GENETIC VARIABILITY AND CORRELATION OF YIELD AND
YIELD RELATED CHARACTERS OF SOME POTATO (Solanum
tuberosum L.) VARIETIES FROM ETHIOPIA
.
M.Sc. THESIS
ABRAHAM LAMBORO
JANUARY 2013
HARAMAYA UNIVERSITY
Genetic Variability and Correlation of Yield and Yield Related Characters
of Some Potato (Solanum tuberosum L.) Varieties from Ethiopia
A Thesis Submitted to the College of Natural and Computational Sciences,
Department of Biology
Haramaya University
In Partial Fulfillment of the Requirements for the Degree of Master Of
Science In Genetics
By
Abraham Lamboro
January 2013
Haramaya University
APPROVAL SHEET
School of Graduate Studies
Haramaya University
As Thesis Research advisor, we here by certify that we have read and evaluated this thesis
prepared, under our guidance, by Abraham Lamboro, entitled Genetic Variability and
Correlation of Yield and Yield Related Characters of Some Potato (Solanum tuberosum
L.) Varieties from Ethiopia. We recommend that it be submitted as fulfilling the Thesis
requirement for the degree of M.Sc in Genetics.
Yohannes Petros(PhD)
______________________
_______________
Major Advisor
Signature
Mebeaselassie Andargie(PhD)
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Co-advisor
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Date
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As member of the Board of Examiners of the M.Sc Thesis Open Defense Examination, We
certify that we have read, evaluated the Thesis prepared by Abraham Lamboro and examined
the candidate. We recommended that the Thesis be accepted as fulfilling the Thesis
requirement for the Degree of Master of Science in Genetics.
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Internal Examiner
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ii
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DEDICATION
I dedicated this work to my Father Lamboro Lire and my Mother Workinesh Doilaso for
their love, dedicated parenting and prayers for my success in life and academic career.
iii
STATEMENT OF THE AUTHOR
First, I declare that this thesis is the result of my own work and that all sources or materials
used for this thesis have been duly acknowledged. This thesis is submitted in partial
fulfillment of the requirements for a M.Sc. degree at Haramaya University and to be made
available at the University’s Library under the rules of the Library. I confidently declare that
this thesis has not been submitted to any other institutions anywhere for the award of any
academic degree, diploma, or certificate. Brief quotations from this thesis are allowable
without special permission, provided that accurate acknowledgement of source is made.
Requests for permission for extended quotation from or reproduction of this manuscript in
whole or in part may be granted by Dean of the School of Graduate Studies when in his or her
judgment the proposed use of the material is in the interests of scholarship. In all other
instances, however, permission must be obtained from the author.
Name: Abraham Lamboro
Signature: ____________________
Place: Haramaya University
Date of Submission: January 2013
iv
BIOGRAPHICAL SKETCH
Abraham Lamboro was born on June 17, 1982 in Hadiya Zone of Southern Nations
Nationalities and Peoples Region. He attended his elementary school at Wasgebeta Primary
and Junior secondary school and his secondary school at Wachemo Preparatory and
Comprehensive High School. He joined Haramaya University in 2003/2004 and graduated
with B.ED degree in Biology on July 8, 2006. He then worked for four years in Southern
Nations Nationalities and Peoples Region Education Bureau, Homecho General High School
as a biology teacher until he joined Haramaya University for postgraduate study in October
2010.
v
ACKNOWLEDGEMENTS
I would like to express my most sincere appreciation and gratitude to my advisors, Dr.
Yohannes Petros and Dr.Mebeaselassie Andargie, for tireless and able supervision, support,
encouragements, constructive comments, suggestions and unreserved guidance throughout the
course of the study. Both have worked hard to keep me on the right track and for the
successful accomplishment of the study.
I would like to express my sincere appreciation to Haramaya University Agricultural Research
Center and Holleta Agricultural Research Center for providing potato genotypes used in the
present study.
I would like also to thank Areka Agricultural Research Center for allowing me a plot of land
to conduct the field experiment. I would also like to thank Firehun Libu for provision of his
personal laptop computer for writing my thesis.
I, certainly, must acknowledge my parents for their care, support, help and encouragement
during my high school education and undergraduate study that paved the way for today's
success.
I would like also to acknowledge Gibe Woreda Education Office for paying salary during my
study leave and Department of Biology of Haramaya University for accepting and train me as
a postgraduate student.
Lastly, the following individuals deserve particular mention: Melese Lire, Temesgen Degele,
Solomon Lamboro, Libu Megebo, Belaynesh Lire, Deselech Tuloro and Degefe Tumiso, for
their encouragement, support and understanding and nice friendship.
Above all, I thank and praise the Almighty God, Who offered me this chance.
vi
LIST OF ACRONYMS
ANOVA
Analysis of Variance
CSA
Central Statistical Agency
DAP
Diammonium Phosphate
FAO
Food and Agricultural Organization
GA
Genetic Advance
GCV
Genetic coefficient of Variation
P.C
Path Coefficient
PCV
Phenotypic Coefficient of Variation
SNNPRFEDB
Southern Nations Nationalities and Peoples Region, Finance and
Economic Development Bureau
SNNPR
Southern Nations Nationalities and Peoples Region
vii
TABLE OF CONTENT
page
STATEMENT OF THE AUTHOR
iv
BIOGRAPHICAL SKETCH
v
ACKNOWLEDGEMENTS
vi
LIST OF ACRONYMS
vii
TABLE OF CONTENT
viii
LIST OF TABLES
x
ABSTRACT
xi
1. INTRODUCTION
1
2. LITERATURE REVIEW
4
2.1. Economic Importance and Production of Potato
4
2.2. Botany and Developmental stages of Potato
5
2.3. Genetic Variability, Heritability and Genetic Advance in Potato
2.3.1. Genetic variability
2.3.2. Heritability
2.3.3. Genetic advances
7
7
9
11
2.4. Association of Characters
2.4.1. Correlation co-efficient
12
12
3. MATERIALS AND METHODS
18
3.1. Description of the Experimental Site
18
3.2. Experimental Materials
18
3.3. Experimental Design and Crop Management
19
3.4. Data Recorded
20
3.5. Statistical Analysis
3.5.1. Analysis of variance
3.5.2. Analysis of genetic parameters
3.3.3. Analysis of correlation coefficient(r)
3.3.4. Path-coefficient analysis
22
22
22
24
25
4. RESULTS AND DISCUSSION
26
4.1. Minimum, maximum and mean values
26
viii
TABLE OF CONTENT(CONTINUED)
4.1.1. Analysis of variance
4.1.2. Estimate of Genetic Parameters
4.1.3. Genotypic and phenotypic coefficients of variation
4.1.4. Broad sense heritability
4.1.5. Genetic advance
4.1.6 . Correlation coefficients
4.1.7. Path coefficients analysis
4.1.7.1. Phenotypic direct and indirect effects of characters on tuber yield
4.1.7.2. Genotypic direct and indirect effects of characters on tuber yield
27
30
30
32
33
34
37
37
41
5. SUMMARY, CONCLUSION AND RECOMMENDATION
43
5. 1. Summary
43
5.2. Conclusions
44
5.3 . Recommendation
44
6. REFERENCES
45
7. APPENDICES
55
ix
LIST OF TABLES
Table
Page
1. Potato varieties that were used in the study and their sources.............................................. 19
2.Analysis of Variance (ANOVA) for potato varieties ............................................................ 22
3. Potato varieties exhibiting extreme values for the 12 characters investigated; their means
and standard errors.................................................................................................................... 27
4. Analysis of variance for 12 characters of 18 potato varieties grown at Hosanna, 2012. ..... 29
5. Estimates of components of variance, heritability (in the broad sense) and genetic advance
as percent of mean for 12 characters of potato varieties tested at Hossana, 2012.................... 31
6. Phenotypic (above diagonal) and genotypic (below diagonal) correlation coefficient among
potato traits. .............................................................................................................................. 35
7. Path coefficient analysis showing direct (bold) and indirect influence (off diagonal) of 11
characters on tuber yield of potato at phenotypic level tested at Hossana. .............................. 40
8. Path coefficient analysis showing direct (bold) and indirect influence (off diagonal) of 11
characters on tuber yield of potato at genotypic level tested at Hossana. ................................ 42
x
Genetic Variability and Correlation of Yield and Yield Related Characters of Some
Potato (Solanum tuberosum L.) Varieties from Ethiopia
ABSTRACT
This research was conducted to determine genetic variability and association of yield and
yield related characters of some potato (Solanum tuberosum L.) varieties using correlations
and path coefficient analysis. The experimental design was a Randomized Complete Block
Design with three replications in 2012 growing seasons in Hossana, Ethiopia. Twelve
agronomic traits were used to determine genetic variability of potato varieties. Analysis of
variance revealed the presence of significant differences (p<0.01) among all varieties for all
observed traits. Genotypic and phenotypic coefficients of variation were higher than the other
traits for biological yield, tubers per plant, tuber yield and plant height. The characters with
high GCV indicate high potential for effective selection. The phenotypic coefficients of
variation (PCV) were higher than corresponding genotypic coefficients of variation (GCV) for
all characters denoting environmental factors influencing their expression. Days to maturity,
plant height, days to flowering, tubers per plant, biological yield, tuber yield and stems per
plant were found to be the most heritable traits studied in the potato varieties. In this study,
relatively higher heritability associated with higher predicted genetic advance was observed
for tubers per plant, biological yield, and medium tuber percentage. These traits therefore,
deserve greater attention in future breeding programs for developing better potato varieties.
High positive significant correlation was found between tuber yield and biological yield, plant
height and tuber yield, stems per plant and tuber per plant. Therefore, it is possible suggest
emphasis should be given to those positively correlated traits. The genotypic correlation
coefficients were higher than the corresponding phenotypic correlation coefficients for most
of the characters indicating the inherent association among the characters. Path analysis of
tuber yield and its components shows that stems per plant, biological yield and harvest index
exerted positive highest direct influence on tuber yield.
Key words: Potato (Solanum tuberosum L.), genetic variability, correlation coefficients, path
analysis,Heritability
xi
1. INTRODUCTION
Potato (Solanum tuberosum L.) is a member of the family Solanaceae. It is one of the most
important food crops in Ethiopia as well as many countries of the world. It produces more
calories and protein per unit land area with minimum time and water than most of the major
food crops (Upadhya, 1995). It is clonally propagated, highly heterozygous, autotetraploid,
and also a world leading vegetable crop that furnishes appreciable amount of vitamin B and
vitamin C as well as some minerals (Thompson and Kelly, 1957).
Potato is very low in fat, with just 5% of the fat content of wheat and the calories of bread.
Boiled potato has more protein than maize and nearly twice the calcium (FAO, 2008).
Potato has originated some 8,000 years ago in the high Andes of South America and was
cultivated in the vicinity of lake Titicaca near the present boarder of Peru and Bolivia
(Horton,1987, cited in Tsegaw, 2006) where a staggering 5,500 cultivated varieties have been
developed by generations of farmers. Taken by the Spanish to Europe in the 16th century, the
tuber quickly adapted to northern growing conditions and soon became a staple food at a time
of rapid population growth. From Europe, it spread further across the globe. Today potatoes
are grown on an estimated 180,000 sq km of farmland (FAO, 2006). It was introduced to
Ethiopia in 1858 by the German botanist, Schimper (Tsegaw, 2006).
Its area and production are increasing day by day. In declaring 2008, the International Year of
Potato, the UN General Assembly seeks to focus world attention to the role of potato in
defeating hunger and poverty (Hossain et al., 2008).
Potato is regarded as a high-potential food security crop because of its ability to provide a
high yield of high- quality product per unit input with a shorter crop cycle (mostly less than
120 days) than the major cereal crops like maize. Recently, the price of cereals has increased
worldwide and in Ethiopia the price subsequently stabilized at high level, whereas the price of
1
root and tuber crops remained relatively low during the entire food crisis. This shows that
there is room for added value in the chain of tuber crops (FAO, 2008).
Ethiopia is known to have a suitable edaphic and climatic conditions for the production of
high quality seed potatoes. About 70% of the available agricultural land is located at an
altitude of 1800-2500m above sea level and receives an annual rainfall of more than 600mm,
which is suitable for potato production (Tsegaw, 2003).
Potato production in Ethiopia covers an area of about 1600, 000 ha (Ferdu et al., 2009). Potato
average yield 9 tones/ha in Ethiopia is much lower than the world average yield 15 tones /ha
(Ferdu et al., 2009).
The phenotypic expression and heritability of yield and other quantitative traits vary due to
genotypic differences, environmental influences and genotype by environment interactions
(Bradshaw, 1965; Becker and Leon, 1988; Crossa et al., 1990).
For a successful breeding program, genetic diversity and variability play a vital role. Genetic
diversity in a population is a prerequisite for an effective plant-breeding program. Genetic
divergence is a useful tool for an efficient choice of parents for hybridization to develop high
yielding potential cultivars. The importance of genetic divergence in the improvement of crop
has been stressed in both self and cross-pollinated crops (Gaur et al., 1978). Evaluation of
genetic divergence is important to know the source of genes for a particular trait within the
available germplasm (Tomooka, 1991).
It is also useful for making a comparative study of a few characters to select the desirable ones
from different genotypes. Study of correlation between different quantitative characters
provides an idea of association that could be effectively utilized in selecting a better plant
type in potato breeding program(Engida et al., 2007).
2
High yield with good quality is the most important objective practiced for its improvement in
potato breeding. Generally, a path coefficient analysis is needed to clarify relationship that
exists between characteristics, because correlation coefficients describe relationships in a
simple manner. Path coefficient analysis shows the extent of direct and indirect effects of the
causal components on the response component. In most studies involving path analysis,
researchers considered the predictor character as first-order variables to analyze their effects
over dependent or response variable such as yield (Tuncturk and Ciftci, 2005).
The current area cropped with potato (about 0.16 Mha) is small and the average yield (less
than10 Mg ha−1) is far below the potential. The low acreage and yield are attributed to many
factors, but lack of high-quality seed potatoes is a major factor (Lemaga et al. 1994; Endale et
al. 2008 ; Gildemacher et al. 2009). Therefore, the present study was undertaken to determine
the characters that contribute to yield in potato. Hence, this research was carried out with the
following objectives in mind.
The general objective was to determine genetic variability and association of yield and yield
related characters of some Potato (Solanum tuberosum L.) varieties from Ethiopia.
While the specific objectives were:
1. To determine the degree of variability, heritability and genetic advance of some agronomic
characters of potato.
2. To evaluate tuber yield components and their interrelationships with each other as well as
their association with yield using path analysis.
3
2. LITERATURE REVIEW
2.1. Economic Importance and Production of Potato
Potato (Solanum tuberosum) is one of the most economically important annual vegetable
crops of Solanaceae family. It is high yielding, having a high nutritive value and gives high
returns to farmers (Humera and Iqbal, 2010). Potato is a crop of worldwide importance. It
supplies at least 12 essential vitamins as well as minerals, proteins, carbohydrates and iron
(Gray and Hughes, 1978; Thornton and Sieczka, 1980). Potato tubers give an exceptionally
high yield per acre, many times more than that of any grain crop (Burton, 1969) and are used
in a wide variety of dishes, processed, livestock feed and industrial uses (Feustel, 1987). It is
the fourth most cultivated food crop exceeded only by wheat, rice and maize in world
production for human consumption (Ross, 1986).
The cultivated potato of world commerce, Solanum tuberosum L., is a primary food crop
grown and consumed worldwide, forming a basic food and source of primary income for
many societies. Indigenous primitive cultivated (landrace) and wild (Solanum petota) potatoes
form the germplasm base used for breeding advanced potato varieties (Spooner et al., 2010).
Potato in our country is also a very essential food and cash crop, favorite choice especially by
the mid-to-highlanders. It is mainly consumed as boiled, salad, stews and recently potato chips
and crisps are getting attention from roadside vendors who fries and sell it on the spot (Ferdu
et al., 2009).
Among African countries, Ethiopia has possibly the greatest potential for potato production:
70 percent of its arable land, mainly in highland areas above 1500 m, is believed suitable for
potato. Since the highlands are also home to almost 90 percent of Ethiopia's population, potato
could play a key role in ensuring national food security. At present, potato is still widely
regarded as a secondary crop, and annual per capita consumption is estimated at about 5 kg.
However, potato cultivation is expanding steadily: FAO estimates that production has
increased from 280 000 tones in 1993 to around 525 000 tones in 2007 (FAO, 2008).
4
The Southern Ethiopia is located in the Southern Nations, Nationalities and Peoples Regional
State (SNNPRs) and partly in the Oromiya region. The major potato producing zones in the
SNNPRs are Gurage, Gamo Gofa, Hadiya, Wolyta,Kambata, Siltie and Sidama and West Arsi
zone in Oromiya region. More than 30% of the total number of potato farmers are located in
this area (CSA, 2008\2009).
2.2. Botany and Developmental stages of Potato
The name “potato” is believed to have originated from the Taínos Indian name, “batatas”.
Potato is one of about 2,300 species in the family Solanaceae. This family includes about 90
genera, the largest of which is the genus Solanum, including about 1,500 species. About 100
species of Solanum are tuber bearing and thus commonly referred to as “potato.” The
Solanaceae include such plants as tobacco, tomato, eggplant, chili pepper, horse nettle,
bittersweet nightshade, ground cherry and petunia. Botanically, advanced potato cultivars,
today grown in North America, Europe, and other countries are classified as Solanum
tuberosum L. (William et al., 2010).
All of the species are distributed entirely in the Americas from the southwestern United States
south to Uruguay, Argentina and Chile. Chromosome numbers vary from diploid (2n = 2x =
24), triploid (2n = 3x = 36), tetraploid (2n = 4x = 48), pentaploid (2n = 5x = 60) to hexaploid
(2n = 6x = 72). The cultivated potato has all these ploidy levels except hexaploid and
originated along the high Andes of southern Peru. Landrace (native cultivar) populations
today grow throughout the Andes from Venezuela to northern Argentina and also near sea
level in southern Chile. Despite having originated in southern Peru, modern cultivars grown
worldwide come from the Chilean landraces (William et al., 2010).
The potato plant has a short life span ranging from 80 to 150 days from planting to maturity,
with differences existing between varieties. Its developmental stages are often described in
terms of tuberization and tuber development. The life cycle of a potato tuber is characterized
by initiation and growth followed by a period of dormancy and finally sprouting resulting in
5
the next (vegetative) generation (Spooner et al., 2005).The vegetative growth stages are
described as follows:
a. Sprouting tuber growth stage one is the onset of sprout growth that follows dormancy
termination is accompanied by substantial increases in cell metabolism; sprouts appear from
the eyes of the primary tuber.
b. Vegetative growth stage two is plant establishment in which all vegetative parts of the
plants (leaves, branches, roots and stolons) are formed. Stages one and two last from 30 to 70
days depending on soil temperature and other environmental factors, the physiological age of
the tubers and the characteristics of particular cultivars.
c. Tuber initiation growth stage three is approximately 30-60 days after the seed tuber is
planted, tuber formation begins. Tubers are derived from lateral underground buds developing
at the base of the main stem that when kept underground develop into stolons. When
conditions are favorable for tuber initiation, the elongation of the stolon stops and cells located
in the pith and the cortex of the apical region of the stolon first enlarge and then later divide
longitudinally. The combination of these processes results in the swelling of the sub apical
part of the stolon (Spooner et al., 2005).
d. Developing tuber growth stage four. During enlargement tubers become the largest sink of
the potato plant storing massive amounts of carbohydrates (mainly starch) and also significant
amounts of protein. Furthermore, tubers decrease their general metabolic activity and as such
behave as typical storage sinks.
e. Mature tuber growth stage five. Potato tubers are harvested from 90 to 160 days after
planting and this may vary with cultivars, production area and marketing conditions. Starch
typically represents 20% of the fresh weight of mature tuber. After potato vines die back, the
skin of tuber thickens and hardens which provides greater protection to tubers during harvest
and blocks entry of pathogens to the tuber (Spooner et al., 2005).
6
2.3. Genetic Variability, Heritability and Genetic Advance in Potato
2.3.1. Genetic variability
The amount of variability that exists in the germplasm collections of any crop is of the utmost
importance towards breeding for better varieties. Particularly, genetic variability for a given
character is a basic prerequisite for its improvement by systematic breeding (Engida et al.,
2007).
The breeding methodology to be adopted for the improvement of a crop mainly depends upon
the amount of genetic variability present in the crop. It is of immense importance that the
hybrids are obtained only from desirable parental combinations. Therefore, it is very
important to select the desirable parents which could transmit high yield and other economic
traits to their progeny (Haydar et al., 2009b).
Varieties of asexually propagated crops consist of large assemblages of genetically identical
plants, and there are only two ways of introducing new and improved varieties: by sexual
reproduction and by the isolation of somatic mutations. The latter method has often been used
successfully with potato have occasionally arisen in this way. When sexual reproduction is
used, hybrids are produced on a large scale between existing varieties; the small number that
have useful arrays of characters are propagated vegetatively until sufficient numbers can be
planted to allow agronomic evaluation (Haydar et al., 2009b).
Information on the nature and magnitude of variability present in a population owing to
genetic and non genetic causes is an important prerequisite for initiating any systematic
breeding program. As yield increase is the main objective of a breeder, so it is important to
know the relationships between various characters that have direct and indirect effect on yield.
The knowledge of association of quantitative characters, especially the yield and its attributes
provide an idea of association that could be effectively utilized in selecting the desired
characters in segregating population ( Ara et al., 2009).
7
The composition of the phenotype (the observable properties of an organism), is simply
expressed as the outcome of three major sources of variation : the genotype, the environment
and genotype by environment interaction which includes all factors external to the plant that
affect development and growth, and interaction of all kinds. Lee (2006) described genetic
variance as a measure of the extent of genetic differences among the germplasm units
(individual or families). Sattar et al.(2007) reported high genotypic coefficients of variation
for number of tubers per plant, yield per plant and average weight of a tuber. The highest
genotypic and phenotypic coefficients of variations were observed for yield of tubers per plant
and number of tubers per plant (Sattar et al., 2007). Mondal (2003) obtained higher genotypic
and phenotypic coefficients of variation for average tuber weight/plant tuber yield/plant and
tubers number/plant in potato.
Studies within-population genetic structures are essential to the understanding of micro
evolutionary processes in plant populations. Spatial genetic structure within plant populations
is influenced by various factors such as gene flow, clonal pattern, and micro environmental
selection (Vekemans and Hardy, 2004). Gene flow, mediated by pollen and seed dispersal, is a
key factor and also it determines the scale of local adaptation and the role of population
structure in the evolutionary process. With spatially limited gene flow, populations should be
more inbred and more likely to differentiate in response to local selective force or genetic drift.
In addition to gene flow, within-population genetic structure may also be influenced by the
balance between sexual and vegetative reproduction (clonal growth). Clonal multiplication has
been hypothesized to result in a decrease in genetic variation and clonal diversity. However,
several reviews have demonstrated that most clonal plants have high genetic diversity, similar
to nonclonal plants and that a low rate of repeated sexually produced seedling recruitment
may be sufficient to maintain genetic diversity (Kang and Chung, 2000).
8
2.3.2. Heritability
Heritability is specific to a particular population in a particular environment, but the extent of
dependence on environment is also a function of the genes involved. Individuals with the
same genotype can exhibit different phenotypes through a mechanism called phenotypic
plasticity, which makes their heritability difficult to measure in some cases. Recent insights in
molecular biology have identified changes in transcriptional activity of individual genes
associated with environmental changes. But, there are a large number of genes whose
transcription is not affected by the environment (Visscher et al., 2008).
Heritability estimates along with genetic gain are considered to be more useful in predicting
the outcome of selecting the best individuals (Johnson et al., 1955). However, it may be noted
that the heritability value indicates the relative effectiveness of selection based on phenotypic
expression of a character but, genetic advance is more useful in predicting the actual value of
the selection as shown by Johnson et al. (1955).
Theoretically, heritability can range from one where all variation is due to genetic factor, to
zero where all the variations results from the environment. Actual heritability value will fall
somewhere between these extreme values. It is very difficult to determine the presence,
amount or types of phenotypic expressions strongly influenced by the environment (Welsh,
1990, cited in Basazen, 2006). A large percentage of heritability for a character is regarded as
highly heritable whereas if it is smaller, some environmental agency is considered responsible
for phenotypic manifestation of the character (Dabholkar, 1992).
Lush (1940) defined heritability in “Broad Sense” as the ratio between the genotypic variance
as a whole and that due to phenotype. It expresses the extent to which individual phenotypes
are determined by the genotypes .But this idea does not give a clear picture of transmissibility
of variation from one generation to the next, as the genotypic variation included fixable
additive effects and non- fixable dominance and epistatic gene effects, whose utility in plant
improvement programme was limited. Therefore, he further defined heritability in the “narrow
sense” as the ratio of additive genetic variance to the phenotypic variance (Lush, 1949).
9
Similarly (Falconer, 1989), further divided heritability into broad sense and narrow sense,
depending whether it refers to the genotypic value or breeding value. The ratio of additive
variance to phenotypic variance expresses the extent to which phenotypes are determined by
the genes transmitted from the parents. The ratio also expresses the magnitude of genotypic
variance in the population, which is mainly responsible for changing the genetic composition
of a population through selection (Falconer, 1989).
Moreover, heritability serves as a guide to the reliability of phenotypic variability in the
selection programme and hence determines its success (Hamdi, 1992). However, Johnson et al.
(1955) stated that heritability estimates together with genetic advance are more important than
heritability alone to predict the resulting effect of selecting the best individuals. Main
quantitative traits associated with high heritability and high genetic advance have great
importance in selection of genotype in early generations (Memon et al., 2005). Heritability
values can be used as a measuring scale to determine genetic relationships between parents
and progeny (Memon et al., 2007). Better heritability values recorded points to the possibility
of improvement in the parameters so that attention may be focused on important traits while
synthesizing genotypes (Ahmed et al., 2007). Yield is a polygenic trait and attributed to its
associated traits therefore for higher yield the total genetic expression of all its component
genes is needed. However their expression is also influenced by environmental factors (Sial et
al., 2003). Heritability and genetic advance enables the breeders to use the best genetic stock
for improving the crop (Mangi et al., 2008). The success of any breeding programme depends
upon the amount of genetic diversity existing in the germplasm and it is a prerequisite to have
a good knowledge of heritability and genetic advance present in different yield associated
parameters (Waqar-ul Haq et al., 2008). Rambaugh et al. (1984) described that heritability
study must be conducted in favorable environments rather than unfavorable environments;
genetic parameters such as mean, genotypic variance, broad sense heritability and genetic
advance are decreased under unfavorable environments.
Heritability plays a predictive role in breeding, expressing the reliability of phenotypes as a
guide to its breeding value (Tazeen et al., 2009). It is understood that only the phenotypic
value can be measured directly while breeding values of individuals are derived from the
10
phenotypic value by appropriate analyses. It is breeding value, which determines how much of
the phenotype would be passed to the next generation (Rehman and Alam, 1994). Heritability
indicates the degree of connection to between phenotypic value and breeding value (Falconer,
1989). The efficiency of the process of selection depends upon the kind and magnitude of
variation. There is a direct relationship between heritability and response to selection, which is
referred to as genetic progress (Tazeen et al., 2009).
Sattar et al.(2007) obtained high heritability coupled with high genetic advance as percent of
mean for number of tubers per plant, yield per plant and average weight of a tuber suggesting
selection for these traits would give good response. Haydar et al.(2009a) reported high
heritability (in a broad sense) as well as high genetic advance as percentage of mean for plant
height, branches number, tubers number and tuber yield indicated that these traits could be
improved through selection and were governed to a great extent by additive gene. Panse (1999)
also indicated that tuber yield, number of stems, number of leaves, maturity, shoot fresh
weight, number of tubers and average tuber yield had high genotypic coefficient of variation,
high heritability and high genetic advance irrespective of the environment.
2.3.3. Genetic advances
Genetic advance is the measure of the expected genetic progress that would result from
selecting the best performing genotypes for a character being evaluated (Allard, 1999).
Genetic advance is also of considerable importance because it indicates the magnitude of the
expected genetic gain from one cycle of selection (Hamdi et al., 2003). Selection which is the
retention of the desired genotypes and elimination of the undesirable ones is a major and
important process in breeding for improvement of one or more plant attributes. In a population
under selection for a quantitative character, genotypic frequencies and hence gene frequencies
are altered and these changes are further modified by the mating systems that may be
employed to advance the selected individuals to the next generation(s) (Chopra, 2000). Thus,
the utilization of any criterion for selection as linked with high genetic coefficient of variation
11
and estimates of heritability as the magnitudes of heritability and other genetic parameters for
a character would vary from location to location (Ramachandran et al., 1982).
High value of heritability and predicted genetic advance clarifies that the selection among
genotypes would be effective for yield and yield components (Ghandorah and Shawaf, 1993).
The studies conducted by various researchers have shown that high heritability alone is not
enough for selection in advance generations; it must be accompanied with substantial amount
of genetic advance (Memon et al., 2007; Mangi et al., 2008). However, if a character or trait is
controlled by non additive gene action, it gives high heritability but low genetic advance,
while the character ruled by additive gene action, heritability and genetic advance both would
be high (Ahmed et al., 2007).
Haydar et al. (2009b) reported high estimates of heritability and genetic gain for plant height,
number of branches, tubers number and yield indicated that these traits are largely controlled
by additive gene action and that strong selection for them would be effective. Haydar (2007)
recorded comparatively high heritability in potato for fresh weight and tuber weight/plant. Ara
et al.(2009) reported high heritability and genetic gain (GA %) for fresh weight/plant, number
of main stem and tuber fresh weight; indicating these characters are largely controlled by
additive gene action and that straight selection for them would be effective.
2.4. Association of Characters
2.4.1. Correlation co-efficient
Correlation coefficient is a linear association between two variables (Gomez and Gomez,
1984). Knowledge of correlations that exist between important characters may facilitate the
interpretation of the result obtained and provide the basis for planning more efficient program
for the future (Johnson et al., 1955). It is indicated by the correlation coefficient(r) and
measures the degree of association, genetic or non-genetic, between two or more traits
(Hallauer and Miranda, 1998). It measures the mutual association between two variables but
does not indicate the cause and effect relationship of traits contributing directly or indirectly
12
towards economic yield (Shivanna et al., 2007). The value of correlation coefficient, which is
a ratio of the covariance between the two variables and the geometric mean of their variances,
ranges from -1 to +1, the extreme values indicating perfect negative and positive association,
respectively (Gomez and Gomez, 1984).
Sadek et al.(2006) pointed out that estimation of simple correlation between various
agronomic characters may provide good information necessary for crop breeders, when
selection is based on two or more traits simultaneously. Information obtained from correlation
coefficients for characters could also be useful as indicators of the more important ones under
consideration.
Mevlut et al. (2008) stated that correlation analyses are being widely used in many crop
species by plant breeders to understand the nature of complex interrelationships among traits
and to identify the sources of variation in yield. Yield is a complexly inherited trait as its
manifestation is an outcome of intricate interaction of several traits and environment.
Therefore, proper understanding of association of different traits provides more reliable
criterion for selection to achieve the goal of high yield (Muhammad et al., 2001). Yield
components, not only directly affect the yield, but also indirectly by affecting other yield
components in negative or positive ways (Roopa and Ravikumar, 2008). High yield through
yield attributes, as primary interest in crop improvement, requires understanding the
magnitude of correlations among various yield traits (Tadele et al., 2009).Becker (1993)
stated that correlation studies are of interest to plant breeders because traits that are correlated
with the main breeding objectives may be useful for indirect selection. Tadele et al.(2009)
noted that information on the extent and nature of interrelationships among characters help in
formulating efficient scheme of multiple trait selection. Traits under consideration may have
strong correlation or not at all. Grafius (1959) indicated that a positive genetic correlation
between two desirable traits makes the job of the plant breeder easy for improving both traits
simultaneously. On the other hand, a negative correlation between two desirable traits
impedes or makes it impossible to achieve a significant improvement in both traits.
13
Therefore, knowledge of the relationship that exists between tuber yield and other characters
and also interrelationships among various characters is necessary to be able to design
appropriate selection criteria in potato breeding program. According to Grafuis (1959),
increasing total yield would be made easier by selecting for yield components because the
components are more simply inherited than the total yield itself. Thus, studies on correlation
enable the breeder to know the mutual relationship between various characters and determine
the component characters on which selection can be based for yield environment.
Yield is a complex character associated with many interrelated components (Murat and
Vahdettin, 2004). Numerous researchers (Sidhu and Pandita, 1979; Birhman and Kang, 1993;
Amadi, 2005, and Amadi and Ene Obong., 2007) have used simple correlation coefficients to
study the interrelationships between tuber yield and other characters.
Environment plays an important role in correlation. In some cases, environment affects two
traits simultaneously in the same direction or sometimes in different directions. Genetic and
environmental causes of correlation combine together and give phenotypic correlation. The
dual nature of phenotypic correlation makes it clear that the magnitude of genetic correlation
cannot be determined from phenotypic correlation (Usman et al., 2006).
Phenotypic and genotypic correlations have been computed by calculating the appropriate
components of variance. Phenotypic correlation (rp) involves both genetic and environmental
effects. It can be directly observed from measurements of the two characters in a number of
individuals in a population (Hallauer and Miranda, 1998). Genetic correlation is the
association of breeding values (i.e., additive genetic variance) of the two characters (Falconer,
1989). Both measure the extent to which degree the same genes or closely linked genes cause
co-variation in two different characters (Hallauer and Miranda, 1998). Correlation coefficient
provides a measure of the association between characters (Cerna and Beaver, 1990). Johnson
et al. (1955) also reported that higher genotypic correlation than phenotypic correlation
indicated an inherent association between various characters.
14
Galarreta et al. (2006) observed a significant correlation between tuber yield with tuber
number and tuber weight. Er (1984) found that tubers/plant and tuber yield were increased
when big tubers were used in sowing. Gunel et al. (1991) noted highly positive and significant
correlation between tuber yield with big tubers percentage and vegetation period. Yildirim et
al. (1997) observed that both yield components (tuber number and tuber weight) were
associated with tuber yield, but they indicated that tuber numbers were important than tuber
weight. Number of tubers and average tuber weight were positively and significantly
correlated with yield (Lopez et al., 1987, Ozkaynak and Samanchi, 2005, Rasool et al., 2006).
Desai and Jaimini (1997) also reported that tuber yield, number of stem, number of leaves,
maturity, shoot fresh weight, number of tubers and average tuber weight had high genotypic
coefficients of variation, high heritability and high genetic advance irrespective of
environments.
Sattar et al. (2007) reported genotypic and phenotypic correlation of the number of tubers per
plant and weight of tubers per plant were highly significant. Plant vigour, number of
compound leaves per plant and number of tubers per plant, average weight of a tuber and dry
matter content of tuber had high degree of positive association with tuber yield per plant.
Khayatnezhad et al.(2011) also observed stronger positive correlations between tuber yield and
main stems/plant, plant tuber weight, plant height.
Amadi et al.(2008) also found phenotypic correlation coefficients revealed a significant
positive correlation between tuber yield and average tuber weight per plant, number of tuber
per plant, early blight severity, days to tuber initiation, and days to maturity.Murat and
Vahdettin (2005) had reported positive significant relations between tuber yield and plant
height, number of stems per hill, number of tuber per hill, percentage of medium tuber,
percentage of big tuber, dry matter content and starch content. Also they observed negative
and significant relationships between tuber yield and small tuber percentage.
15
2.4.2. Path co-efficient analysis
Although information about the correlation of agronomic and morphological characters with
yields is helpful in the identification of the components of this complex character, yet these do
not provide precise information on the relative importance of direct and indirect influences of
each of the component characters. With increasing number of variables it becomes necessary
to measure the contribution of these variables to the observed correlation and hence partition
the correlation coefficient into components of direct and indirect influence (Guler et al., 2001,
Onder and Babaoglu, 2001). This, in turn, allows separation of the direct effects of one
variable (other variables are kept constant) from indirect effects of other variables, giving a
clearer picture of the individual contributions of each variable to yield (Radovan, 1992).
Assuming yield is a contribution of several characters which are correlated among themselves
and to the yield; path co-efficient analysis was developed by (Wright, 1921). According to
Dewey and Lu (1959) unlike the correlation coefficient which measures the extent of
relationships, path coefficient measures the magnitude of direct and indirect contribution of
the component characters to a complex character and it has been defined as a standardized,
regression coefficient which splits the correlation coefficient into direct and indirect effects.
Mehmet and Telat(2006) recommended that study of direct and indirect effects of yield
components to increase the yield provides the basis for its successful breeding program and
hence the problem of yield decrease can be more effectively tackled on the basis of
performance of yield components and selection for closely related characters.
In order to get a clear picture of the interrelationships between different traits, the direct and
indirect effects of different characters worked out using path coefficient analysis in respect of
the yield (Singh et al., 2004). Since path analysis permits a critical examination of the specific
factor that produces a given correlation, it could be successfully employed in formulating an
effective selection strategy (Kumbhar et al., 1980).
16
Path analysis of tuber yield and its traits indicated that plant height, medium tuber weight and
big tuber weight evolved the highest direct influence. Conversely, main stems/plant had a
positive and low direct effect with an indirect negative effect via tuber weight/plant and
positive effect with average tuber weight and tubers/plant on tuber yield. In addition to, the
indirect effects of plant height, tubers/plant was stronger than its direct effects. These showed
that tuber weight/plant, average tuber weight, tubers/plant were the main characters for tuber
yield (Khayatnezhad et al., 2011).
Ara et al.(2009) and Haydar (2007) reported that main shoot number had highest positive
direct effect followed by fresh weight/plant at 80 days after planting and number of leaves
/plant. Higher values of direct effect of main shoot number on fresh weight/plant after 90 days
after planting were the reflection of significant positive correlation of these characters with
fresh tuber yield were the reflection of significant positive correlation of these characters with
tuber yield per plant; suggesting that while using these characters as a criterion for selection,
other causal characters must be considered simultaneously. Sattar et al.(2007) obtained tuber
per plant, average weight of tuber, number of compound leaves per plant had high positive
direct effect on tuber yield. It was also reported that negative indirect effect for dry matter
content. Amadi et al. (2008) observed tuber per plant, average weight of tuber had high
positive direct effect on tuber yield. Yildirim et al. (1997) stated that average tuber weight,
tubers/plant, tuber weight/plant and plant height had positive and high direct effects on tuber
weight/plant. He also reported that main stems/plant; plant height had positive and high direct
effects on tuber yield. Tuncturk and Ciftci, (2005) reported tuber per hill had the greatest
direct effect on tuber yield while its indirect effects on tuber yield were positive through
number of tubers per hill, average tuber weight, medium tuber percentage, dry matter contents,
but negative through plant height, stems per hill, small tuber percentage and big tuber
percentage.
17
3. MATERIALS AND METHODS
3.1. Description of the Experimental Site
A field experiment was conducted in Southern Nations Nationalities and People’s Regional
State, at Araka Agricultural Research Center, Hossana Experimental Site. It is located at an
altitude of 2200m above sea level and 230km South West of Addis Ababa. It has an average
annual rain fall of about 671mm and annual mean temperature of 180C and has loam soil type
(SNNPRFEDB, 2010).
3.2. Experimental Materials
Sixteen potato varieties, which were released by the regional and national research institutions
at different times and two locally available potato genotypes were used. The institutes that
released the varieties were Haramaya University Research Center, Holeta Agricultural
Research Center and Hadiya Zone Agricultural and Rural Development Office (Table 1).
18
Table 1. Potato varieties that were used in the study and their sources.
SNo
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Variety
Bolbo
Bubu
Gera
Bule
Belete
Gudanie
Menegesha
Wochecha
Awash
Chiro
Marachera
Guassa
Gorobella
Bedassa
Jalanie
Sako
Challa
Zengena
Source
Local
Haramaya
Holeta
“
“
“
“
“
Holeta
Haramaya
Holeta
Holeta
Holeta
Haramaya
Holeta
Local
Holeta
Holeta
3.3. Experimental Design and Crop Management
The experiment was arranged in a randomized complete block design (RCBD) with three
replications. Each variety was planted in 3m × 3m plots maintaining row to row spacing of
75cm and plant to plant in a row spacing of 30cm. Each plot consisted of four rows which
accommodated ten plants per row and thus forty plants per plot. A distance of 1m was
maintained between the plots. The experiment was conducted under rainy season. Agronomic
characters were determined on the means of five randomly selected plants in the middle rows
of each plot. Recommended agronomic practices were followed, fertilizers were applied and
plant protection measures like fencing experimental field from damage of wild animals were
taken when required. Days to emergence, days to flowering and days to maturity were
recorded on plot basis.
19
3.4. Data Recorded
Pre and post harvest observations were taken for the selected sample plants from each plot for
all characters. Data recording for each character were carried out as follows.
Days to emergence (DE): The numbers of days from planting to the emergence of 50% of
plants in each plot were recorded.
Days to flowering (DF): Number of days from planting to when 50% of the plants in a plot
produced flowers on 50% of their buds.
Days to maturity (DM): Number of days from planting to when 90% of the plants in a plot
reached physiological maturity.
Plant height (PH): The height of the plants from the ground level to the tip of the plant were
measured in centimeter and averaged over the sample plants to get the mean plant height in
centimeter.
Stems per plant (SP): The total number of stems that arise from each plant was counted and
averaged over the total sample plants in each plot to get the mean number of stems per plant
for each variety. Only the main stems i.e. those originating from the mother tubers were
counted. The record was taken at full flowering.
Tuber yield (TY) : The total weight of tubers/plant (kg). Tuber from the sample plants in
each plot were weighed and averaged to get tuber yield per plant. The mean tuber yield per
plant in kilogram was used for statistical analysis (to calculate range, coefficient of genotypic
and phenotypic variations, heritability estimates and expected genetic advance in percent).
Tubers per plant (TP): This was obtained by counting the whole tubers produced by all
sample plants in the plot and averaging over the number of sample plants.
Biological yield (BY): The above ground potato plant parts were dried and weighed using a
sensitive balance. The weight of dry plant parts in each plot were averaged to get the mean
weight of each variety in kilogram.
Harvest index (HI): to estimate harvest index average tuber yield was divided by the average
biological yield following (Debouk and Hidalgo, 1986) formula.
20
Harvest Index = Tuber yield(kg)
Biological yield (kg)
Small tuber percentage (STP): The proportion of small size tubers (diameter less than or
equal to 1 ½ inch) per plant were counted and recorded as percent of tubers for each plot
(USDA, 2003). The percentage of small tubers in each plot was used to calculate the different
statistical parameters.
Medium tuber percentage (MTP) : The proportion of medium size tubers (diameter less
1
than 2 2 inch and greater than 1 ½ inch) per plant were counted and changed into percentage
(USDA, 2003).
Big tuber percentage (BTP) :The percentage of big tubers (diameter greater than or equal to
1
2 2 inch) per plant were determined for each plot and used for statistical analysis (USDA,
2003).
21
3.5. Statistical Analysis
3.5.1. Analysis of variance
Data were subjected to analysis of variance following the procedures described by Gomez and
Gomez (1984) using SAS version 9.1.3
Table 2.Analysis of Variance (ANOVA) for potato varieties
__________________________________________________________________________
Source of variation
Df
MS
Em
__________________________________________________________________________
Replication ( r )
r-1
MSr
2 e + g2 r
Genotypes (g)
Error (e)
g-1
MSg
(r-1) (g-1)
Mse
2 e + g2 g
2 e
Total
gr-1
__________________________________________________________________________
Where: r = number of replication, g = number of genotypes, df = degree of freedom, MS =
mean square, MSr =mean square due to replication, Em= expected mean, 2 g =genotypic,
2 e= environmental variance.
3.5.2. Analysis of genetic parameters
Estimation of genetic parameters was used to identify and ascertain the genetic variability
among the genotypes and to determine the extent of environmental effects on various
characters. Components due to genotypic variance (𝜎2g), environmental variance (𝜎2e), and
broad-sense heritability (H2) were calculated by adopting the following formulas suggested by
different authors.
Phenotypic and genotypic variance components were calculated by the methods suggested by
Burton and Devane (1953).
22
Genotypic variance (2g) = Msg-Mse \ r
Phenotypic variance (2p) =
2g +2e
Environmental variance (2e) = Mean square
Where: MSg = mean square due to genotype
Mse = Environmental variance
r = number of replication
According to Singh and Chaudhary (1985), the phenotypic and genotypic coefficients of
variances were expressed by the following formula:
GCV (%) = (2g/X) x100
Where:
GCV
= genotypic coefficient of variation
X
= Mean value of the trait
PCV (%) = (2p /X) x 100
Where: PCV = phenotypic coefficient of variation
Heritability in the broad sense,
Heritability in broad sense was calculated for each trait by using (Allard, 1960) formula.
H2 (%) = (2g /2p) x100
Where:
H = heritability in broad sense
2p = phenotypic variance
2g = genotypic variance
Genetic Advance (GA): Genetic advance as the percent of mean was calculated by dividing
the genetic advance with the mean and multiply it by 100 (Johnson et al., 1955).
GA = H2𝜎pK
Where: h2 = heritability in the broad sense
K = selection differential at 5% intensity of selection, that is 2.06.
σp = the phenotypic standard deviation
GA% (as % of mean) = GA/grand mean
23
3.3.3. Analysis of correlation coefficient(r)
The phenotypic correlation coefficients were calculated by using the formula suggested by
Gomez andGomez (1984) as:
rpxy =
𝐶𝑜𝑣𝑃𝑥𝑦
√𝜎2 𝑝𝑥𝜎2 𝑝𝑦
Where: rpxy = phenotypic correlation coefficient between traits x and y.
Covp xy = Phenotypic covariance between traits x and y
𝜎 2 𝑝𝑥 = Phenotypic variance of trait x
𝜎 2 𝑝𝑦
= Phenotypic variance of trait y
Both genotypic and environmental effects and genotypic correlation, which the inherent
association between two variables, were estimated by the formula of (Al- Jibouri et al., 1958).
rg = Gcovx.y/ √ (2gx. 2gy)
Where: rg = genotypic correlation coefficient
Gcovx.y = genotypic co-variance between variables x and y
2gx = genotypic variance for variable x
2gy = genotypic variance for variable y
Testing correlation for Significance :The significance of the simple linear correlation can be
tested in the following way as described by (Walepole et al., 2002).
t=r
n2
1 r2
Standard error (SE):
with n-2 d.f., where n is the number of observations.
Estimate of error variance was estimated by the method given
by Hallauer and Miranda (1998)
24
SE =
√𝟐(𝑴𝑺𝒆)𝟐
𝒅𝒇𝒆+𝟐
Mse = mean square of error and dfe = error degree of freedom
3.3.4. Path-coefficient analysis
In path coefficient analysis, direct and indirect effects of the independent character for yields
were estimated by applying (Dewey and Lu, 1959) formula.
rij = Pij + ΣrikPkj
Where: rij ═mutual association between the independent character (i) and dependent character
(j) as measured by genotypic correlation coefficients.
Pij = components of direct effects of the independent character (i) on the dependent
character (j) as measured by genotypic co-efficient variation.
ΣrikPkj = summation of components indirect effect of a given independent character (i) on a
given dependent character (j) via all other independent characters (k).
The residual effect (P2R) was estimated as described by Dewey and Lu (1959):
1=P2R + Σpij rij
25
4. RESULTS AND DISCUSSION
4.1. Minimum, maximum and mean values
The minimum, maximum, mean and standard error of the studied 12 traits are presented in
(Table3). Wide ranges were recorded for days to maturity, plant height, days to emergence,
stem per plant, tuber per plant, harvest index, small tuber percentage, medium tuber
percentage and big tuber percentage. Sattar et al.(2007) obtained wide range of variation in
plant height, days to maturity, tuber yield, stem /plant, days to emergence in potato genotypes
in Bangladesh.
The range for days to maturity was from 90 for Sako to118 for Menagesha. Days to flowering
ranged from 50 for Challa, Gorobella, Bule to 65 for Bubu and plant height ranged from
25.6cm for Sako to 74.8cm for Zengena. Similar to the current study Khayatnezhad et
al.(2011) obtained the height of the potato plant ranged from 28.4cm to 71.2cm. Whereas days
to emergence, stems/plant, tubers /plant, biological yield, harvest index were 18-31, 16-35,
5.4- 38.2, 0.09kg - 0.5kg and 16.2-20, respectively.
The tuber percentage showed wide range of variation in which, the proportion of small,
medium and big tuber percentage were varied from 28-91.6%, 6-57.9%, 12-22% , respectively.
Tuber yield /plant ranged from 2.00 kg for sako to 6.083kg for chiro. Maximum tuber yield
was obtained in Chiro, Gorobella, Bubu, Jalanie, Guassa, Bedassa, Belete, Gudanie and
Zengena, respectively had good quality and high yielding varieties in the study area. While
low yield was found for Bolbo, Bule, Marachera, Menagesha, Wochecha and Sako(Appendix
table 1). Range and mean values in this study indicate that the presence of variability among
the tested varieties for most of the traits studied.
26
Table 3. Potato varieties exhibiting extreme values for the 12 characters investigated; their
means and standard errors.
Trait
DE
DF
DM
PH
SP
TY
TP
BY
HI
STP
MTP
BTP
Maximum scoring
genotype
Mean ± SE
Score
Genotype
Score Genotype
Bolbo,Challa,Bule,Bedassa,Zengena
18
31.00 Bubu
21.74±0.42
Challa,Gorobella,Bule
Bubu
50.00
65.00
54.81±0.50
90.00 Sako
118.00 Menagesha 102.87±0.79
25.60 Sako
74.80 Zengena
54.38±1.53
16.00 Belete
35.00 Jalanie
24.53±0.64
2.00 Sako
6.083 Chiro
4.44±0.163
Menagesha
Bolbo
5.40
38.20
18.02±1.00
Sako
Bubu
0.09
0.50
0.25±0.014
Gudanie
Challa
16.2
20.00
17.95±0.061
Chiro
Bolbo
28
91.60
52.79±2.29
Marachera
6
57.90 Jalanie
36.93±1.71
12
Marachera
22.00 Gorobella
19.92±0.19
Minimum scoring genotype
DE = Days to emergence, DF = days to flowering, DM = days to maturity, PH = plant height,
SP = stems per plant, TY= Tuber yield, TP = Tubers per plant, BY = Biological yield, HI =
Harvest index, STP = Small tubers percentage, MTP = Medium tubers percentage, BTP = Big
tubers percentage, SE= standard error
4.1.1. Analysis of variance
Analysis of variance (ANOVA) was carried out following the procedures described by Gomez
and Gomez (1984). The analysis of variance showed that there were highly significant
(p<0.01) differences among the varieties for all the characters (Table 4). This may be
attributed to the existence of large variability among varieties maintained at Areka
Agricultural Research Center, Hossana Experimental Site. Coefficient of variation was low for
all of the agronomic traits studied indicating good precision of the experiment.
In close agreement with this study, Khayatnezhad et al.(2011) reported significant differences
in plant height, main stem/plant, tuber/plant, average tuber weight, tuber /plant, tuber yield,
dry matter content, starch content, medium tuber percentage and big tuber percentage in ten
27
potato genotypes. Haydar et al.(2009a) also reported highly significant differences for plant
height and tuber weight/plant.
28
Table 4. Analysis of variance for 12 characters of 18 potato varieties grown at Hosanna, 2012.
____________________________________________________________________________________________________________
Character
MSr(2)
MSg(17)
MSe(34)
LSD (5%)
CV %
___________________________________________________________________________________________________
DE
9.185
25.195**
1.773
2.210
6.1
DF
1.907
38.558**
1.731
2.183
2.4
DM
2.907
102.162**
2.398
2.569
1.5
PH
4.317
389.948**
2.301
2.517
2.8
SP
7.907
66.986**
1.437
1.989
4.9
TY
1.834
3.8783**
0.197
0.7364
10.0
TP
34.796
149.213**
7.999
4.693
15.7
BY
0.00065
0.032**
0.0016
0.05083
16
HI
0.105
0.243**
0.204
0.7501
2.5
STP
0.939
88.00**
2.9
2.295
3.2
MTP
0.887
486.717**
2.537
2.643
4.3
BTP
4.056
1.874**
1.807
2.272
6.9
_______________________________________________________________________________________________________________
MSr = mean square due to replication, MSg = mean square due to genotype, MSe = mean square due to error, DE = Days to
emergence, DF= days to flowering, DM = days to maturity, PH =plant height, SP = stems per plant, TY = Tuber yield, TP = Tubers
per plant, BY = Biological yield, HI = Harvest index, STP = small tubers percentage, MTP = Medium tubers percentage, BTP = Big
tubers percentage, figures in parenthesis indicate the degree of freedom, LSD=Least significant difference **,*, = significant at p ≤
0.01 and p ≤0.05 probability level, CV = coefficient of variation , respectively
29
4.1.2. Estimate of Genetic Parameters
4.1.3. Genotypic and phenotypic coefficients of variation
Analysis of different genetic parameters like genotypic and phenotypic variance, genotypic
and phenotypic coefficient of variability, heritability and genetic advance as percentage of
mean for twelve characters under study are presented in (Table 5). High genotypic and
phenotypic variance were found for small tuber percentage, medium tuber percentage, plant
height, stems per plant, tubers per plant and days to maturity indicating greater scope of
selection for the improvement of the six characters while medium genotypic and phenotypic
variance were found for days to flowering and days to emergence, denoting medium chance of
selection for improvement of these characters while low genotypic and phenotypic variances
were observed for big tuber percentage, tuber yield and biological yield. These findings are in
close agreement with (Haydar et al., 2009a). However, the phenotypic and genotypic variation
values cannot be used for comparing the degree of variability for different characters as the
means of the characters to be measured could also be different (Okelola et al., 2007).
Therefore, for the comparison purpose coefficients of variations were used.
Genotypic and phenotypic coefficients of variation were higher ( >20%)for medium tuber
percentage, biological yield, tubers per plant, tuber yield and plant height. These results are
inconformity with the result of (Mondal, 2003) who reported higher genotypic and phenotypic
coefficients of variation for average tuber weight/plant, tuber yield/plant and tubers
number/plant in potato. (Haydar, 2007) observed that fresh weight and tuber weight/plant
recorded comparatively high estimates of phenotypic coefficient of variability and genotypic
coefficient of variability. The characters with high GCV indicate high potential for effective
selection (Burton, 1957). However medium GCV and PCV value were found for stems per
plant, small tuber percentage and days to emergence. Hence these traits provide practically
average chance for selection while low PCV and GCV (<10%) obtained for days to flowering,
days to maturity, big tuber percentage and harvest index and hence these traits provide
practically less chance for selection. The phenotypic coefficients of variation (PCV) were
higher than corresponding genotypic coefficients of variation (GCV) for all the characters
30
studied denoting environmental factors influencing their expression. Relatively wide
difference were obtained between PCV and GCV
for days to emergence, tuber per plant,
biological yield, harvest index and big tuber percentage, indicating greater influence of
environment on those traits.
Table 5. Estimates of components of variance, heritability (in the broad sense) and genetic
advance as percent of mean for 12 characters of potato varieties tested at Hossana, 2012.
Character
DE
σ2 g
7.81
σ2 e
1.773
σ2 p
9.58
PCV(%)
14.23
GCV(%) H2b
12.85
81.52
GA
519.77
GA%
23.86
DF
DM
PH
SP
TY
TP
BY
HI
STP
MTP
BTP
12.27
33.25
129.22
21.85
1.23
47.07
0.01
0.013
28.36
161.4
0.26
1.731
2.398
2.301
1.437
0.1970
7.999
0.0016
0.2043
2.9
2.537
1.8074
14.00
35.65
131.52
23.29
1.43
55.07
0.012
0.22
31.26
163.94
2.07
6.82
5.80
21.1
19.66
26.79
41.15
43.8
2.66
10.59
34.70
7.2
6.40
5.61
20.90
19.05
25.4
38.1
40
0.64
10.08
34.4
2.56
670.59
1147.16
2321.11
934.20
212.63
1307.50
18.79
5.701
1044.87
2596.72
37.22
12.23
11.15
42.68
38.08
47.89
72.55
75.19
0.317
19.79
70.31
1.87
87
93.26
98.25
93.97
86.62
85.53
83.3
5.9
90.72
98.45
12.56
DE= Days to emergence, DF= Days to flowering, DM = Days to maturity, PH = Plant height,
SP = Stems per plant, TY= Tuber yield, TP = Tubers per plant, BY = Biological yield, HI =
Harvest index, STP = Small tubers percentage, MTP = Medium tubers percentage, BTP = Big
tubers percentage, σ2g = Genotypic variance, σ2 p = phenotypic variance, σ2e = environmental
variance, PCV = phenotypic coefficient of variance, GCV = genotypic coefficient of variance,
H2b = Heritability in broad sense, GA = genetic advance and GA% = genetic advance as
percent of mean.
31
4.1.4. Broad sense heritability
The heritability estimate showed broad ranges of variation (Table 5) among the 12 characters
measured. According to Singh(2001), high heritability of trait(≥80%) provides selection for
such trait could be fairly easy due to a close correspondence between the variety and the
phenotype due to the relative small contribution of the environment to the phenotype. But
selection may be considerably difficult or virtually impractical for traits with low heritability
(≤40%) due to the masking effect of the environment so that the greater the proportion of the
total variability is due to environment. Based on these, small tuber percentage, days to
maturity, plant height, days to flowering, tubers per plant, biological yield, days to emergence,
medium tuber percentage, tuber yield and stems per plant were found to be the most heritable
traits in the potato varieties studied. This indicates that these characters are highly heritable.
Also this indicates that selection for these traits in the varieties would be most effective for the
expression of these traits in the succeeding generations. Therefore, a good improvement can
be made if some of these traits are considered as selection criteria in future breeding program.
On the other hand, comparatively low heritability was observed for big tuber percentage and
harvest index. Similar findings had been reported for tubers per plant, yield of tuber per plant,
plant height, days to maturity and plant vigour by Sattar et al. (2007), and also in agreement
with the findings of Ara et al. (2009). Desai and Jaimini (1997) also reported that tuber yield,
number of stem, number of leaves, maturity, shoot fresh weight, number of tubers and average
tuber weight had high heritability.
Heritability value by itself cannot provide the amount of genetic progress that would result
from selection of the best individuals (Johnson et al., 1955). The studies carried out by various
researchers have shown that high heritability alone is not enough for selection; it must be
accompanied with substantial amount of genetic advance (Memon et al., 2007; Mangi et al.,
2008). To be used as a selection criterion for the breeding improvement, it has to be coupled
with higher predicted genetic gain. According to Allard (1960), the higher the heritability and
genetic gain values, the better will be the chance to select genotypes with good performance.
32
4.1.5. Genetic advance
The expected genetic advance values for 12 characters of potato varieties evaluated are
presented in (Table 5). These values are expressed as percentage of genotypes mean for each
character. Therefore, comparison could be made among various characters which had different
units of measurement.
In this study, relatively higher heritability associated with higher predicted genetic advance
was observed for tuber per plant, biological yield and medium tuber percentage indicating the
major portion of genotypic variation attributable to additive gene action. These traits therefore,
deserve greater attention in future breeding programs for developing better potato varieties.
High heritability estimates with genetic advance as percentage of mean are more useful in
predicting yield under phenotypic selection than heritability alone according to Mondal (2003)
in potato. On the other hand higher heritability associated with medium predicted genetic
advance were obtained for plant height, tuber yield, and stems per plant. This findings are in
close agreement with that of Haydar et al. (2009b) and Ara et al. (2009) who reported high
heritability (in a broad sense) as well as high genetic advance as percentage of mean for plant
height, branches number, tubers number and tuber yield.
Comparatively, high heritability with low genetic advance was estimated for days to maturity,
days to emergence, harvest index, big tuber percentage, small tuber percentage and days to
flowering. So, these characters may not be considered important. The association of high
heritability with low predicted genetic advance was reported to be attributed by predominant
effects of non additive gene (Ahmed et al., 2007).
Panse(1957) suggested that effective selection may be done for the characters having high
heritability accompanied by high genetic advance which is due to the additive gene effect. He
also reported that low heritability accompanied with genetic advance is due to non-additive
gene effects for the particular character and would offer less scope for selection because of the
influence of environment.
33
4.1.6 . Correlation coefficients
The results of the correlation coefficients (Table 6) revealed phenotypic and genotypic
correlation between characters. In this study high positive significant correlation was found
between tuber yield and biological yield, plant height and tuber yield, tuber per plant and
small tuber percentage, stems per plant and tuber per plant. These findings were in agreement
with the results of (Burton, 1969), who reported positive significant association between tuber
yield and stems per plant, plant height and tuber weight per plant.
Days to emergence had high significant positive association with days to flowering and days
to maturity. Similarly, days to maturity had high significant positive correlation with
biological yield. Plant height and biological yield, tuber yield and plant height had high
significant positive associations. This indicates that increase in positively associated
characters contributes in order to increase yield per plant.
Therefore, for selection purposes to improve tuber yield per plant, it is suggested that
emphasis should be given to those positively correlated traits. Yildirim et al. (1997) found
similar results for plant height, main stem/plant, average tuber weight, tuber weight/plant and
tuber yield. Galarreta et al. (2006) reported that there is a significant correlation between tuber
yield with tuber number and tuber weight. Khayatnezhad et al. (2011) determined that
significant correlation between tuber yield and stem per plant, tuber weight per plant and tuber
yield, plant height and tuber yield, Amadi et al. (2008) also reported that number of tubers and
average tuber weight were positively and significantly correlated with yield. These results are
in agreement with the current findings.
34
34
Table 6. Phenotypic (above diagonal) and genotypic (below diagonal) correlation coefficient among potato traits.
______________________________________________________________________________________________________________________________________
Trait
DE
DF
DM
PH
SP
TY
TP
BY
HI
STP
MTP
BTP
______________________________________________________________________________________________________________________
DE
1
0.442**
0.364**
-0.011
-0.361**
0.156
-0.337*
0.262 -0.237
-0.131
-0.118
-0.010
DF
0.513**
1
-0.082
-0.263
0 .152
-0.006
0.169
0 .163 -0.094
0.056
-0.202
0.145
DM
0.410**
-0.084
1
0.313*
-0.202
0.100 -0.469** 0.362** -0.138
-0.101
-0.082
0 .179
PH
-0.012
-0.273
0.330*
1
0.089
0.574** -0.137
0.404** -0.068
-0.346*
0.252
0.004
SP
-0.406**
0.163
-0.214
0.10
1
0.289* 0.449** 0.246
-0.028
0.135
0.073
0.094
TY
0.186
-0.007
0.110
0.615**
0.318*
1
-0.008
0.653** 0.001
-0.423**
0.314*
0.015
TP
-0.400**
0.191
-0.512** -0.145
0.491**
-0.015
1
-0.051
0.193
0.601**
-0.337*
0.148
BY
0.301*
0.18
0.384**
0.415**
0.261
0.720** -0.057
1
-0.042
-0.245
0.086
0.125
HI
-1.00**
-0.38**
-0.55**
-0.26
-0.11
0.00
0.816**
-0.182
1
0.008
0.079
0.122
STP
-0.143
0.016
-0.102
-0.036
0.144
-0.45**
0.635**
-0.251
0.00
1
-0.789** 0.112
MTP
-0.13
-0.21
-0.084
0.253
0.14
0.34*
-0.357*
0.088
0.00
-0.767**
1
-0.196
BTP
-0.029
0.418**
0.490**
0.038
0.273
0.016
0.436**
0.35*
1**
0.31*
-0.53**
1
____________________________________________________________________________________________________________
** = Correlation is highly significant at p< 0.01, * = Correlation is significant at p< 0.05, DE = Days to emergence, DF = days to
flowering, DM = Days to maturity, PH = plant height, SP = Stems per plant, TY= Tuber yield, TP = Tubers per plant, BY = Biological
yield, HI = Harvest index, STP = small tubers percentage, MTP = Medium tubers percentage, BTP = Big tubers percentage.
35
Days to emergence has positive non significant association with tuber yield, biological yield,
and negative non- significant correlation with plant height, harvest index, medium tuber
percentage, small tuber percentage, big tuber percentage, similarly days to flowering had
positive non-significant correlation with stem per plant, tuber per plant, biological yield, small
tuber percentage, big tuber percentage and also negatively non-significant relationships with
days to maturity, medium tuber percentage, tuber yield, harvest index and plant height. Days
to maturity had positive non-significant association with tuber yield, big tuber percentage and
negative non-significant correlation with small tuber percentage, medium tuber percentage,
harvest index and stems per plant. Plant height has positive non-significant correlation with
stem per plant, medium tuber percentage, big tuber percentage and negative non- significant
association with tuber per plant and harvest index. Stems per plant had positive nonsignificant relationships with biological yield, small tuber percentage, medium tuber
percentage and big tuber percentage, but it had significant positive association with tuber yield.
Biological yield had strong positive significant association with small tuber percentage and
non-significant correlation with harvest index and big tuber percentage. And characters like,
tuber per plant and harvest index, harvest index and medium tuber percentage had positive
non- significant associations whereas tuber per plant and biological yield, harvest index and
big tuber percentage, tuber yield and tuber per plant, medium tuber percentage and big tuber
percentage, harvest index and small tuber percentage had negative non-significant correlation.
Therefore, improvement of tuber yield in potato is possible by using appropriate breeding
strategy through selection for those positively correlated traits.
On the other hand, negative and strong significant correlation were found between small tuber
and medium tuber percentage, days to maturity and tuber per plant, tuber per plant and stems
per plant, days to emergence and stems per plant. Negative significant association were
determined between plant height and small tuber percentage, tuber yield and small tuber
percentage, tuber per plant and medium tuber percentage, tuber yield and medium tuber
36
percentage, days to emergence and tuber per plant, days to maturity and plant height. This
may be indicative of the existence of a compensatory relationship between pairs of characters.
This indicates increase in one of the character may lead to decrease in the other. This is in
agreement with the findings of Khayatnezhad et al. (2011), who reported negative significant
association between tuber per plant and medium tuber percentage, tuber yield and medium
tuber percentage, small tuber percentage and medium tuber percentage. Negative relation was
observed between tuber number and tuber weight as it was reported by Hamed et al. (2011).
The genotypic correlation coefficients were higher than the corresponding phenotypic
correlation coefficients for most of the characters indicating the inherent association among
the characters (Table 6). The low phenotypic correlation coefficient could arise due to the
modifying effect of environment on the association of characters at genetic level under study
as explained by Nandpuri et al.(1973). Johnson et al. (1955) also reported that higher
genotypic correlation than phenotypic correlation indicated an inherent association between
various characters. However, lower genotypic correlation was obtained between small tuber
percentage and plant height, days to flowering and medium tuber percentage, harvest index
and tuber yield, small tuber percentage and harvest index, medium tuber percentage and
harvest index (Table 6).This may be indicative of low inherent association between the
characters. On the other hand, big tuber percentage had perfect positive correlation with
harvest index at genetic level indicates increase in one character lead to increase in the other
character, but harvest index had perfect negative association with days to emergence.
4.1.7. Path coefficients analysis
4.1.7.1. Phenotypic direct and indirect effects of characters on tuber yield
In the present study, the phenotypic and genotypic correlation coefficients of the tuber yield
with other characters were further divided into direct and indirect effects using path
coefficient analysis. In computing the path analysis the tuber yield was considered as a
dependent variable while the rest of the variables were used as independent variable.
37
Path coefficient analysis based on tuber yield as a dependent variable obtained positive direct
effect for harvest index, stems per plant, days to emergence, tuber per plant, plant height and
biological yield (Table 7). Compared to simple correlation, path analysis of tuber yield and its
characters shows that days to emergence, stems per plant, biological yield, and harvest index
exerted positive highest direct influence on tuber yield. Whereas days to flowering, days to
maturity, small, medium and big tuber percentage exerted high negative direct influence on
tuber yield. Conversely tuber per plant and plant height had positive and low direct effect on
tuber yield.
Stems per plant had the greatest direct effect on tuber yield. Its indirect effect on tuber yield
were positive through days to maturity, plant height, tuber per plant and biological yield but
negative through days to emergence, days to flowering, harvest index, small, medium and big
tuber percentage. The second highest positive direct effect on tuber yield was days to
emergence. While it had highest positive indirect effect via biological yield, days to maturity,
and low via small tuber percentage and big tuber percentage. Thirdly, plant height had highest
direct effect on tuber yield and its indirect effect was positive and high through biological
yield and small tuber percentage. Finally biological yield had highest direct effect on tuber
yield with high positive indirect effect via days to emergence, plant height, stem per plant and
small tuber percentage. The strong positive direct effect of the characters studied shows
positive correlation with tuber yield. This analysis showed that days to emergence, plant
height, stems per plant, biological yield and harvest index were the main characters for tuber
yield. Sattar et al.(2007) obtained tuber per plant, average weight of tuber, number of
compound leaves per plant had high positive direct effect on tuber yield. He also reported that
negative indirect effect for dry matter content.
Strong negative direct effect were obtained for small tuber percentage, medium tuber
percentage, days to flowering and days to maturity whereas small tuber percentage had high
positive indirect effect via medium tuber percentage and vice versa. Days to maturity had high
positive indirect effect through days to emergence, plant height and biological yield but low
positive via days to flowering, small and medium tuber percentage.
38
Big tuber percentage had negative medium direct effect on tuber yield with its positive
indirect effect via all characters except for days to flowering and days to maturity. This
suggests that low correlation between these characters and tuber yield. Yildirim et al. (1997),
Amadi et al. (2008), Lopez et al. (1987), Ozkaynak and Samanchi, 2005, Rasool et al. (2006),
stated that tuber per plant and tuber weight had positive and highest direct effects on tuber
yield. These findings were in accordance with the results of present study. Khayatnezhad et al.
(2011) reported medium tuber percentage, tuber per plant, tuber weight per plant had highest
direct effect on tuber yield. This is also in agreement with the current findings. He also
reported that small tuber percentage had negative low direct effect on tuber yield, which
disagree with this finding.
The residual effect (0.214) indicated that about 78.6 percent of the variability in tuber yield
was contributed by the eleven characters studied in path analysis. About 21.4 percent of the
variability towards yield in the present study might be due to many reasons such as other
characters which were not studied, environmental factors and sampling errors as stated by
Sengupta&Karatia(1971).
39
Table 7. Path coefficient analysis showing direct (bold) and indirect influence (off diagonal) of 11 characters on tuber yield of potato
at phenotypic level tested at Hossana.
________________________________________________________________________________________________________
Trait
DE
DF
DM
PH
SP
TP
BY
HI
STP
MTP
BTP
rp
__________________________________________________________________________________________________________________________________________________________________
DE
0.449
-0.1410
0.1630
-0.0490 -0.1621
-0.1513
0.1176
-0.1064
-0.0588
0.0529
0.0045
0.156
DF
-0.1330 -0.301
0.0246
0.0791
-0.0457
-0.0508
-0.0491
0.0283
-0.0168
0.0608
-0.0436 -0.006
DM
-0.0768
0.0173
-0.2110
-0.0660
0.0426
0.0989
-0.0763
0.0291
0.0213
0.0173
-0.0377 0.100
PH
-0.0004 -0.0959
0.1142
0.3650
0.0324
-0.0489
0.1474
-0.0248
-0.1328
0.0919
0.0001 0.574**
SP
-0.1963
0.0826 -0.1098
0.0484
0.5440
0.2442
0.1338
-0.0152
0.0734
0.0397
0.0511
0.289*
TP
-0.0007
0.0003
-0.0009
-0.0003
0.0009
0.0211
-0.0001
0.0004
0.0126
-0.0007
0.0297
-0.008
BY
0.0875
0.0544
0.1209
0.1349
0.0821
-0.0170
0.334
-0.0140
-0.0818
0.0287
0.0417 0.653**
HI
-0.0706
-0.0280
-0.0411
-0.0202
-0.0008
0.0575
-0.0125
0.2980
0.0002
0.0235
0.0363 0.001
STP
0.0745 -0.0318
0.0574
0.2071 -0.0768
-0.3419
0.1394
-0.0050
-0.569
0.4489
0.0637 -0.423**
MTP
0.0487 0.0834
0.0338
-0.1040
-0.0301
0.1392
-0.0355
-0.0325
0.3258
-0.413
0.0809
0.314*
BTP
0.0001 -0.0245
-0.0302
-0.0001 -0.0158
-0.0250
-0.0211
-0.0206
-0.0189
0.0331 -0.169
0.015
______________________________________________________________________________________________________________________
Residual effect = 0.214, ** = is significant at p< 0.01, * = is significant at p< 0.05 DE = Days to emergence, DF = Days to flowering,
DM = Days to maturity, PH = Plant height, SP = Stems per plant, TY=Tuber yield, TP = Tubers per plant, BY = Biological yield, HI =
Harvest index, STP = Small tubers percentage, MTP = Medium tubers percentage, BTP = Big tubers percentage, rp = phenotypic
correlation.
40
4.1.7.2. Genotypic direct and indirect effects of characters on tuber yield
Path coefficient analysis showing direct and indirect effects of eleven characters on tuber yield
of potato at genetic level are presented in (Table 8). The highest positive direct effect was
obtained for small tuber percentage followed by days to flowering, medium tuber percentage,
biological yield, stems per plant while low were found for plant height, harvest index and big
tuber percentage. However, days to maturity and days to emergence exerted highest negative
direct influence on tuber yield.
Small tuber percentage had strongest direct effect on tuber yield with low positive indirect
effects via all the characters except medium tuber percentage. Whereas days to flowering had
negative low indirect effect through days to emergence, plant height, harvest index and
medium tuber percentage but low positive indirect effects were found for the rest characters.
Tuber per plant had low direct effect as compared to its indirect effect via days to maturity and
small tuber percentage. Similarly, big tuber percentage was found to have low direct effect
relative to its indirect effect through small tuber percentage and harvest index.
Biological yield, stems per plant and medium tuber percentage had significant genotypic
correlations with yield and exerted highest direct effect on tuber yield indicating these
characters are more important than others for genetic improvement of potato yield.
The genotypic residual effect (0.345) of path analysis shows about 65.5 of the variability is
due to eleven characters studied. Also indicates that studied characters were enough to
contribute tuber yield per plant in potato.
41
Table 8. Path coefficient analysis showing direct (bold) and indirect influence (off diagonal) of 11 characters on tuber yield of potato
at genotypic level tested at Hossana.
_________________________________________________________________________________________________________
Trait
DE
DF
DM
PH
SP
TP
BY
HI
STP
MTP
BTP
rg
_____________________________________________________________________________________________________________________
DE
- 0.153
-0.0785
-0.0627
0.0018
0.0621 0.0612
-0.0461
0.1530
0.0218 0.0198
0.0044
0.186
DF
0.0938
0.183
-0.0154
-0.0499
0.0298
0.0349
0.0329
-0.0695
0.0029 -0.0384
0.0765
-0.007
DM
-0.1496
0.0031 -0.365
-0.1204
0.0781
0.1868
-0.1402
0.2007
0.0372 0.0306 -0.1788
0.110
PH
-0.0012
-0.0267
0.0323
0.098
0.0098
-0.0142
0.0406 -0.0255
-0.0035
0.0249 0.0037
0.615**
SP
-0.0434
0.0174 -0.0228
0.0107
0.107
0.0525
0.0279
-0.0117
0.0154
0.0149
0.0292
0.318*
TP
0.0382
0.0208 -0.0558
-0.0158
0.0535
0.109
-0.0062
0.0889
0.0692 -0.0389
0.0475
-0.015
BY
-0.1069
0.0228
0.0487
0.0527
0.0331
-0.0072
0.127
-0.0231 -0.0318
0.0112
0.0445
0.720**
HI
-0.095
-0.0361
-0.0523
-0.0247
-0.0104
0.0775 -0.0171
0.095
0.0000
0.000
0.095
0.000
STP -0.1069
0.0119 -0.0763
-0.0268
0.1077
0.4749
-0.1877
0.000
0.748
-0.5737
0.2318
-0.45**
MTP
-0.0227 -0.0367 -0.014
0.0443
0.0245
-0.0624
0.0154
0.000
0.1342
0.175
-0.0927
0.34*
BTP
-0.0024
0.0351
0.0411
0.0032
0.0229
0.0366
0.0294
0.084
0.0260 -0.0445
0.084
0.016
____________________________________________________________________________________________________________
Residual effect= 0.345,**= is significant at p< 0.01, * = is significant at p< 0.05 DE = Days to emergence, DF = Days to flowering,
DM = Days to maturity, PH = Plant height, SP = Stems per plant, TY=Tuber yield, TP = Tubers per plant, BY = Biological yield, HI
= Harvest index, STP = Small tubers percentage, MTP = Medium tubers percentage, BTP = Big tubers percentage, rg = genotypic
correlation.
42
5. SUMMARY, CONCLUSION AND RECOMMENDATION
5. 1. Summary
The cultivated potatoes of world commerce are collectively designated under the name
Solanum tuberosum L. It is one of the important crops in the developed as well as in the
developing countries of the world due to its characteristics of being a staple food and high
yielding potential. Therefore, there is a bright prospect to promote potato crop as
supplementary food in developed and developing countries of the world. It is the most
industrial plant which plays an important role in feeding the world. Comparing with rice and
wheat, potato consists the valuable amount of energy and protein per unit area.
Potato production in Ethiopia covers an area of about 1600,000 ha. Ethiopia is known to have
a suitable edaphic and climatic condition for the production of high quality potatoes. For
making comparative study of a few traits to select desirable ones from different genotypes
different genetic parameters such as genotypic and phenotypic variance, genotypic and
phenotypic coefficient of variability, heritability (H2b) and genetic advance as percentage of
mean and correlation coefficient and path analysis were done for twelve characters under
study.
The genotypic coefficients of variation (GCV) were less than corresponding phenotypic
coefficients of variation (PCV) for all characters, denoting environmental factors influencing
their expression. Significant differences among all the genotypes were obtained. Correlation
coefficient analysis measures the magnitude of relationship between various plant characters
and determines the component characters on which selection can be based for improvement in
potato tuber yield. However, path coefficient analysis helps to determine the direct effect of
traits and their indirect effects on yield. This study was intended to clarify the inter relationship between yield and some agronomic traits in potato by partitioning the observed
phenotypic correlation into direct and indirect effect in order to identify traits of utmost
43
importance that may be used as selection criteria in breeding potato for improved yield. The
result of correlation coefficient for tuber yield had strong positive and significant association
between plant height and biological yield. On the contrary strong and negative significant
relations were obtained between, tuber yield and small tuber percentage, tuber per plant and
medium tuber percentage, tuber yield and medium tuber percentage
In path coefficient analysis, stem per plant, days to emergence, plant height and biological
yield had highest direct effect on tuber yield.
5.2. Conclusions
Path coefficient analysis helps to determine the direct effect of traits and their indirect effect
on yield. In this study small and medium tuber percentage, stems per plant and biological
yield at genetic level and days to emergence, plant height biological yield, stems per plant at
phenotypic level exerted highest direct effect on tuber yield indicating that these traits are of
utmost importance and could be used successfully as indices for selection for high yields in
potato. Most of the traits except harvest index and big tubers percentage were found to be
most heritable. Higher heritability associated with higher predicted genetic advance was
observed for tuber per plant, biological yield and medium tuber percentage indicating the
major portion of genotypic variation attributable to additive gene action. These traits therefore,
deserve greater attention in future breeding programs for developing better potato varieties.
5.3 . Recommendation
High yield with good quality is the most important objective in potato breeding. Therefore,
from the potatoes which were studied Chiro, Gorobella, Bubu, Jalanie, Guassa, Bedassa,
Belete, Gudanie and Zengena respectively are the varieties with high yielding in the study area.
So, by considering those characters with high heritability accompanied with high genetic
advance, traits with strong positive association with tuber yield and characters having highest
positive direct effect on tuber yield, breeders could select these characters in the future for
further improvement of potato with good quality and high yielding.
44
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54
7. APPENDICES
Appendix Table 1. Mean values of studied traits, measured from 18 potato varieties
NO
1
2
Genotype
DE
DF
Awash
Bedassa
22.67
21.00cde
52.33
55.00cd
94.00
103.67cd
49.60
59.73de
23.67
27.00cd
4.558
5.150bcde
13.73
19.73abc
3
4
5
6
7
Belete
Bolbo
BUbu
BUle
Challa
23.33bc
19.33ef
29.67k
18.67ef
19.33ef
53.00def
52.33efg
61.67a
50.33g
50.00g
104.67bc
98.00L
106.67b
104.00bcd
101.33
54.33gh
56.87fg
65.40b
60.87cd
48.63I
17.33h
28.67bc
24.33def
26.33de
19.33gh
5.018cdef
4.122gh
5.583abc
3.403Hi
4.225fg
8
9
10
11
12
13
14
Chiro
Gera
Gorobella
Guassa
Gudenie
Jalanie
Marachera
24.67b
20.00ef
20.00ef
19.33ef
24.00b
24.00b
58.67b
54.67cde
52.00fg
56.33bc
53.67def
56.67bc
53.67def
102.67cde
102.67cde
104.67bc
102.67cde
103.33cde
102.00cde
110.00n
57.83ef
67.20b
61.20cd
47.80I
62.70c
52.73h
43.33k
22.33f
20.00g
30.00b
32.33a
23.33ef
34.00a
18.33gh
15
16
17
18
Menagesha
Sako
Wochecha
Zengena
24.00b
20.67de
22.67bcd
18.00f
56.67bc
63.33a
53.33def
53.00def
118.00m
90.00s
102.67cde
100.67e
54.93gh
26.13m
36.13L
73.47a
23.67ef
26.33de
19.67g
25.00def
bcd
20.00ef
DM
efg
PH
k
SP
I
TY
ef
TP
defg
BY
defg
HI
e
STP
MTP
d
BTP
0.1067
0.2167d
b
17.667
18.000a
e
42.67
52.67n
40.00
23.67g
19.13ab
20.20a
10.67fgh
36.80L
16.00bcde
18.87abcd
14.73cdefg
0.3667abc
0.1933d
0.4133a
0.2000d
0.1300e
18.000a
18.000a
18.000a
18.000a
18.667a
31.00g
89.87a
48.67c
49.23c
38.67f
37.00e
24.00g
34.00e
46.00c
57.23a
20.20a
20.20a
20.20a
20.20a
18.47b
6.083a
4.334efg
5.857ab
5.275abcd
4.883cdefg
5.567abc
3.367hI
18.67abcd
15.40cdef
16.07bcde
21.33ab
13.27efg
22.73a
22.47a
0.3333bc
0.1967d
0.3000c
0.3967ab
0.2933c
0.4000a
0.3000c
18.000a
18.000a
18.000a
18.000a
17.400b
18.000a
18.000a
28.90g
62.00b
57.67c
60.67b
47.33cd
42.33e
88.00a
51.37b
26.00fg
41.67d
27.00f
45.83c
53.23b
7.67w
20.20a
20.20a
20.20a
20.20a
17.47b
20.20a
20.20a
3.123h
2.000s
2.770I
4.733defg
6.73h
28.80m
9.60gh
18.87abc
0.1967d
0.0900e
0.1967d
0.3433abc
17.473b
18.000a
18.000a
18.000a
46.00d
72.00m
56.00c
36.67f
36.10ef
26.00fg
40.00d
48.00c
20.80a
20.20a
20.20a
20.20a
Values with the same superscript letters are non-significantly different at p≤ 0.05, DE= Days to emergence, DF= days to flowering, DM = days maturity, PH =
plant height, SP = stems per plant, TY= Tuber yield, TP =Tubers per plant, BY = Biological yield, HI = Harvest index, STP = small tubers percentage,
MTP=Medium tubers percentage, BTP=Big tubers percentage
55
56