducks may obtain part of their food from plant and animal life in and around the pond, but supplemental feeding
is necessary. Ponds are stocked with fish such as Tilapia, Carp, etc. which are raised for human food. Manure
from the ducks provide nutrients for growth of animal and plant life which the fish consume.
Semi-confinement duck housing is similar except that ducks are allowed outdoors during the day over 2-3
weeks of age. Ducklings require a higher temperatures (about 30°C) at the time of hatching, but as they grow
older they become better able to regulate their body temperature. Then, the optimum is around 13 °C.
Ducks more water than chickens and turkeys, and they excrete more, too. Their droppings contain over 90%
moisture, so it require more effort to keep litter floors inside in a dry condition.
14.8. ábra - Fig. 14.8. Duck farming technology
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7. Questions:
1. What are the main elements of chicken keeping technology?
2. What are the main elements of turkey keeping technology?
3. What are the main elements of geese keeping technology?
4. What are the main elements of duck keeping technology?
5. Describe the concept of free-range technology?
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15. fejezet - 15. Processing
technologies
Poultry is a major source of consumable animal protein nowadays, since the industry has developed a highly
efficient production system. turkeys are the most common species produced, while others (ducks, geese etc.)
have regional significance. Due to the fact that poultry meat can fit into changing lifestyles and preference for
convenience food the consumption is increasing steadily.
In order to meet the ever increasing consumer demand the producers must keep quality as key issue. The main
structure of a carcass are: muscle, fat, bone and connective tissue, as well as cartilage and ligaments. Nutritive
value of poultry meat is characterised by protein content and its correlation with fat. chickens broiler and
turkeys have less fat (6-8%) compared with meat geese (30-39%) and ducks (26-36%), but significantly more
protein (21,5-22,5% vs. 12 -17%).
1. Main steps in the processing plants
The processing starts with slaughtering, then subsequently their feathers, intestine (lungs, kidneys, etc.), head
and other unwanted parts are removed and thoroughly washed in water. Then this cleaned portion is cut into
required sizes and packed. The man phases of processing are:
Pre-slaughter handling
Before transporting the poultry to the processing plant it is essential to have the digestive tracts to empty. This
also reduces the potential for contamination during processing. Poultry is transported at night to reduce stress.
The birds form transport boxes are transferred to continuously moving shackles where they are suspended by
both legs. If handling and transfer of birds is stressful it has serious animal welfare consequences moreover, it
has negative effects on the quality, so stress of any kind must be avoided.
15.1. ábra - Fig. 15.1. A typical processing plant
Slaughtering
Stunning and killing is done on the conveyor belt with moving shackles. The birds are stunned by an electric
current on their heads running through a water bath. It only causes unconsciousness, and the birds are killed by
hand or by a mechanical rotary knife cutting through their neck (carotis). This way the birds are bleed to remove
blood from their body.
Scalding and feathering: Following bleeding, the birds go through scalding tanks containing hot water with
which the feathers can be removed. The temperature of the water varies from 50°C (to preserve yellow skin
colour) to 60°C (turkeys and spent hens). After the bath specifically designed rubber “fingers” beat off the
feathers, then the carcasses pass through a flame that burns off any remaining feathers.
Removal of heads and legs, evisceration and inspection: The heads and legs of the birds are removed with a
rotary knife, then carcasses are rehung to the eviscerating shackle line where the preen, or oil gland the viscera
(internal organs) are removed either by hand (with knives) or by using automated mechanical devices. The
carcasses are generally inspected for quality compliance. The rejected parts are coolected separately as
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15. Processing technologies
“inedibles,” and the carcasses are further cleaned. The heart, stomach, and liver are all considered edible offal
and are independently processed, finally the carcasses are then washed thoroughly.
Chilling: After the carcasses have been washed, they are chilled to a temperature below 4 °C to prevent
spoilage.
15.2. ábra - Fig. 15.2. Poultry slaughtering
2. Raw & processed poultry products
Whole or individual parts of birds may be packaged raw for direct sale. to be sols frozen or fresh. The birds are
cut into a number of pieces, and they should be used within 14 to 21 days after slaughter. smoking (prior to it
the flesh must be brined)
mechanical deboning (meat-bone separation) resulting in minced product that has been used for sausages or
various toppings.
15.1. táblázat - Table 15.1. Nutrient composition of roasted or broiled poultry cuts(per
100 grams)
Poultry type and cut
energy (kcal) fat (g)
protein (g)
cholesterol
(mg)
light meat with skin
222
10,85
29,02
84
dark meat with skin
253
15,78
25,97
91
light meat without skin
173
4.51
30,91
85
dark meat without skin
205
9.73
27,37
93
Chicken
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Duck
flesh and skin
337
28,35
18,99
84
flesh
201
11,2
23,48
89
flesh and skin
305
21,92
25,16
91
flesh
238
12,67
28,97
96
light meat with skin
197
8.33
28,57
76
dark meat with skin
221
11,54
27,49
89
light meat without skin
157
3.22
29,9
69
dark meat without skin
187
7.22
28,57
85
Poultry type and cut
iron (mg)
zinc (mg)
vitamin
B12 (μg)
thiamine (mg)
light meat with skin
1,14
1,23
0,32
0,06
dark meat with skin
1,36
2,49
0,29
0,066
light meat without skin
1,06
1,23
0,34
0,065
dark meat without skin
1,33
2,8
0,32
0,073
flesh and skin
2,7
1,86
0,3
0,174
flesh
2,7
2,6
0,4
0,26
Goose
Turkey
Chicken
Duck
Goose
flesh and skin
2,83
0,077
flesh
2,87
0,092
Turkey
light meat with skin
1,41
2,04
0,35
0,056
dark meat with skin
2,27
4,16
0,36
0,058
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15. Processing technologies
light meat without skin
1,35
2,04
0,37
0,061
dark meat without skin
2,33
4,46
0,37
0,063
Source: Composition of Foods,Agriculture Handbook no. 8-5, U.S. Department of Agriculture.
3. Environmental issues connected to processing
Slaughtering and rendering activities may generate significant quantities of organic waste and By-products
accounting for 25% of the initial live bird bodyweight (carcass on average is 75%). Moreover, it require large
amounts of high
quality water for cleaning and cooling. Wastewater then has high biochemical and chemical oxygen demand
(BOD and COD) due to the presence of organic material such as blood, fat, flesh, and excreta, as well as high
levels of nitrogen, phosphorus, residues of chemicals such as chlorine and various pathogens including
salmonella and campylobacter. Poultry processing facilities also use qiute high amount of energy to heat water,
produce steam and for the operation of mechanical and electrical equipment, refrigeration, and air compressors.
4. Product quality
„Qualitas” is a Latin origin word, meaning the totality of features that make it suitable for the supplies to meet
the needs of the consumer. It objectively and neutrally describes material properties, which are not connected to
either positive or negative value judgments. The term is often used to distinguish between comparable products,
and the quality of the goods of the interior and exterior of all properties, which makes it suitable for certain
goods expectations and standards compliance.
Quality assurance
The quality, however, should not be mixed with quality assurance! The quality assurance is a system that
includes all the activities of all of which can guarantee the product is constant, the standards and expectations of
conformity, and also that no defective products leave the production place
The food quality properties
Food-hygienic safety consists of microbiological contamination (pathogenic, or its toxins), antinutritive
materials (biogenic amines, antinutritive materials), chemical contamination (e.g. drug residues, heavy metals),
radiological contamination. It also means immunity from preserving agents (overdose which may endanger the
food-hygienic safety). Nutrition-biological factors mean protein, fat and carbohydrate (as main component),
vitamins, essential fatty acids - amino acids content, flavourings, micronutrients and other beneficial
microorganisms. Hedonic values include visual features, such as looks, colour and shape, stock, texture,
consistency, taste, flavour and freshness, as condition.
Hygienic and toxicological factors are germ species, germ number and durability. Processing-technology factors
such as amount of connective tissue, tendons, fat content and fat type, condition, construction, water-binding
and extraneous water absorption capacity.
15.3. ábra - Fig. 15.3. Possible ways of salmonella infection in poultry
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5. Egg Quality
Eggs are recognised by consumers as versatile and wholesome and they have a natural balance of essential
nutrients. According to the consumer expectancies, a fresh egg has clean, smooth, brown or white shell, a pure,
deep-yellow yolk and a translucent, firm white.
The nutritive value of the egg
The egg is one of the most complete foods available. It consists of 10% shell, 58% white and 32% yolk. The
nutritive content of an average large egg (containing 50 g of edible egg) includes 6.3 g protein, 0.6 g
carbohydrates 5.0 g fat, The average egg provides app. 313 kilojoules of energy, of which 80% comes from the
yolk.
Egg protein is of high quality and is easily digestible. Almost all of the fat in the egg is found in the yolk and is
easily digested.
Eggs contain every vitamin except vitamin C. They are particularly high in vitamins A, D, and B12, and also
contain B1 and riboflavin. Eggs are a good source of iron and phosphorus and also supply calcium, copper,
iodine, magnesium, manganese, potassium, sodium, zinc, chloride and sulphur. All these minerals are present as
organic chelates, highly bioavailable, in the edible part of the egg.
Internal egg quality
As soon as the egg is laid, its internal quality starts to decrease due to the loss of water and CO2, however, the
chemical composition of the egg (yolk and white) does not change much. To maintain egg quality frequent egg
collection and rapid storage in the cool room at 10 °C are the best. The main factors affecting internal egg
quality: disease, egg age, temperature, humidity, handling, and storage.
External egg quality
There are five major types of shell problems in the egg industry: cracks due to excess pressure; cracks due to
thin shells, body-checks, pimpled or toe holes, and shell-less eggs.
Eggs can also be damaged after they are laid, either by cracking or by contamination. Some typical internal and
external faults and abnormalities are listed below together with their likely causes.
6. Questions:
1. What are the main steps of poultry processing?
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2. Please describe raw & processed poultry products!
3. What are the elements of Product quality?
4. What Environmental concerns are connected to processing?
5. What are the key poultry product quality traits (egg and meat)?
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