Automated oestrus detection and
North American Holstein genetics
in pasture based dairying in
New Zealand
Report on a research project carried out at Massey
University, Palmerston North, New Zealand, as part of
veterinary studies at Utrecht University, Utrecht,
The Netherlands
Supervision by:
Prof. N.B. Williamson, Massey University
Dr. P.L.A.M Vos, Utrecht University
October 2006- January 2007
Drs. Pieter Adriaan van Iren
0248258
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P.A. van Iren
October 2006 – January 2007
1
Automated oestrus detection and
North American Holstein genetics
in pasture based dairying in
New Zealand
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P.A. van Iren
October 2006 – January 2007
2
Contents
Contents
3.
General introduction
4.
Chapter 1 Dairy farming in New Zealand
Introduction
Seasonal dairying
Breeds and genetics
5.
5.
6.
7.
Chapter 2 Stages in the life of a dairy cow
Introduction
Puberty
Insemination and mating
Gestation and parturition
Puerperium
9.
9.
9.
13.
14.
16.
Chapter 3 Automated heat detection using a camera-software
device and oestrus detection strips
Introduction
The oestrus detection strip
The camera-software device
Trials with CSD
18.
18.
18.
19.
20.
Chapter 4 Automated heat detection by a camera-software
device and North American Holstein genetics
Abstract
Introduction
Materials and methods
Results
Discussion
22.
22.
22.
24.
27.
30.
Chapter 5 Integration of a camera-software device with electronic
identification for detection of oestrus in dairy cattle
Abstract
Introduction
Materials and methods
Results
Discussion
31.
31.
31.
32.
34.
35.
Acknowledgements
37.
References
38.
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October 2006 – January 2007
3
General introduction
This report is the result of a three months research internship conducted at Massey
University, Institute of Veterinary, Animal and Biomedical Science (IVABS),
Palmerston North, New Zealand.
This internship is a compulsory part of the last 2 years of Veterinary Education at
Utrecht University, Faculty of Veterinary Medicine, The Netherlands, together with 72
weeks of practical internships, to achieve the Diploma in Veterinary Medicine.
The trial that forms the fundamental basis of this project is conducted at Massey
University, Palmerston North during the breeding seasons of 2003/2004. This
research was carried out by Johne Alawneh, with help of Olivier van Doorne and Elly
Ebbens (Both Dutch veterinary students, also under supervision of Prof. N.B.
Williamson) and many others. Data collected in this trial are reviewed with a focus on
genetics.
Direct supervision and guidance during this internship was in hands of Prof. N.B.
Williamson at IVABS, Palmerston, North New Zealand. Dr. P.L.A.M Vos was
responsible for supervision on behalf of the Faculty of Veterinary Medicine, Utrecht
University, The Netherlands.
Professor Norman Williamson is an expert on dairy cattle reproduction and involved
in automatic oestrus detection with a camera-software device since its early
beginning. Responsible for introducing tail paint in New Zealand, involvement of Prof.
Williamson in automation of the most frequently used method of oestrus detection in
New Zealand dairy herds seems no more than self-evident!
Designing an automated version of tail paint has started in 2000 and ever since trials
and research has been done to further develop an automated oestrus detection
system. Involvement of Dutch students is significant since students participated in
projects in 2003, 2005 and 2006.
The focus of this report will be different from the earlier reports. The aim of this
project is to investigate the possible difference of functioning of the CSD, comparing
cows with a major North American Holstein influence with more typical New Zealand
Friesian-Holstein and Jersey animals. Therefore data from the 2003 trials are
reanalyzed after allocating the animals into groups based on their genetic merit.
The central query in this research will consequently be:
“Does the use of the CSD cause a greater or lesser improvement in oestrus detection
in a high North American Holstein strain of cows compared with strain with lower
Holstein influences?”
The differences may be interesting, especially now poorer fertility in animals with high
North American Holstein (NAH) genetics becomes more evident all over the world
and suboptimal expression of oestrus if hypothesised to be one of its causes.
Besides the data analysis of the previous trials the author was also involved in a new
trial, started in the 2006 mating season. Aim of this trial was to integrate the CSD
with an automatic identification system, the next step in developing a fully integrated
system of detecting heat and drafting oestrous animals for insemination.
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October 2006 – January 2007
4
Chapter 1 Dairy farming in New Zealand
Introduction
The past
Early reports on dairy farming in New Zealand show that major growth occurred after
the possibility of transporting frozen or cooled products to Britain as a major market.
Records show a rapid increase of dairy farms after 1882, the first year refrigerated
transport was made possible. Export value of butter and cheese rose from £15,000 in
1881 to £62,000 in 1882. In previous years export to Britain did take place but
products were often of poor quality or even deteriorated on arrival, thereby not
creating a strong market. Growing markets in Europe after refrigerated transportation
was made possible, led to a rapid increase of dairy cow numbers, exceeding one
million in 1924 (Belshaw, 1927).
Dairying in New Zealand initially focussed on producing butter and cheese, since
those products were easily preserved when refrigeration was not accessible to most
people and the same was the case in the European dairy industries.
The abundance of land suitable for pasture, combined with a moist, mild climate and
adequate rainfall made New Zealand exceptionally suitable for dairying. Mild winters
in most of the country made housing during winter needless, saving the costs
involved in building sheds and stall feeding during winter (Belshaw, 1927). Those
characteristics have never changed, Dairy farming in New Zealand is still mainly
pasture based and seasonally bound.
In 1921 the average dairy farm consisted of 70-80 acres, of which over 85% was
used for pasture or silage and hay production. Over 93% of the labour involved in
dairying was supplied by the farmer and his family and hired labour was a rare
exception.
Most of the milk was used to produce butter and cheese on the farm. Factory
production of dairy products in cooperative enterprises rapidly started to grow after
1911, in line with growing demands for export (Belshaw, 1927).
Until 1954, export was still mainly towards the British market with 90% of butter and
92.5% of cheese being exported to Britain. Between 1954 and 1972 markets
changed rapidly, finding new markets in Asia and Latin America. At the end of 1972
only 40% in volume of export was towards Britain, making up 46% of total export
value, a nearly 50% decrease from 1954 (Lewthwaite, 1980).
The present
The New Zealand dairy industry has grown rapidly in the last century, reaching a
production of 14,103 million litres of milk in 2004/2005. This production was attained
by 3,868 million cows in 12,271 herds with an average size of 317 cows per herd
throughout New Zealand. Since 1974 the average number of cows per herd has
doubled.
Most of the dairy farms are situated on the North Island. Breeds most frequently used
are Holstein-Friesian, Jersey and Ayrshire, although most cows are crossbreds of the
mentioned breeds. In 2001-02 the average New Zealand cow produced 308 kg of
milk solids per year, containing 176 kg of fat and 132 kg of protein (National Dairy
Statistics, 2004-2005).
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Subsidies on agriculture has been removed in New Zealand since 1984. At the start
of 1984 33% of farm income was directly derived from government subsidies. In 2003
subsidies only made up 2% of farm income. At present, most of the subsidies
towards agriculture are spent on agricultural research (Smith and Montgomery,
2004). A consequence of this absence of subsidies is that the costs of production of
dairy products must be below world market prices to gain profit from dairy farming.
Seasonal dairying
Having to produce at world market prices, New Zealand dairy farming is still mainly
based on pasture availability. The mild climate, adequate rainfall and mild winters
guarantee an all-year round availability of pasture with peaks in late spring-early
summer and a smaller one in autumn. Year round grazing saves the high costs of
building stables, expenses for the purchase of feed and of labour for stall feeding.
This makes land possession the greatest expense (Verkerk, 2003).
Depending on pasture availability requires careful adjustment of the nutritional
demand of the herd to pasture on offer. This consequently means that high pasture
growth should coincide with the period of peak milk production and makes mating
and calving strongly seasonally bound (Verkerk, 2003; Lucy, 2005; Alawneh, Thesis).
Reaching the peak of production in 4 to 6 weeks, this means that cows must all calve
within a short period. (Ball and Peters, 3rd edition). To match maximal production and
pasture growth, calving must occur preceding the expected maximal pasture growth
by that number of weeks.
Breeding in New Zealand usually takes place in a period of 2-3 months. On most
farms a 4-8 week artificial insemination (AI) period after Planned Start of Mating
(PSM) is followed by a period of natural mating by herd bulls (Alawneh, Thesis).
Mating of heifers is usually started 7 days before mating the cows to allow the heifers
a longer postpartum period to re-establish ovarian cyclicity before the breeding
season after having her their first calf. (Grosshans, 1997).
The narrow timeframe of mating puts high pressure on oestrus detection since
missing an oestrous of a cow greatly decreases the chance of getting her with calf in
this limited time. Since cows appearing non-gravid after pregnancy testing are
usually culled, missing oestrus leads to high costs for the farm. Artificial insemination
is usually carried out by professional AI-technicians, though do-it-yourself AI (DIY AI)
is used increasingly as in the rest of the world. Australian research indicates a
significant lower conception rate in DIY AI compared to AI carried out by a
professional technician (Mee, 2004).
Its low cost and reasonably high accuracy, mean that tail painting is the most
frequently used method of oestrus detection in New Zealand. Alawneh et al. (2006)
found an overall accuracy for tail painting combined with visual observation of 98%.
Besides tail painting, simple mount detectors are used for detecting cows on heat.
Most other systems, particularly the ones based on measuring activity, appear to be
of less value under New Zealand circumstances, due to the considerable distance
between pasture and milking parlour (Verkerk, 2003).
To maintain the compact calving period, corticosteroids to induce parturition were
frequently used in the past. Nowadays shortening the mating period is more
accepted. Intravaginal hormone releasing devices (e.g. CIDR TM, InterAg, Hamilton,
New Zealand) are frequently used to treat anoestrous cows postpartum, thereby
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6
shortening the calving to conception interval. Synchronizing oestrus is not frequently
done in New Zealand herds (Verkerk, 2003).
Slight differences in climate and therefore pasture growth rate, mean that calving and
consequently mating generally starts earlier in the warmer northern areas than in the
more moderate southern areas (Curry, 1963).
Breeds and genetics
In 1884 the first Friesians were introduced from the Netherlands (Jasiorowski et al.,
1988). Friesians, now usually referred to as Holstein-Friesians due to the major
influence of Holsteins, form a considerable part of New Zealand dairy herds. Beside
Holstein-Friesians, Jerseys and in lesser extent, Ayrshire cows have a dominating
influence on New Zealand dairying. Each of the dairy breeds is used for particular
qualities. Jersey cows appear to be efficient in the conversion of pasture to
particularly milksolids, producing a lower milk volume. Butterfat and non-fat milk
solids are both high. In the pay-out system of the New Zealand dairy industry a high
portion of milksolids in a lower volume is favourable. Also, Jerseys seem to have
strong legs, appreciated in the New Zealand system where pasture is often at a
longer distance from the milking shed. Jerseys are also heat tolerant, making them
suitable for New Zealand summers. Holstein-Friesians are able to produce a large
volume of milk per lactation, though milk solids are lower compared to Jersey cattle
and production is usually better using a total mixed ration system. Holstein-Friesians
are less heat tolerant. Ayrshires are hardy animals, good foragers and have a fine
milk producing ability (French et al. 1966).
Although purebred herds still occur, the use of cross breeding between Friesians,
Jerseys and Ayrshire is widespread and still increasing. In the seasons of 2001-2002
and 2004-2005 breed percentages in New Zealand were calculated as shown in
Table 1. The table shows an increase in the use of crossbreeds and a decrease in
purebreds. Beside cross breeding dairy breeds, also semen from beef bulls is used
to obtain calves of greater value for finishing. (National Dairy Statistics, 2001-2002
and 2004-2005)
Breed or crossbreed
% of Cows
‘01-‘02 ‘04-‘05
Holstein-Friesian
54%
48.6%
Jersey
15%
14.8%
Ayrshire
1%
1%
Holstein-Friesian x Jersey
23%
28.3%
Other
7%
7.3%
Table 1 Breed percentages of cows in New Zealand
(National Dairy Statistics 2001-2002 and 2004-2005)
The influence of North American Holsteins (NAH) on the New Zealand HolsteinFriesian population is substantial. Currently, the percentage of NAH genes in the
New Zealand dairy cow population is estimated to be around 40%, meaning that the
average New Zealand dairy cow has approximately 40% NAH genes (Williamson,
2006). This influence however is still low compared to for instance the British Isles
and the Netherlands with 80% and nearly 100% of NAH genetics respectively (Mee,
2004).
This low influence of NAH on New Zealand herds, compared to most herds all over
the world, is probably the result of poorer performance of NAH animals in the New
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October 2006 – January 2007
7
Zealand seasonal pasture based system. Though NAH animals are capable of
producing large volumes of milk, their optimal production is reached in a total mixed
ration system (Horan et al, 2005). Solely on pasture the NAH tend to produce less
optimally, thereby they are not able to compete with New Zealand Holstein-Friesians.
Milk volume production of NAH animals may exceed the New Zealand HolsteinFriesians but the amount of milk solids produced can not compete in a pasture based
system.
Besides these differences in production NAH animals have a higher mature weight
and have a lower Body Condition Score (BCS) throughout lactation compared to New
Zealand Holstein-Friesian animals. (Lucy, 2005)
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8
Chapter 2 Stages in the reproductive life of a dairy cow
Introduction
This chapter discusses the relevant stages in the life of a dairy cow with a focus on
fertility. Major events influencing fertility are puberty and the puerperium. In both
periods the animals have to acquire a physiological oestrous cycle after being
acyclic, in order to get ready for breeding. These stages are important for the cow’s
life expectancy since in New Zealand seasonal dairying culling is a usual
consequence of not being pregnant after a mating period. Cow fertility in New
Zealand is assumed to be high compared to countries with non-seasonal dairying
(Mee, 2004). This is likely to be the consequence of this strict policy.
Puberty
Puberty is the age at which the reproductive organs of an animal become active and
cyclicity therefore starts. The reproductive organs become responsive to
gonadotrophins and become able to generate steroidal sex hormones and release
gametes (Hafez, 6th edition). The pineal gland appears to have a major role in the
onset of puberty by influencing the release of gonadotrophins by the anterior pituitary
(Noakes, 8th edition). An average age of 12 months is recorded for onset of puberty
in heifers (Hafez, 6th edition). However, the age at which puberty occurs depends on
several factors. Diet and weight gain greatly influence the onset of puberty (Chelikani
et al. 2003). Also breed and season appear to be involved (Ball and Peters, 3rd
edition). Izard and VandenBergh (1982) found a higher percentage of heifers
reached puberty during a trial period when oro-nasally treated with bull urine,
compared to a control group treated with water (67% vs. 32% respectively). Rekwot
et al. (2001) report a decrease of onset of puberty from 26.4 months to 23.1 months
in Bunaji and Friesian x Bunaji heifers when exposed to vasectomised bulls.
Noakes (8th edition) states that body size appears to be the major stimulus for the
onset of puberty, rather than age. This explains the 5-20 months age spread at which
oestrus can first occur. For Friesians an average weight of 240-270 kg is accepted as
the weight when first ovulation usually occurs.
In seasonally calving herds, where most heifers need to calve at 22-24 months of
age, early onset of cyclic activity is especially important since mating needs to be
carried out from the age of 13 months (Noakes, 8th edition). As soon as puberty has
occurred the heifer gets a repetitive oestrus cycle. However, in first ovulations silent
heat can occur, masking developing cyclic activity.
The different stages and the hormonal regulation of the bovine oestrous cycle are
described below.
Stages of the bovine oestrous cycle
The bovine oestrous cycle lasts approximately 21 days, with a range of 18 to 24
days. Unless domestic Bovines are pregnant or acyclic due to another cause the
cycle continues throughout the year, making domestic cattle polyoestrous (Noakes,
8th edition). The cycle consists of several stages with different hormonally influenced
processes. Each stage has its own leading hormone, responsible for the major
events taking place in that period (Noakes, 2nd edition).
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Pro-oestrus
Pro-oestrus can be seen as the first stage of the cycle. Pro-oestrus is the period
preceding oestrus and is characterised by an increase of follicular activity, leading up
to generally one ovum becoming ready for ovulation. Follicular growth is possible due
to regression of the Corpus Luteum (CL) of the previous ovulatory cycle, thereby
ending the progesterone dominance present during dioestrus. Pro-oestrus is mostly
dominated by oestrogen (oestradiol 17β) produced by the dominant follicle (Noakes,
8th edition).
Oestrus
Oestrus is the stage wherein the animal is receptive to mating. A further rise of
oestrogen preceeding ovulation causes the animal to show typical oestrus behaviour.
The animal shows more interest in other animals especially to those also in oestrus
and becomes restless. (Noakes, 8th edition) Mounting other animals, chin-resting,
licking the ano-genital region of other cows and standing to be mounted are other
behavioural signs of oestrus (van Vliet and van Eerdenburg, 1996; Noakes, 2001;
Kerbrat, 2004). Standing to be mounted is seen as the primary and most distinctive
sign of oestrus, showing that the animal is in a pre-ovulatory state (Orihuela, 2000).
The fact that the oestrous cow is mounted by other cows is the sign most used for
detection. Behavioural signs of oestrus are best expressed in a herd large enough to
have multiple animals on heat at the same time (Van Vliet and van Eerdenburg,
1996).
A number of physiological alterations of the reproductive organs are visible, besides
the behavioural signs, including a clear mucous vaginal discharge (Noakes, 8th
edition; Alawneh et al., 2006) and hyperaemia of the vaginal mucosa (Noakes, 8th
edition).
Estimations of the duration of oestrus vary between researchers, definitions of
oestrus and methods of detection, varying from 14.4 h detected by visual observation
to 10.9 h detected by radiotelemetry in a study carried out by Cavalieri et al (2003).
Van Vliet and van Eerdenburg (1996) found a duration of oestrus of 13.7 ± 6.7h.
Using a radiotelemetric system, Nebel et al. (2000) found a length of 7.1± 5.4h
between the first and last standing event.
Metoestrus
Metoestrus follows oestrus and at this stage final maturation of the Graaffian follicle
and ovulation take place. After ovulation the Corpus Luteum (CL) develops from the
granulosa and theca cells of the follicle at the site of ovulation (Noakes, 2nd edition).
During metoestrus both oestrogen and progesterone concentrations are low but then
progesterone rises to achieve from the estrogen dominance that has controlled
oestrus (Senger, 1st revised edition).
Dioestrus
During dioestrus progesterone formed by the functional CL is the predominant
hormone. Progesterone inhibits final maturation of follicles, although follicle growth
waves continue (Noakes, 2nd edition).
Hormonal influences of the oestrous cycle
The oestrous cycle exists due to hormonal interactions in the hypothalamic-pituitaryovarian axis (HPO-axis). All structures interact by modulating each others action,
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promoting or inhibiting processes of the other structures involved. These interactions
create a complicated feedback system that maintains a physiological oestrous cycle.
The hypothalamus and anterior pituitary are both situated in the central nervous
system. The hypothalamus releases Gonadotrophin Releasing Hormone (GnRH)
which promotes the secretion of gonadotrophins by the anterior pituitary (Noakes, 8th
edition). Release of GnRH is modulated by extra-hypothalamic stimulation or
inhibition such as day length in seasonal breeders (Noakes, 8th edition). In cattle, the
suckling by a calf can inhibit GnRH release by the cow’s hypothalamus (Montiel et
al., 2005).
Hypothalamic release of GnRH occurs from two centres. The surge centre releases a
well-timed higher amount of GnRH that in the end will cause ovulation, while the tonic
centre is responsible for a more continuous GnRH secretion (Noakes, 8th edition).
The surge release of GnRH is evoked by a rise in the concentration of oestradiol
produced by the maturating dominant follicle on the ovary.
The major effect of GnRH is promoting the release of Follicle Stimulating Hormone
(FSH) and Luteinising Hormone (LH) by the anterior pituitary. Release of these
gonadotrophins stimulates folliculogenesis, follicle maturation and ovulation followed
by luteinisation after ovulation.
On the other hand the ovarian structures each provide feedback to the upper parts of
the axis. The maturing dominant (Graaffian) follicle produces oestrogen, which has a
negative effect on the tonic release of GnRH but as soon as follicular oestrogen
production reaches its maximum, it evokes the preovulatory LH-surge (Noakes, 8th
edition). Inhibin, produced by the granulosa cells of the antral follicles is an important
factor in the negative regulation of FSH secretion. In this way, inhibin and oestrogen
have a synergistic effect on FSH secretion during the early luteal phase (Kaneko et
al., 1997).
Progesterone, produced by the Corpus Luteum (CL) formed by the theca and
granulosa cells of the Graaffian follicle after ovulation, inhibits hypothalamic release
of GnRH and LH/FSH secretion by the pituitary, thereby inhibiting another
preovulatory LH-surge. Although LH/FSH secretion is diminished by progesterone,
their concentration is still high enough for follicle growth waves to occur. Ovulation
however will not occur until progesterone concentrations decline again as soon as
the luteolysis occurs (Noakes, 8th edition). The hormone profile of the cow with
physiological cyclic activity is shown in Figure 1.
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Figure 1. Trends in hormonal concentrations in the cow
(Noakes, 8th edition)
Appearance of the ovaries throughout the oestrous cycle
Growth and maturation of follicles on the ovaries occurs in a wavelike pattern
throughout the cycle (Figure 2). Each wave starts with recruitment when
gonadotrophins stimulate the rapid growth of a number of follicles. After recruitment
selection occurs and a smaller number of follicles grow further until dominance
occurs.
Figure 2. development of follicular waves and CL
during the oestrous cycle (Noakes, 8th edition)
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In the cow only one or occasionally two or more follicles become dominant, inhibiting
growth of other follicles. Maturation of a dominant follicle to an ovulatory stage can
only take place after a decrease in progesterone due to luteolysis.
Recruited follicles which do not reach the stage of dominance go into atresia and not
even each follicle reaching dominance will ovulate. Only the follicles that are
dominant in a time of low progesterone will ovulate (Senger, 1st Revised edition).
After ovulation (day 1 of the cycle) the CL rapidly begins to form. By 48 hours it is a
soft not easily palpable structure of approximately 1.4 cm. On day 7 or 8 the CL
reaches its maximal size of around 2 cm and is easily detected by rectal palpation of
the ovary as a compact mass, often protruding from the surface of the ovary. About
one day before oestrus the CL rapidly regresses and becomes a corpus albicans.
The dominant follicle is then the major structure on the ovaries when evaluated by
palpation per rectum. The follicle attains a size of 1.9 cm or more at the time of
ovulation. Throughout the cycle follicles of varying sizes can be felt (Noakes, 8th
edition).
Insemination and mating
In modern dairying Artificial Insemination (AI) is the most used method of breeding.
AI allows obtaining a large amount of offspring from a proven superior sire, thereby
facilitating genetic improvement. In 2004/05 74.2% of all New Zealand dairy cows
were artificially mated (Dairy Statistics 2004/05).
In AI diluted, cryopreserved semen is introduced through the cervix into the corpus
uteri. Since capacitation of spermatozoa in the female genital tract takes several
hours (Senger, 1st revised edition) and is fertile for at least 18-24 hours, the optimal
time for insemination is 6-24 hours before ovulation. Ovulation occurs 17-38 hours
(average 27 hours) after the first standing event of oestrous, therefore insemination
should take place in the latter half of standing heat since standing heat lasts for 1518 hours (Chaudhari and Sabo, 2006).
Since in most cases the precise stage of oestrus a cow is in when seen on heat is
not known in most cases, cows seen on heat in the morning are best inseminated
that afternoon. Cows seen in oestrus in the afternoon are consequently inseminated
the next morning (Noakes, 8th edition).
Conception rate (CR) after AI is dependent on several factors, including cow fertility,
technician’s skills, bull fertility and environmental factors.
Chebel et al. (2004) found that heat stress prior to AI lowered the conception rate
after AI. In this study a lower CR was recorded in animals that had suffered from
postparturient disease. Also, CR is reported to be higher in primiparous animals
compared to multiparous cows (Tenhagen et al., 2003; Chebel et al., 2004).
Impaired luteal function causes a decrease in Pregnancy Rate (PR). Low levels of
progesterone, measured as AUC of progesterone concentrations in milk samples,
are thought to negatively correlate with high milk yield, high dry mater intake and high
total digestible nutrient intake (Hommeida et al., 2004).
Kaproth et al. (2002) reported a relationship between the number of straws thawed at
one time and conception rate. Spermatozoan motility decreases significantly after
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being thawed for over 20 minutes, the time it approximately takes to prepare the
straws and inseminate four cows. The dosis of spermatozoa used for insemination
also influences CR. Insemination with 2 million spermatozoa has highly significant
poorer results compared to a standard dose of 15 million cells, even when deep
(intracornual) insemination is used (Anderson et al., 2004). Since in New Zealand
freshly chilled semen is mostly used, this decrease in fertility due to freezing is not to
be expected.
Exposure to a vasectomised bull postpartum appears to increase the pregnancy rate
60 days after parturition (Izard and VandenBergh, 1982).
Gestation and Parturition
Early development and maternal recognition
Following successful mating or artificial insemination during oestrus and fertilization
of the ovum in the ampulla pregnancy occurs.
The zygote starts a series of mitotic divisions, at first not increasing the size of the
early embryo (Hafez, 6th edition). Three to four days after fertilisation the zygote
reaches the uterus in the morula stage. Until attachment to the uterine wall occurs
the zygote freely moves, although in the cow change of uterine horn is rarely seen. In
the cow the embryo attaches to the uterine wall at 12 days post-ovulation. At the
same time the embryo rapidly increases its size.
Maternal recognition of the embryo occurs at 16-17 days. Production of Tau
Interferon (IFNτ) by the conceptus inhibits the release of prostaglandin F2α (PGF2α)
into the uterine vein, thereby preventing luteolysis.
In the cyclic (non-pregnant) animal PGF2α is produced in response to oxytocin
secreted by the CL, binding on the endometrial cells’ oxytocin-receptors. An increase
of oxytocin receptors is stimulated by oestradiol produced by the growing follicles.
IFNτ prevents this increase in oxytocin receptors, probably by preventing the rise in
uterine oestrogen receptors which occurs in a cyclic animal (Noakes, 8th edition).
The CL appears to be necessary for the production of progesterone for the first 200
days of gestation. After 200 days progesterone production by the placenta is high
enough to maintain pregnancy, even though the CL also still produces progesterone
(Ball and Peters, 3rd edition).
At 35 days the alantochorionic sac starts to distend the gravid horn and expands into
the non-gravid horn. At 40-60 days vascularisation of the chorion rapidly increases
and villi of the allantochorion protrude into the uterine carunculae, eventually forming
the caruncle-cotyledon complex making nutrition and gas exchange possible for the
growing and developing embryo. Until development of the cotyledons, nutrition and
gas exchange occurs by diffusion through the uterine fluid (Noakes, 8th edition).
End of gestation and parturition
Duration of gestation differs between breeds. Jerseys and Holstein-Friesians have an
average gestation of 279 days and Ayrshires 278 days. Beef cattle tend to have a
slightly longer gestation of around 279 (Angus) to 285 (Hereford) days.
In cattle (and also in other ungulates such as sheep), the foetus mainly determines
the onset of parturition. When the calf is fully developed and ready for birth it has a
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fully functioning hypothalamus. Stress factors such as hypoxia and hypercapnia
cause a rise in ACTH in the foetal blood by activation of the fetal pituitary. ACTH
results in the production of adrenaline, which causes final maturation of the calf, and
adrenal corticosteroids (mainly cortisol). The foetal cortisol stimulates the turnover of
progesterone to oestrogen in the placenta, thereby lowering the concentration of
progesterone in the dam’s blood. The oestrogens will increase the responsiveness to
oxytocin of the myometrium and will cause softening of the cervix. Later, oestrogen
will stimulate PGF2α synthesis and release by the cotyledon-caruncle complexes.
PGF2α causes increasing myometrial responsiveness to oxytocin and probably
causes luteolysis (Noakes, 8th edition). This complex process will lead to expulsion of
the foetus and the foetal membranes. The change of hormone concentrations and
events around parturition are shown in Figures 3 and 4.
Figure 3. Trends in hormone concentrations around parturition in the cow.
Parturition is on day 0. (Noakes, 8th edition)
___________________________________________________________ 15
P.A. van Iren
October 2006 – January 2007
Figure 4. Physiological changes around parturition in cattle (Noakes, 8th edition)
Puerperium
The puerperium after calving is when the reproductive organs recover from
pregnancy and cyclicity is re-established. In this period milk production commences
and increases towards peak production.
Parturition, the onset of lactation and resuming cyclicity make the puerperium a
demanding period in which disease susceptibility is generally higher.
Postpartum anoestrus
During part of the puerperium cyclic activity will be absent. In this period the uterus
regains normal shape and size and the endometrium recovers from gestation. In the
first days after parturition involution is rapid, followed by a slower phase. Most of the
involution process is complete by 20-25 days, though microscopic recovery can take
up to 52 days.
During most of the recovery process the cow is anoestrous. The pituitary is refractory
and unable to generate a preovulatory LH-surge. Though minimal activity of follicles
is seen, follicles will seldom exceed 6 mm in diameter. Suckling of the calf will
increase the refractory period of the pituitary in most occasions (Noakes, 8th edition).
Return to cycling activity after gestation
The first follicular waves are seen after 7-10 days postpartum. At this stage the
anterior pituitary is able to cause small rises in plasma FSH concentration in reaction
___________________________________________________________ 16
P.A. van Iren
October 2006 – January 2007
to GnRH release by the hypothalamus. Although FSH release is possible, the
pituitary’s ability to release high amounts of LH has not yet recovered. Therefore
ovulation is not possible at this stage. This is demonstrated by a failure of LH-rise
after endogenous GnRH administration within 10 days postpartum. Also the
administration of a high dose of oestradiol benzoate, imitating the oestrogen release
by a dominant, pre-ovulatory follicle, will not evoke the LH surge needed for ovulation
within 5 days postpartum (Noakes, 8th edition).
If a growing dominant follicle produces enough oestrogen to evoke an LH surge by
the pituitary, ovulation can occur at 21 days postpartum in dairy cows (Noakes, 8th
edition). For Holsteins in the USA an interval to first ovulation of 33.3 ± 2.1 days is
found (Wiltbank et al., 2006). A shortened luteal phase of 14 days or less is often
seen after first ovulation, especially in animals regaining cycling activity soon after
parturition (Noakes, 8th edition).
First ovulation is commonly not accompanied by oestrous behaviour, probably
because the central nervous system needs exposure to progesterone as would occur
in the luteal phase of a normal cycle (Noakes, 8th edition).
Many different factors can influence the onset of cycling activity. Apparently, the
recovering uterus inhibits the release of LH demonstrated by a rapid rise in plasma
GnRH after hysterectomy of animals postpartum (Noakes, 8th edition). Zain et al.
(1995) found that puerperal complications significantly delayed first ovulation
postpartum.
Suckling delays cycling activity, probably due to the release of opiod peptides that
results from teat stimulation by the calf. Also, corticosteroids will inhibit LH-release
(Noakes, 8th edition).
A literature study by Butler (2003) shows that nutritional status greatly influences the
postpartum anovulatory period.
A deep Negative Energy Balance (NEBAL)
increases the interval from parturition to first ovulation. Rukkwamsuk et al. (1999)
and Shrestha et al. (2005) support these findings. Having a deep negative energy
balance suppresses pulsatile LH secretion by the pituitary and decreases ovarian
responsiveness to LH. Insulin appears to stimulate the growth of follicular cells but is
low during NEBAL. IGF-1 is crucial for follicular development and is also negatively
correlated to a negative energy status (Butler, 2003). Johnsson et al. (1997) found an
inverse relationship between the plasma concentration of glucose and time to first
ovulation postpartum in dairy cows. An inverse relationship between Total Digestive
Nutrient (TDN) intake and interval from calving to first ovulation is also reported (Zain
et al., 1995).
High tri-iodothyronine (T3) / thryroxine (T4) is associated with the early onset of
ovarian cyclicity. Since T3/T4 are usually lower in periods of heat stress, this might
explain the prolonged interval from calving to first ovulation seen in hot periods (Reist
et al., 2003). Johnsson et al. (1997) also found a prolonged interval calving to first
ovulation in periods of heat stress.
Surprisingly, Shipka and Ellis (1999) found that bull exposure postpartum extends the
period of ovarian reactivation in dairy cows, causing a prolonged interval from calving
to first ovulation. This does not support findings in sheep and beef cattle, reporting
that the presence of a mature male animal usually shortens the anovulatory
anoestrous period postpartum in other species. Izard and VandenBergh (1982)
confirm a shortening of the interval between parturition and resuming cycling activity
when a bull is present postpartum.
___________________________________________________________ 17
P.A. van Iren
October 2006 – January 2007
Chapter 3 Automated heat detection using a camera-software
device and oestrus detection strips
Introduction
The camera-software device (CSD) is a new device, developed as an extension of
the tail painting system most frequently used in New Zealand and mentioned earlier.
The complete system consists of a digital camera, a software program and a number
of reflective strips placed on each cow to be observed (Oestrus Detection Strips,
ODS). These strips are partly covered with a layer of paint. The system is based on
the tail paint principle: as soon as the oestrous animal becomes mounted, a portion
of paint will be rubbed of.
The aim of the CSD is to automate the reading of oestrus signs as previously done
by visually scoring the removal of tail paint from the cow’s tail base. The CSD is used
to automatically measure the amount of paint rubbed off the ODS when cows are
mounted during oestrus. Required equipment is mounted in the milking shed and the
system operates during milking to detect cows on heat, securing a twice daily
inspection of the entire herd.
The oestrus detection strip
The ODS consists of a strip of reflective tape (3M Scotchlite reflective strip, 9920, 3M
company Ltd. Auckland, New Zealand) partly covered by a layer of black paint.
(water-based low sheen acrylic, Resene Paint Ltd. Palmerston North, New Zealand)
The mentioned materials where chosen according to preliminary suitability studies
performed by Butler (2000) and Alawneh (2003) (Alawneh, Thesis).
When an oestrous animal is mounted, part of the paint will rub off and therefore the
measured area of reflection of light increases.
The strips’ dimensions are 150mm x 50 mm and the central part is covered by the
black paint. This leaves a reflective part of 25mm x 50 mm on both ends of the strip.
Strips where hand made by cutting lengths of tape of 150 mm x 50 mm. Both ends
where covered with adhesive tape to ensure two reflective indicator areas of 50 mm x
25 mm. Black paint was subsequently applied to the middle part using a paint brush
or spray applicator. The indicator areas and the specific height x width ratio (3X1)
allowed the software to recognise the strip. (Figure 5.)
Figure 5. Schematic representation of an oestrus detection strip
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P.A. van Iren
October 2006 – January 2007
Figure 6. Photograph of an ODS on a cow, slight
rubbing is visible in the centre part
(Photograph by P.A. van Iren)
The camera-software device
The CSD consists of a digital camera and a computer equipped with the appropriate
adequate software. Video Image Processing Software, VIPS made by Bailey and
Hodgson (1988) was initially used. In current studies an update version of this
software and camera are used.
Two types of cameras (SONY SX-900, Intel web cam™) were tested in a trial
(Alawneh, Thesis) to investigate their suitability for the CSD in prototype trials. The
Intel web cam™ was chosen because of it’s low costs, but didn’t appear to have the
adequate resolution. Further, a wide angle lens was suspected to cause problems
because of the variability in the height of cows. Also with the Sony and the VIPS
system, the image capture became unreliable after approximately an hour of
operation due to a bug in the software driver.
In the current studies a robust, commercially available camera and adjusted software
were used. (EDiT ID, software, proof of concept version, EditID Ltd. Auckland, New
Zealand)
The camera is flanked by a strong light source on each side to insure adequate
reflection emitted by the strip. For optimal reflection the camera should be mounted
directly above the position of the ODS, but in some milking parlour settings, this
appeared to be impossible because of the construction of the rotary dairy platforms.
The camera was then set up to view the strips from an angle, with the lights
projecting at the same angle.
The software program used for analysis of the images taken by the camera is able to
automatically identify the presence of the ODS by recognizing the reflecting indicator
areas and the specific height x width ratio of the strips. The software calculates a
percentage of reflective area in the middle part of the strip, indicating the percentage
of paint removed from the strip by mounting activity. The entire system is
schematically shown in figure 7.
___________________________________________________________ 19
P.A. van Iren
October 2006 – January 2007
Figure 7. General CSD component set up (Alawneh, Thesis)
Trials with the CSD
Since the start of the design of the camera-software device numerous trials and
projects have been undertaken to achieve a device functioning on a commercially
acceptable level.
Experiments, in the field and in the lab, testing reflection, durability, flexibility and
adhesion to glue were conducted to choose the optimal reflective material for making
the ODS. A number of paints were tested for reflection, durability, elasticity, ability to
withstand weather conditions and adhesion to the strip. These experiments resulted
in the choice of the 3M Reflective Strip (3M Scotchlike reflective tape, 3M Company
Ltd. Auckland, New Zealand) and the Zylone low sheen black paint for this trial
(Water-based low sheen acrylic, Resene Paint Ltd. Palmerston North, New Zealand)
(Alawneh, Thesis).
The Ados F2 glue (CRC Industries New Zealand Ltd. Auckland, New Zealand) was
used for application and its durability was tested. In the last two trials Ados F3 was
used because its’ shorter drying time, whilst other properties were similar.
In 2003 Alawneh et al. tested the CSD at Massey Dairy Unit No. 4, Palmerston North.
In this trial the CSD was compared to a control group using tail paint. In this trial
significant differences in sensitivity (85% vs. 78%; p=0.006) specificity (99.6% vs.
98.0%; p<0.001), Positive Predictive Value (88%vs. 51%; p<0.001) and overall
accuracy (99% vs. 98%; p<0.001) were found between a CSD treated and a control
group respectively. In this research oestrus was detected using visual observation,
tail paint and the CSD in the CSD group and using tail paint and visual observation
only in the control group. Besides the sensitivity, specificity and PPV, a number of
reproductive parameters was calculated to compare the achievements of both groups
as shown in Table 2 (Alawneh et al. 2006).
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P.A. van Iren
October 2006 – January 2007
Reproductive monitor
Group
Control
CSD
P-value
Target
% calved < 40d at PSM
21 day submission rate
28 day submission rate
Return intervals 2-17d
Return intervals 18-24d
Return intervals 39-45d
Ratio of (18-24d) to (39-45d)
1st service -49 d NRR
Total services – 49d NRR
1st service pregnancy rate
Total services conception rate
Services/ conception
4 week ICR
8 week ICR
26%
76%
81%
21%
64%
3%
22:1
47%
57%
39%
46%
2.2
44%
70%
19%
75%
81%
32%
56%
1%
42:1
71%
74%
72%
70%
1.4
70%
90%
0.10
0.92
1.00
0.007
0.077
0.11
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
10%
90%
92%
13%
69%
7%
9:1
61%
61%
60%
60%
1.7
57%
86%
% not in calf by PSM +165d
Calving to conception interval
27%
84d
10%
77d
<0.001
<0.001
7%
83d
Table 2. Reproductive performance of CSD vs. Control group
(Alawneh et al., 2006)
In 2005 Alawneh et al. compared a longitudinal (CSD long) and a transverse (CSD
trans) placement of the ODS to oestrus detection using visual observation and tail
paint (Control). This experiment was again conducted at Massey Dairy Unit No. 4,
Palmerston North. It appeared that a transverse placement of the ODS resulted in a
less accurate, specific and sensitive oestrus detection than the longitudinal
positioning. The number of false positives in the CSD trans in this experiment was
much higher than in the CSD long group.
Sensitivity (93.5, 82, 86.7), specificity (99.3, 98.8, 99.1) and overall accuracy (99.1,
98.2, 98.7) were calculated for CSD long, CSD trans and control group respectively.
Accuracy was defined as the proportion of true detections compared to the total
amount of detections. Pregnancy testing was used as “gold standard” to confirm true
oestrus in this trial. (Alawneh et al., 2006)
The author was involved in a trial integrating the CSD with electronic identification
software (EDiT ID Ltd. Auckland New Zealand) allowing automated identification of
cows in oestrus by means of an electronic ID ear tag (Admin Tags, Allflex New
Zealand Ltd. Palmerston North). Integration of electronic identification with
automated oestrus detection should, in the end, lead to a fully automated system of
detecting and drafting cows on heat. More information on this trial is to be found in
chapter 5 of this report.
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P.A. van Iren
October 2006 – January 2007
Chapter 4 Automated heat detection by a camera-software
device and interaction with North American Holstein genetics
Abstract:
Aim
This analysis is carried out to investigate a relationship between a high percentage of
North American Holstein (NAH) genes, reduced fertility and poorer expression of
oestrus. The efficacy of a camera-software device (CSD) for detection of oestrus in
dairy cattle was tested in groups of high, medium and low percentages of NAH
genes.
Methods
The trial that forms the basis of this research is conducted at Massey Dairy Unit No.
4 during the mating season of 2003 (Alawneh et al., 2006). Four hundred and eighty
animals were used to test the functioning of the newly developed CSD. In the current
research the animals were reallocated into groups according to their NAH genotype.
Groups were made of less than 10%, 10-30% and over 50% NAH genes. Outcomes
for the methods of oestrus detection were calculated and compared among the
genetic groups using a χ2-test. A reproductive monitor report comparing the
reproductive performance of the separate groups was also made using DairyWIN™.
Results
No significant results were obtained from this research. A comparison of the
outcomes between the groups, and comparison of the reproductive performance of
the different groups, did not show a clear trend that suggests a relationship between
NAH genetics, oestrus expression and reduced fertility.
Conclusion
To further investigate the cause of the reduced fertility observed worldwide and to
determine the role oestrus expression plays in this decline, more research is needed.
Since fertility is such an important subject in dairying, especially in a seasonal
system, finding the cause(s) of declining fertility is necessary to stop this decline.
Introduction
A decline of reproductive efficiency is reported over the last few decades in countries
all over the world, (Mee, 2004; Horan et al., 2005; Wiltbank et al., 2006; Williamson,
2006).
In Ireland, where a seasonal calving pattern is also maintained, an increase in
calving interval of approximately one day per year is reported (Mee, 2004). Also, a
prolonged interval from calving to first ovulation and a higher prevalence of anoestrus
is found (Horan, 2005).
The prolonged interval to first ovulation is often considered to be the consequence of
a strong NEB after calving (Wiltbank et al., 2006). NAH cows appear to get in a deep
NEB, especially on pasture based systems because of their inability to match dietary
intake to nutrient demand for high production in the absence of concentrate feeding,
(Horan et al., 2003; Williamson, 2006).
For Holstein cows an average of 33 days +/- 2.1 days from calving to first ovulation is
found under typical circumstances in the USA. Anovulation and smaller maximal size
of the ovulatory follicle were more likely to be found in cows with a lower body
condition score (BCS), indicating the possible relationship between NEB and
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P.A. van Iren
October 2006 – January 2007
prolonged puerperal anoestrus. NEB can however not be seen as an adequate
explanation for all cases of postpartum anoestrus (Wiltbank et al., 2006).
Thiengtham (2003) did not find a prolonged interval to first ovulation in a high North
American Holstein genetic merit group of animals compared to a group of more
traditional New Zealand Friesian animals. He did however observe a lower
conception rate in these animals.
Dillon et al. (2003) found a significant difference in calving to service interval between
Montbeliarde and Holstein-Friesians. These breeds had a calving to service interval
of 64.9 and 71.5 days respectively.
Besides the increasing interval to first ovulation postpartum, also a decline in
conception after insemination from 66% in 1951 to 40% in 1997 is reported. One of
the possible causes mentioned is the inaccuracy of oestrus detection (Alawneh,
Thesis; Mee, 2004).
One of the major trends that coincides with the declining fertility of dairy cows
reported all over the world is the increase of North American Holstein (NAH) genetics
in herds worldwide. In the 1990s, research already indicated the poorer reproductive
performance of imported Holsteins in Ireland (Mee, 2004). The average percentage
of NAH genetics rapidly increased from 9% in 1990 to 65% in 2001 in Ireland (Horan,
2005).
For the British Isles, the proportion of NAH was estimated at 80% in 1998, while the
genetic composition of Dutch dairy herds approaches 100% NAH (Mee, 2004). In
New Zealand dairy cows the percentage of NAH genetics is found to be around 40%
(Williamson, 2006).
Multiple factors are considered to be involved in the decline of fertility including
genetic merit, milk yield, management, nutritional factors and oestrus expression and
detection (Mayne et al., 1999; Mee, 2004; Alawneh, Thesis; Williamson, 2006).
Failure to accurately detect oestrus can be a major component in decreasing fertility
especially in seasonal herds. Missing oestrus can occur because of inadequate
oestrus detection, but can also be the consequence of low oestrus intensity or short
oestrus duration. Research on Irish dairy cows showed a decrease in duration of
oestrus from 9.3 hrs in the 1970’s to 8.4 hrs in 2002. Furthermore, the number of
mounts seen per oestrus declined from 52 to 12 in the same period (Mee, 2004).
Although the number of mounts can depend on many factors such as flooring,
number of other cows on heat simultaneously and stress (van Vliet and van
Eerdenburg, 1996; Orihuela, 2000) this decrease is alarming.
Research that used HeatWatchTM mount detectors also pointed out a difference of
duration of oestrus between high (over the herd average of 40kg/d) and low (under
the herd average of 40kg/d) producing cows. The high yielding cows had a mean
duration of oestrus of 6.2 ± 0.5hr, compared to 10.9 ± 0.9hr in the low yielding group.
Possible influences of parity in this trial were excluded by separate analysis of primiand multiparous animals (Wiltbank et al., 2006). This research indicated a negative
correlation between milk yield and oestrus expression while other publications refer
to a negative correlation between milk yield and fertility in general (Dhaliwal et al.,
1996; Butler, 2003; Pryce et al., 2004). Dillon et al. (2003) indicate a relationship
between reduced fertility and survival rate versus NAH genetic influence in dairy
breeds.
Since a large part of the genetic merit of North American Holsteins is due to their
high milk yield, the existence of a negative relationship between high yield and
oestrus expression should become obvious in animals with high NAH genetics. As it
___________________________________________________________ 23
P.A. van Iren
October 2006 – January 2007
appears that there is a reduced intensity of oestrous behaviour in NAH animals,
oestrus detection will be even more difficult in those animals. Decreased numbers of
mounts per oestrus and reduced duration of oestrus will decrease opportunities to
observe oestrous cows and will probably reduce the accuracy of oestrus detection
aids such as tail paint.
For the newly developed camera-software oestrus detection device (Alawneh et al.,
2006), a reduced number of mounts per oestrous cow may influence its utility for
oestrus detection in herds with a high percentage of NAH genetics. The CSD system
uses a reflective strip (Oestrus Detection Strip) partly covered by black, non-reflective
paint and read by a camera, to detect oestrus in dairy cattle. A small number of
mounts received by the oestrus cow may, in some cases, be insufficient to remove
paint from the reflective strip, causing false negatives.
The objectives of this study are:
1. To investigate a relationship between the proportion of NAH genes and
functionality of the CSD.
2. To investigate a possible poorer expression of oestrus in high NAH animals.
Materials and Methods
The data used in this study were derived from a trial conducted in the spring of 2003
at Massey University No. 4 Diary Unit by Alawneh et al. (2006). Materials and
methods for this trial were described as below.
The farm
This trial was conducted from 06 October to 04 December 2003 on the Massey
University Number 4 Dairy Unit, commercially operating in the Manawatu region of
New Zealand,. The farm has 227.37 ha of pasture divided into 98 paddocks. The
herd consisted of 480 cows of Jersey and Holstein-Friesian breeds and their
crossbreds. Study cows were 2-14 years old with body condition scores from 3.0 –
7.0 (mean 4.0 on a scale of 1-8). Cows grazed as one herd on pasture except at
milking and were allowed free access to water. In case of grass shortage the ration
was supplemented with maize-silage to meet daily requirements and prevent
excessive loss of body condition.
The animals were milked in a 50 bail DeLaval rotary parlour twice daily at
approximately 5.30 AM and 3.00 PM. Staff consisted of a farm manager and milking
staff. Oestrus detection occurred by visual observation twice daily before the AM and
PM milkings, aided by tail paint. (Caution Tell Tail, FiL New Zealand, Mount
Maunganui, New Zealand). Staff considered cows to be on heat when >75% of tail
paint was gone or when behavioural signs of oestrus were seen, with standing to be
ridden as the most obvious sign. Artificial insemination occurred once a day after the
AM milking on cows seen on heat that morning or the previous evening. Insemination
was done by an AI professional with Holstein-Friesian, Jersey or crossbreed semen.
Allocating animals into groups
Animals were stratified by age, BCS and days in milk and randomly allocated into two
groups. group was fitted with ODS in a longitudinal orientation (CSD). A second
group was not equipped with an ODS. All cows in both groups had tail paint (Tell Tail
oil-based paint; FiL New Zealand Ltd. Mount Maunganui, New Zealand) applied to
their tail base for oestrus detection by farm staff.
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P.A. van Iren
October 2006 – January 2007
Camera-software device
The camera used for ODS reading was mounted in the above the milking parlour,
120-150 cm above the ODS at a right angle.
The camera was attached to a computer (NEC Versa M320) by a network cable. A
software program (EDiT ID, software, proof of concept version, EditID Ltd. Auckland,
New Zealand) was used to analyse the presence of an ODS on the cows and to
calculate the percentage of paint rubbed off. A cow was considered to be on heat
when either:
- the proportion of paint removed exceeded 10%
- the strip was missing
Cow numbers were recorded manually during milkings.
Oestrus detection strips
Oestrus Detection Strips are strips of reflective material (3M Scotchlite reflective
strips, 9920, 3M Company Ltd. Auckland, New Zealand) partly covered by a layer of
black paint (Water based low sheen acrylic; Resene paint Ltd., Palmerston North,
New Zealand). At oestrus, mounting activity of other cows rubbed off part of the black
paint, thereby creating reflective areas in the middle part of the strip. The strips are
recognized by the system due to its dimensions (height X width ratio of 3X1) and
reflective indicator areas at head and tail ends of the strip.
Pregnancy Diagnosis and milk sampling
Rectal palpation and ultrasound examination were carried out 50-51 days after the
end of mating. Estimates of gestation stage were used to determine when the
oestrus had occurred. An observed oestrus leading to pregnancy was considered to
be a true oestrus. Reverse counts of 21 days (± 3days) and 42 (±3 days) from
inseminations resulting in pregnancy were also made. Any oestrus detected in that
range was considered to also be true one. Milk samples for progesterone analysis
were taken from every animal with suspected oestrus to confirm oestrus. Oestrus
was considered to be true when the concentration of progesterone in the milk sample
was below 1.0 ng/ml. Results of these analyses were not used for the publication of
the 2003 results, but are used in this study.
Analysis of data
In the 2003 trial the CSD and control groups were compared by calculating
sensitivity, specificity, PPV, NPV and accuracy. In this trial sensitivity, specificity,
PPV and overall accuracy were all better for the CSD group than the control. As
shown in table 4, NPV did not differ significantly.
Group
Control
CSD
Method of
oestrus detection
Sensitivity
Specificity
PPV
NPV
Overall
Accuracy
Farmer
78%
98%
51%
99.3%
98%
95% CI
73 to 83
97.7 to 98.3
46 to 56
99.2 to 99.6
97.2 to 98.7
CSD
85%
99.6%
88%
99.4%
99%
95% CI
80 to 87
99.4 to 99.7
84 to 91
99.3 to 99.6
9838 to 99.2
Farmer
72%
98.1%
57%
99%
97%
95% CI
67 to 76
97.8 to 98.3
53 to 61
98.8 to 99.2
96.8 to 97.4
Table 4. results of 2003 trial. (Alawneh et al., 2006)
___________________________________________________________ 25
P.A. van Iren
October 2006 – January 2007
Analysis of data in groups based on the percentage of NAH genes
For the current research the data were reallocated within the control or CSD groups
based on their percentage of NAH genes. Six new groups were created, three
controls and three CSD groups. Two groups consisted of animals having less than
10% NAH genes, two groups had 50% or more NAH genes and two groups had
between 10 and 30% NAH genes. Characteristics of the groups are summarized in
table 5.
Genetic background of each animal present in the 2003 herd was derived from the
Livestock Improvement Corporation (LIC) database.
Control
CSD
Con≤10
Con10-30
Con≥50
CSD≤10
CSD10-30
CSD≥50
Name
% NAH
≤ 10%
10-30%
≥50%
≤10%
10-30%
≥50%
Number of
24
94
17
28
91
16
animals
Method of
VO/TP
VO/TP
VO/TP
CSD,
CSD,
CSD,
oestrus
VO/TP
VO/TP
VO/TP
detection
Average % of
3.11%
20.19%
57.80% 4.05%
20.53%
57,54%
NAH
Average percentage of NAH of trial herd was 25.57%
Table 5. Characteristics of analysed groups (VO = visual observation; TP = tail paint)
Sensitivity, specificity, overall accuracy, positive predictive value (PPV) and negative
predictive value (NPV) were calculated for each group using contingency tables.
Oestrus was defined as true in the following cases (used as the gold standard):
- Detected oestrus was confirmed by pregnancy diagnosis (PD) through
estimating the stage of the detected pregnancy. Oestrus was true if
pregnancy followed insemination during a detected oestrus.
- A detected oestrus preceded an oestrus confirmed by PD by 21±3 days
(Noakes, 8th edition)
- A detected oestrus coincided with a concentration of progesterone in milk
below 1.0 ng/ml 1
1
) In this trial, low progesterone concentrations were occasionally found at stages
of the oestrous cycle, such as luteal stages. Low progesterone was even found in
animals with confirmed pregnancy. Therefore not every occurrence of a low P4
was considered to be a true oestrus. Two drops in P4 with an 18-24 day interval
were considered to be true. Since progesterone results appeared to be less
reliable than the occurrence of pregnancy, PD results outweighed progesterone
results when relevant.
Sensitivity is defined as the number of oestrus events observed divided by the total
number of oestrous events that occurred according to the gold standard. Specificity is
the proportion of animals found not to be in oestrus according to the method of
detection that were not found in oestrus by the gold standard. The PPV is the
probability of an animal observed to be in oestrus actually being in oestrus according
to the gold standard. The NPV describes the probability that an animal found not to
be in oestrus is not in oestrus according to the gold standard.
Overall accuracy was calculated as the measure of the true findings [true positives +
true negatives, i.e. all true cases found]/[true positives + true negatives + false
positives + false negatives, i.e. the total number of findings] (Alawneh et al., 2006).
___________________________________________________________ 26
P.A. van Iren
October 2006 – January 2007
The significance of the difference between the con ≤10, con 10-30 and con ≥50
(control and treated groups) was calculated using a χ2 test. The same was done with
CSD ≤ 10, CSD 10-30 and the CSD ≥50 groups.
Using a χ2 test, the statistical significance of differences in sensitivity of the
mentioned groups true positives (a) and false negatives (c) for each of the three
genetic groups were compared. For specificity, false positives (b) and true negatives
(d) were used, for NPV false (c) and true (d) negatives and for PPV true (a) and false
(b) positives. For overall accuracy a 95% confidence interval was calculated. This is
shown in the table of observed frequencies shown below.
Test
Results
Gold Standard
+
+
a
b
c
d
Table 6. Table of observed frequencies
Besides calculating the values mentioned above, DairyWINTM was used to obtain a
reproductive monitor for each of the separate genetic groups that described their
reproductive performance.
Results
Calculating the test properties led to the following tables. Table 7 shows the results
for the CSD groups and table 8 for the controls.
CSD>/50
Sensitivity 92%
Specificity 100%
Accuracy 99.5%
95% CI
NPV
PPV
CSD10-30
96%
99%
98.9%
CSD<10
95%
99%
98.7%
98.9-100
98.4-99.3
97.8-99.5
100%
92%
100%
92%
100%
83%
χ2
0.32
2.28
P-Value
0.85
0.32
0.36
1.25
0.83
0.53
Table 7. Results for the CSD sister groups (CI = Confidence Interval)
As shown in table 7, none of the observed differences in the calculated values for
these groups was significant and no evidence of better performance of the CSD in
the group with the low percentage of NAH genes was found. There was no better
performance of the CSD in groups of animals with a lower proportion of NAH. There
also was no indication of poorer expression of oestrus in animals with a high
percentage of NAH genes.
CON>/50
Sensitivity 88%
Specificity 99%
Accuracy 98.2%
95% CI
NPV
PPV
CON10-30
86%
98%
97.6%
CON<10
90%
99%
98.8%
96.9-99.4
97.0-98.2
98.0-99.7
100%
71%
99%
92%
99%
87%
χ2
0.29
3.94
P-Value
0.86
0.14
0.14
4.70
0.93
0.10
Table 8. Results for the control groups (CI = Confidence Interval)
___________________________________________________________ 27
P.A. van Iren
October 2006 – January 2007
Also, in the control groups, no significant differences can be seen. There is no
evidence suggesting that oestrus detection as it is done by the farmer is more
successful in groups of animals with a lower NAH percentage so no evidence of
poorer expression of oestrus in animals with a high percentage of NAH genes is
evident.
No statistical analysis has been done on the reproductive monitor (Table 9) because
of the limited time available for this study. Because no statistical analysis was done,
no conclusions were made from comparing the performance of the groups using this
reproductive monitor. Also, no apparent trends can be observed from the data shown
in table 9. It can be seen however that submission rates at 21 and 28 days are higher
in both CON<10 and CSD<10 groups when compared to other groups with higher
percentages of NAH genes. This indicates a higher percentage of animals were seen
in oestrus in these groups, possibly suggesting a more obvious oestrus expression.
Both groups also have a high percentage of irregular oestrus intervals, indicating that
many of the observed oestruses may have been false.
___________________________________________________________ 28
P.A. van Iren
October 2006 – January 2007
Reproduction Monitor
Original Trial 2003
Control * CSD *
CON<10
% calved <40days at PSM
26%
19%
31%
21-day Submission rate
76%
75%
82%
28-day submission rate
81%
81%
86%
Return interval: 2-17d
21%
32%
25%
Return interval: 18-24
64%
56%
71%
Return interval: 29-45d
3%
1%
0%
Ratio of (18-24 day cyc) to
22:1
42:1
(39-45 day cyc)
1st service 49 day NRR
47%
71%
27%
Total service 49 day NRR
57%
74%
50%
1st service pregnancy rate
39%
72%
27%
Total services pregnancy rate
46%
70%
46%
Services per conception
2.2
1.4
2.2
4-week in-calf rate
44%
70%
46%
8-week in-calf rate
70%
90%
88%
% not in-calf by PSM+165
27%
10%
12%
days
Calving to conception interval
84 days 77 days 81 days
Cyc = cycle; NRR = non return rate (* Alawneh et al., 2006)
Analysis based on genetic background
CON10-30
CON>/50
CSD<10
CSD10-30
CSD>/50
Target
25%
78%
82%
18%
64%
6%
12:1
18%
70%
70%
0%
80%
0%
-
23%
91%
94%
50%
50%
0%
-
12%
85%
88%
23%
58%
0%
-
22%
58%
68%
33%
56%
0%
-
10%
90%
92%
13%
69%
7%
9:1
48%
59%
44%
49%
2.0
48%
72%
24%
76%
77%
53%
59%
1.7
45%
65%
35%
65%
69%
71%
67%
1.5
87%
93%
7%
68%
74%
69%
73%
1.4
72%
96%
4%
72%
67%
78%
59%
1.7
58%
84%
19%
61%
61%
60%
60%
1.7
57%
86%
7%
80 days
78 days
74 days
82 days
74 days
83 days
Table 9. Reproduction Monitor of test groups
___________________________________________________________
P.A. van Iren
October 2006 – January 2007
29
Discussion
Analysis of the test properties of oestrus detection, as was done by the farmer with or
without the help of the CSD did not reveal a statistically significant difference in the
performance in oestrus detection between groups with different genetic
compositions. No link could be made between the efficacy of the CSD and the
genetic background of the animals. This indicated that a high percentage of NAH
genes did not cause any difference in efficacy for either of the methods of detecting
oestrus.
No obvious difference could be seen in reproductive performance between groups
after a reproductive analysis using DairyWINTM. In most cases the CSD groups
appeared to perform better than the control groups, but no obvious and repeated
difference was seen between groups of animals with a higher level of NAH genes
compared to those with a lower proportion. No evidence was found from this study to
support the hypothesis that the reduced fertility amongst Holstein animals that is
reported worldwide (Mee, 2004; Horan et al., 2005; Wiltbank et al., 2006; Williamson,
2006) was a result of a reduced intensity of oestrus expression.
Although the submission rate was higher in both CON and CSD <10, the
percentages of return intervals that were irregular (outside the physiological window
of 18-24 days) suggests that part of those submissions may have been of animals
that were not on heat, or that there was a significant number of genuine short cycles,
or that there was a significant number of genuine short cycles.
This study was not sufficient to be definitive and a relationship between reduced
oestrus expression and reduced fertility might still exist. Several factors have possibly
contributed to the fact that this trial was not able to prove such a relationship.
The number of animals in this test was relatively small which limits the power of the
study. The number of animals in the study was greater to begin with, but a number of
the animals had to be excluded since their identity could not accurately be
determined because of loss of ear tags, administrative mistakes and loss of data due
to fact that a number of records could no longer be retrieved since the cows had left
the farm and their records had been removed from the database. Further animals
had to be excluded because no oestrus had been observed or no confirmation of any
oestrus could be given by pregnancy diagnosis or progesterone analysis. This
caused some of the groups to be as small as 16 animals.
This study in bringing such a complex, multifactorial subject as reduced fertility down
to North American Holstein influence only may be oversimplifying the problem.
Analysing this complex matter by only using one simple χ2 analysis on only one trial
with only 480 animals does not approch the much larger thorough analysis that is
needed to determine better the relationship between oestrus expression, reduced
fertility and NAH influence.
Since the importance of fertility is so critical for modern dairying, especially in a
seasonal system, more research is needed. The increase of the calving interval by
one day each year as is reported in Ireland (Mee, 2004) is a worrying development,
as is the decline of reproductive efficiency reported worldwide (Horan et al., 2005;
Wiltbank et al., 2006; Williamson, 2006). The possibility of a NAH influence on the
expression of oestrus must not be overlooked, but since the decline in fertility is more
likely a multifactorial process, a multivariate analysis on a large number of animals is
likely to be required to define the problem and to find a solution.
___________________________________________________________ 30
P.A. van Iren
October 2006 – January 2007
Chapter 5 Integration of a camera-software device with
electronic identification for the detection of oestrus in dairy
cattle
Abstract
Aim
This trial was conducted to test the integration of a camera-software device for
detecting oestrus in dairy cattle at pasture with an electronic identification system.
This step will be necessary for recognizing oestrous animals automatically for
drafting and insemination.
Methods
Dairy cows (n=205) in a commercial herd under typical New Zealand circumstances
were fitted with oestrus detection strips, tail paint and an electronic ear tags for
identification. Recognition of the animals and detection of oestrus by the system were
investigated by comparing logs of the system to insemination records of the farm
staff.
Results
Though final results are not yet calculated a large number of animals lost their strip
during oestrus, instead of paint being rubbed of. The strip loss in these observations
exceeds results of earlier trials. Recognition of the animals appears to be correct, but
allocation to correct bails of the milking parlour was not accurate on several
occasions.
Conclusion
During this trial, several problems and faults in the process of integration came to
light and the trial therefore pointed out areas where improvement is needed to
achieve a commercially operational system.
Introduction
Managing large herds in a seasonal system of dairying, as done in New Zealand, is a
challenge. The success of this management system requires a compact calving
period to match pasture availability with the nutrient demand of the herd. For a
compact calving period to occur, a short mating period is necessary, putting major
pressure on oestrus detection (Verkerk, 2003; Alawneh et al., 2006). Every missed
oestrus decreases the chance to get the animal pregnant this season. Since empty
cows are usually culled, inaccurate oestrus detection can greatly increase costs.
A camera-software device (New Zealand Patent by Massey University No.519743,
IPC7, G01N33/74) is a new device for detecting oestrus, developed as an extension
of the tail painting system frequently used in New Zealand. The complete system
consists of a camera, a software program and a number of reflective strips attached
to each cow to be observed (Oestrus Detection Strips, ODS). The reflective material
of the strips is partly covered with a layer of black paint. The aim of the CSD is to
automate the reading of oestrus signs, as done previously by visually scoring the
percentage of tail paint removed from the cow’s tail base, thereby making oestrus
detection less laborious and more accurate in large herds. The CSD is used to
measure the amount of paint rubbed off the ODS when cows are mounted during
oestrus. The equipment is installed in the milking shed and operates during milking to
___________________________________________________________ 31
P.A. van Iren
October 2006 – January 2007
detect cows on heat. It would be desirable to have a fully automated system for
recognizing and drafting cows on heat for insemination.
The CSD on its own was tested in earlier occasions (Alawneh et al., 2006; Alawneh,
Thesis). In a comparison trial conducted at Massey Dairy Unit No. 4, Alawneh et al.
(2006) found a significant difference between oestrus detection in the conventional
way by tail paint and visual observation and by conventional oestrus detection aided
by the CSD. Cows in the CSD group had a higher non return rate at 49 days after
both first (71% vs. 47%) and all (74% vs. 57%) services and a lower number of
services per conception than the control group (1.4 vs. 2.2). Sensitivity, specificity,
positive predictive value (PPV) and overall accuracy of oestrus detection were higher
for the CSD group when compared to the controls.
A step in developing a fully automated system is integrating automatic electronic
identification of the cows while on the platform with the observations made by the
CSD, making recognition of the animals on heat possible for the farmer. This would
make it possible to automatically draft an oestrous cow after milking because of her
electronic identification on the platform.
In this trial the integration of the CSD with a commercially available identification
system was tested. This trial was conducted on a commercially operating dairy farm
in the Manawatu region of New Zealand from October to December 2006.
Materials and methods
The Farm and the animals
The trial was conducted on a commercial dairy farm in the Manawatu region of New
Zealand near Fielding. The farm comprised 90 ha of pasture divided into 50
paddocks. Cows were fed on a ryegrass clover pasture ration supplemented with
maize-silage in periods of grass shortage to prevent extensive loss of body condition
and they had free access to water. The herd consisted of 211 animals, all included in
the trial. Animals were of Holstein, Friesian and Jersey breeds and their crossbreds.
The cows were kept in 2 herds, a regular herd including all the healthy lactating cows
and a lame herd comprising the lame animals and the animals that received
treatment that required withholding their milk. The lame herd grazed closer to the
milking shed to limit the distance from pasture to milking for the lame animals.
Milking occurred twice daily, at approximately 6.00 AM and 3 PM in a 28 bail Waikato
rotary parlour (Waikato Milking Systems NZ Ltd., Hamilton, New Zealand). Automatic
cup-removers and semiautomatic drafting were used. All animals were fitted with
regular ear tags containing their management identification number (MID) in both
ears and an electronic identification ear tag (EID) (Admin tags, Allflex NZ Ltd,
Palmerston North, New Zealand). EID was fitted in the right ear only.
Besides the use of the CSD, oestrus detection was carried out by visual observation
twice daily before milking, aided by Tail Paint (Caution Tell Tail, FiL NZ Ltd, Mount
Manganui, New Zealand). Each cow was equipped with an oestrus detection strip
(ODS) in longitudinal orientation over the spine in the sacrococcygeal region, just
cranial to the tail paint. Tail paint was applied over the tail base.
Insemination of cows detected on heat by the farm staff (with or without confirmation
by the system) at the AM and PM milking took place after each PM milking and was
carried out by a professional AI-technician using semen of proven bulls.
___________________________________________________________ 32
P.A. van Iren
October 2006 – January 2007
During the trial 65 cows received a treatment in relation to fertility problems.
46 cows with CIDR devices. (Pfizer EAZI-BREED™ CIDR® (Progesterone)
Cattle insert, 8 day program with 2 mg Oestradiol benzoate (ODB; CIDROL,
Bomac Laboratories Ltd. Auckland New Zealand) at day 1 and 1 mg at day 8.
- 19 cows with Prostaglandin F2α (Estraplan injection, 2 ml IM. Parnell
Laboratories Ltd. Auckland, New Zealand)
Further, some cows received treatment for lameness, mastitis or paralysis during the
trial period.
The CSD
The CSD consists of a camera (CS4 VGA 640x480 Camsensor Technologies Ltd.
Auckland, New Zealand) for capturing an image of the ODS on the cows. To
improve visualisation of the strips, two halogen spotlights (Wide angle 40W Tungsten
halogen spotlight) flanked the camera. The camera was mounted 3 bails away from
the entrance.
Automatic reading of the EID is integrated with computer software to allow automatic
recognition of the animals on screen. Automatic identification of the animals was new
in this trial and is not been done in previous trials with the CSD. Cow present sensors
were used to detect the presence of a cow as a trigger for the camera to take
images.
The systems were connected to the PC by a network connection. The software
automatically stores the logs and images made after each milking making analysis
and comparison to a visual log possible. The computer was attached to a speaker in
the shed, providing an auditory signal to check heat in cows suspected of being in
oestrus.
Once a threshold level of paint was removed or if the strip was missing, the cow was
signalled to be suspected of oestrus.
Figure 8. Situation at trial farm
___________________________________________________________ 33
P.A. van Iren
October 2006 – January 2007
The ODS
An oestrus detection strip is a strip of reflective material partly covered by a layer of
black paint. The reflective strip (3M Scotchlite reflective strips, 9920, 3M Company
Ltd. Auckland, New Zealand) is 15 cm long with two reflective areas, each 25x50mm
at each end and a centre part covered with black paint (figure 9.). The black centre
part measured 100x50 mm.
The dimensions of the strip, together with the two reflective indicator areas made it
possible for the CSD to recognize the strips.
figure 9. Schematic representation of an Oestrus detection strip
Strips were fixed to the sacrococcygeal region of the cow in longitudinal orientation
over the spine. Glue (ADOS F3, CRC Industries New Zealand Ltd. Auckland, New
Zealand) was used to attach the strips to the hair and skin of the cow. Because of the
high degree of moulting seen on the animals, the region was clipped and cleaned
with a dry cloth before applying the glue. Glue was also applied on the strip for
optimal adherence. Glue was allowed to cure for several minutes before the strip was
attached to the cow.
Strip maintenance took place one to two times a week, depending on the number of
cows on heat. In the first weeks new strips were applied twice a week due to the
large amount of animals coming on heat daily. In the last two weeks maintenance
was done only once a week since the number of cows coming on heat rarely
exceeded 5 cows a day.
Damaged, dirty or loose strips were replaced and new strips applied to all cows with
strips missing due to mounting activity or whatever cause. One person stood near the
entrance of the rotary platform to inspect the strips. Unsuitable strips were removed
and the area was provided with new glue. A second person was present near the exit
to place the strips, allowing the glue to cure as long as possible before attaching the
strip.
Results
At the time of writing, results are not yet calculated so actual figures are not
available. However, the author did notice that strip loss rate appeared to be higher
than the 40% found in previous trials (Alawneh, Thesis). Also, only few strips were
seen with paint missing and the strips that had paint rubbed off, showed a
percentage generally lower than 10%.
___________________________________________________________ 34
P.A. van Iren
October 2006 – January 2007
The system appeared to pick up a lot of false positives, meaning that a lot of the
cows that are were selected as in oestrus according to the CSD, were not selected
by the farmer. A high number of false positives observed were associated with loss of
strips in animals not selected in oestrus by the farmer and an apparent failure of the
CSD to recognize strips on cows.
In addition to the false positives, often cows that were selected as on heat by the
farmer were not picked by the CSD. In most cases these animals had apparently
normal, non-rubbed, strips while having been seen mounted several times and
having over 50% of their tail paint missing.
Sunlight seemed to have a major influence on CSD functioning. During sunrise when
the sunlight shone directly into the shed, CSD performance was particularly poor.
During a timeframe of several minutes, every cow came up as on heat. This was
regardless of whether a strip was present or not, since the system was not able to
detect the presence of a strip.
Another problem that occurred is that animals were not always allocated to the
correct bail of the milking platform, thereby mixing up cow identification and images
taken by the camera, thus coming up with wrong animals being matched with
information on strips missing or rubbed.
Discussion
Results found in this trial, although not analysed, are inconsistent with the results of
earlier trials. CSD performance was poorer, possibly due to a number of causes. Also
the integration of oestrus detection and electronic identification is not perfected at the
time of writing.
Inspection of the trial site with J. Alawneh revealed a number of settings were not
implemented in exactly equal to the optimal settings as found and reported from his
previous research.
His observation was that the high strip loss together with the low amount of rubbed
strips can be explained by the positioning of the strips, the process of application and
the manufacturing of the ODS. Whereas strips were located cranially to the tail base
in a longitudinal orientation, the optimal position would have been more cranial in the
lumbo-sacral area. The position as used in this trial will increase a sliding activity that
would tend to remove strips rather than an impact of the brisket of the mounting cow,
causing paint to rub off. The sliding activity would mostly increase the number of
strips rolled off the spine when a mounting cow dismounts the oestrous animal.
Clipping the area for the ODS before application decreases adhesion of ODS to the
skin and hair by disturbing the skin secretions and the coat of the cow. It would have
been better to wipe the area with a damp cloth moistened with alcohol to remove
excess hair and debris before applying the glue.
In this trial a spray paint applicator was used to paint the ODS instead of brush
application as was used before. Possibly this causes a better adherence between the
strip and the paint. A better adherence would make it less likely that paint will be
rubbed off during mounting activities, as was seen in this trial.
The focus of the spotlights only partly reached the ODS while the other part of the
light reached a pipe of the milking parlour mounted above the cows, projecting a
shadow over the cows back where the CSD was attempting to capture an image.
___________________________________________________________ 35
P.A. van Iren
October 2006 – January 2007
Also the spotlights were not shining exactly parallel to the camera lens. Since the
strips are retroreflective, meaning reflection of light is back towards the source of the
light, this set up will decrease the amount of reflection reaching the camera, thereby
contributing to the high number of strips not being recognized by the system.
The bracket that supported the camera in the trial herd also needed to be mounted in
a way that prevents movement or vibration that altered the position from where the
image was being captured. In this trial, movement of the camera was possible to a
slight degree that was possibly still too much.
From a check of the images obtained, ideally the camera should have been mounted
200 mm closer to the cows and 200 mm caudally over the cows to increase the
frame of view on the cows back and thereby insure that all strips were fully visible
within this frame.
Finally, the author thinks the fact that not enough people with experience in CSDoestrus detection were directly involved in this trial has contributed to the poorer
results compared to earlier trials. Although, due to circumstances, earlier involvement
of experts was not possible, this could have made rectification of some of the
apparently crucial faults in the set up possible during the trial, thereby improving the
systems function.
___________________________________________________________ 36
P.A. van Iren
October 2006 – January 2007
Acknowledgements
I would like to thank Professor Williamson for his guidance and support during the
research internship that ended in this report. I am also grateful to Dr. Vos for his help
with finishing this report after my return to the Netherlands. Jan van den Broek and
Nicolas Lopez-Villalobos have been very helpful with the statistical analysis.
I greatly enjoyed the practical help of Kim Dowson during the trial and appreciated
the comments of John Alawneh on the entire system in our trial setting at the
Bunnythorpe site. I’m grateful to Steve and Laura Barr for their patience in the milking
shed throughout the entire trial. The people of Edit iD have been of great support
during my entire work at the Bunnythorpe site.
Furthermore I have greatly appreciated all the things the Lewis family has done to
make me feel at home and help me get around Palmerston North. They treated me
as part of their family and supported me throughout my entire stay in New Zealand.
Most of all I would like to thank my parents, Frank and Tine for supporting me in so
many ways throughout my entire life, but especially during my stay in New Zealand.
They made me confident enough to face the adventure but maintained a safe haven
to return to.
___________________________________________________________ 37
P.A. van Iren
October 2006 – January 2007
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October 2006 – January 2007