Heritability Estimates For Yield Research Articles

Evaluation of 10 Edamame Breeding Lines to Determine Yield, Agronomic, and Seed Composition Traits

Edamame is a vegetable soybean (Glycine max) that is harvested at the R6 growth stage. Although it is relatively new to America, the acreage and market demand of edamame have steadily increased. Developing new cultivars that are more adapted to local environments and crop management systems is significantly important to promoting specialty crop production and meeting the market requirements. In this study, 10 edamame breeding lines and four check cultivars were evaluated during 2020–23 to determine the potential production in the southeastern United States. Among genotypes, there were significant differences in the fresh pod and mature seed yields and agronomic and seed composition traits that were investigated. The year effects and genotype × year interactions were also significant in most cases. Fresh pod and mature seed yields were not significantly correlated with most of other agronomic traits and seed compositions. Over 4 years, the fresh pod yield averaged 11,227.5 kg·ha−1 (range, 9800.1–13,154.3 kg·ha−1), and the mature seed yield averaged 2814.7 kg·ha−1 (range, 2029.2–3175.2 kg·ha−1). The average 100-seed weight of 14 genotypes was 26.9 g (range, 23.1–30.1 g), and the average seed size of nine breeding lines was larger than that of the check. Maturity occurred on average 153.3 days after planting (range, 147.1–159.5 days). Based on dry weight, seed protein, oil, and sucrose contents had averages of 43.5%, 18.7%, and 5.0%, respectively. The estimates of broad-sense heritability were medium to high (66.82%–94.90%) for most of the traits, whereas the heritability estimates for fresh pod yield and duration from flowering to maturity were relatively low (23.44%–42.29%). Several breeding lines exhibited good yield, larger seed size, and higher contents of protein, oil, and oleic acid, suggesting the potential of release and commercial production.

Heritability and genetic variance estimates for agronomic traits and glycoside yield in four elite stevia breeding populations

AbstractHeritability estimates of traits assist breeders in optimizing cultivar development and can help predict gain from selection in breeding programs. Narrow‐sense heritabilities were measured in agronomic traits and glycoside concentration in four elite stevia (Stevia rebaudiana Bertoni) populations using half‐sib family analysis. Gain from selection at 20% selection intensity was estimated for morphological, yield, and glycoside traits. Experiments were conducted in two field locations in North Carolina. Variation was observed across cultigens for agronomic traits including stem height, branch width, and leaf size, for both subjective and objective measurements. Yield, lodging resistance, disease resistance, and percent survival showed a high genetic variation across cultigens. In addition, glycosides including Reb A, Reb C, and Reb D also showed high variation by cultigen. Heritability estimates for plant morphological traits were highest for stem height, and moderate for yield and branch width. However, other traits such as leaf area and lodging resistance showed low heritability (0.10). Glycosides including Reb A, Reb C, Reb D, stevioside and total steviol glycosides (TSG) showed high heritability. The estimated gain from selection per year for stem height (24 mm/year), leaf area (131 mm2/year) and yield (dry weight) (1.2 Mg/ha per year) suggest significant improvements are possible per breeding cycle. The estimated gain for glycoside concentration and percent of TSG of Reb A (26.44 mg/g, 14.51%), Reb C (20.20 mg/g, 20.17%), Reb D (1.70 mg/g, 1.49%), stevioside (6.73 mg/g, 10.72%), and TSG (20.90 mg/g), similarly, indicate significant gains are possible per breeding cycle.

Genetic diversity, heritability, correlation coefficient, and path analysis of forage yield components in Iranian Phalaris aquatica L. genotypes

Twenty-six selected genotypes of Phalaris aquatica L. from Iranian germplasm were evaluated to evaluate the genetic diversity of some agromorphological characteristics. Each selected genotype was cloned and planted as spaced single plants according to a randomized complete block design (RCBD) with four replications in 2016 and 2017. Large and significant (p < 0.01) differences among genotypes were found for all traits. The estimates of broad sense heritability were low to high (h$^{2}$$_{b}$ = 0.16 - 0.75) for studied traits. High heritability estimates for dry matter yield (DMY) indicate a sufficient genetic variability for further improvement. There was the highest heritability rate and genetic advance for plant height and DMY. Selection for traits with high heritability and genetic advance can be successful. The dry matter yield cut 1 (DMY1) correlation with the number of days to flowering, number of days to pollination, plant height, and crown diameter cut 2 was positive and significant. In stepwise multiple linear regression, the plant height, number of stems per plant, and spike length explained more than 84% of the total variation of DMY1. The plant height was the most crucial component of DMY1. The path analysis showed that plant height positively affected DMY1 (0.83). The highest negative indirect effects on DMY1 were observed for plant height via the number of stems per plant (-0.238). Axes 1 and 2 of the principal coordinate analysis explained 40.94% and 18.48% of the variation, respectively, and, although not entirely separated, general groupings can be determined. In factor analysis, component 1 was positively associated with the traits dry matter yield cut 2 (DMY2) (0.855), dry matter yield (0.821), and plant height (0.755). Therefore, the first component can be called the biomass component. Finally, selection would be more effective in improving forage yield based on yield components. In conclusion, the results indicated appropriate genetic variability in the studied genotypes. However, the studied genotypes will deliver a valuable germplasm to employ in breeding programs for forage cultivar production. This progress is crucial in introducing these selected genotypes to develop a core collection of Phalaris aquatica germplasm in Iran.

Assessment of Variability and Genetic Diversity for Elite Rice (Oryza sativa L.) Genotypes of Telangana and Andhra Pradesh

The current investigation was undertaken with eighteen elite rice genotypes to study the genetic diversity, variability, heritability and genetic advance for yield and yield attributing traits. The ANOVA revealed the significant variability among the genotypes for the traits studied. 1000 seed weight is having highest phenotypic coeffcient variation and genotypic coeffcient variation (24.882 &amp; 24.835) followed by grain yield per plant (20.315 &amp; 19.523 respectively). Heritability estimates of yield attributing traits ranged from 58.3% (Panicle length) to 99.6% (1000 seed weight). High heritability along with higher genetic advance observed for 1000 seed weight, numbers of productive tillers, plant height and grain yield per plant indicating that selection for these traits would be effective. The diversity analysis revealed that genotypes were grouped into four clusters, cluster I was the largest comprising 14 genotypes and cluster II with two genotypes followed by Cluster III and IV with one variety each indicating a high degree of divergence among the genotypes.

Factor Analysis of Genetic Parameters for Body Conformation Traits in Dual-Purpose Simmental Cattle.

Simple SummaryBody conformation traits are closely related to economically important characteristics and should be considered in cattle breeding programs. A variety of body conformation traits recorded by classifiers can complicate the analysis process. Factor analysis can reduce the number of variables by combining two or more variables into a single factor, which has biological significance. The results of this study could be used by breeders to define conformation indexes and implement genetic assessments for conformation traits in dual-purpose breeds.In this study, we estimated the genetic parameters for 6 composite traits and 27 body conformation traits of 1016 dual-purpose Simmental cattle reared in northwestern China from 2010 to 2019 using a linear animal mixed model. To integrate these traits, a variety of methods were used as follows: (1) genetic parameters estimates for composite and individual body conformation traits based on the pedigree relationship matrix (A) and combined genomic-pedigree relationship matrix (H); (2) factor analysis to explore the relationships among body conformation traits; and (3) genetic parameters of factor scores estimated using A and H, and the correlations of EBVs of the factor scores and EBVs of the composite traits. Heritability estimates of the composite traits using A and H were low to medium (0.07–0.47). The 24 common latent factors explained 96.13% of the total variance. Among factors with eigenvalues ≥ 1, F1 was mainly related to body frame, muscularity, and rump; F2 was related to feet and legs; F3, F4, F5, and F6 were related to teat placement, teat size, udder size, and udder conformation; and F7 was related to body frame. Single-trait analysis of factor scores yielded heritability estimates that were low to moderate (0.008–0.43 based on A and 0.04–0.43 based on H). Spearman and Pearson correlations, derived from the best linear unbiased prediction analysis of composite traits and factor scores, showed a similar pattern. Thus, incorporating factor analysis into the morphological evaluation to simplify the assessment of body conformation traits may improve the genetics of dual-purpose Simmental cattle.

Genomic evaluation of milk yield in a smallholder crossbred dairy production system in India

BackgroundIndia is the largest milk producer globally, with the largest proportion of cattle milk production coming from smallholder farms with an average herd size of less than two milking cows. These cows are mainly undefined multi-generation crosses between exotic dairy breeds and indigenous Indian cattle, with no performance or pedigree recording. Therefore, implementing genetic improvement based on genetic evaluation has not yet been possible. We present the first results from a large smallholder performance recording program in India, using single nucleotide polymorphism (SNP) genotypes to estimate genetic parameters for monthly test-day (TD) milk records and to obtain and validate genomic estimated breeding values (GEBV).ResultsThe average TD milk yield under the high, medium, and low production environments were 9.64, 6.88, and 4.61 kg, respectively. In the high production environment, the usual profile of a lactation curve was evident, whereas it was less evident in low and medium production environments. There was a clear trend of an increasing milk yield with an increasing Holstein Friesian (HF) proportion in the high production environment, but no increase above intermediate grades in the medium and low production environments. Trends for Jersey were small but yield estimates had a higher standard error than HF. Heritability estimates for TD yield across the lactation ranged from 0.193 to 0.250, with an average of 0.230. The additive genetic correlations between TD yield at different times in lactation were high, ranging from 0.846 to 0.998. The accuracy of phenotypic validation of GEBV from the method that is believed to be the least biased was 0.420, which was very similar to the accuracy obtained from the average prediction error variance of the GEBV.ConclusionsThe results indicate strong potential for genomic selection to improve milk production of smallholder crossbred cows in India. The performance of cows with different breed compositions can be determined in different Indian environments, which makes it possible to provide better advice to smallholder farmers on optimum breed composition for their environment.

Genomic prediction of crossbred dairy cattle in Tanzania: A route to productivity gains in smallholder dairy systems

Selection based on genomic predictions has become the method of choice for genetic improvement in dairy cattle. This offers huge opportunity for developing countries with little or no pedigree data, and preliminary studies have shown promising results. The African Dairy Genetic Gains (ADGG) project initiated a digital system of dairy performance data collection, accompanied by genotyping in Tanzania in 2016. Currently, ADGG has the largest body of dairy performance data generated in East Africa from a smallholder dairy system. This study examines the use of genomic best linear unbiased prediction (GBLUP) and single-step (ss)GBLUP for the estimation of genetic parameters and accuracy of genomic prediction for daily milk yield and body weight in Tanzania. The estimates of heritability for daily milk yield from GBLUP and ssGBLUP were essentially the same, at 0.12 ± 0.03. The heritability estimates for daily milk yield averaged over the whole lactation from random regression model (RRM) GBLUP or ssGBLUP were 0.22 and 0.24, respectively. The heritability of body weight from GBLUP was 0.24 ± 04 but was 0.22 ± 04 from the ssGBLUP analysis. Accuracy of genomic prediction for milk yield from a forward validation was 0.57 for GBLUP based on fixed regression model or 0.55 from an RRM. Corresponding estimates from ssGBLUP were 0.59 and 0.53, respectively. Accuracy for body weight, however, was much higher at 0.83 from GBLUP and 0.77 for ssGBLUP. The moderate to high levels of accuracy of genomic prediction (0.53-0.83) obtained for milk yield and body weight indicate that selection on the basis of genomic prediction is feasible in smallholder dairy systems and most probably the only initial possible pathway to implementing sustained genetic improvement programs in such systems.

Estimation of genetic parameters for production and reproductive traits in Indian Karan-Fries cattle using multi-trait Bayesian approach.

Estimates of variance components are needed for implementing genetic selection. This study was conducted to genetic parameters for production and reproductive traits on Indian Karan-Fries cattle using multi-trait repeatability animal model. Data collected from ICAR-National Dairy Research Institute, Karnal, India (from 1988 to 2019) were used. Single-trait and multi-trait repeatability animal models were used for parameter estimation. The posterior mean of Heritability estimates for 305-day milk yield (305-DMY), lactation milk yield (LMY), lactation length (LL) were 0.20 ± 0.03, 0.19 ± 0.03 and 0.06 ± 0.02, respectively. For age at first calving (AFC), calving interval (CI), and days open (DO), the posterior mean of heritability estimates were 0.24 ± 0.08, 0.06 ± 0.01, and 0.07 ± 0.02, respectively. The repeatability estimates for 305-DMY, LMY, LL, CI, and DO were 0.37 ± 0.02, 0.34 ± 0.02, 0.15 ± 0.02, 0.09 ± 0.02, and 0.12 ± 0.02, respectively. Genetic correlation between milk production traits (305-DMY, LMY, and LL) was positive and strong (> 0.80). However, the genetic correlation between milk production trait and AFC ranges from - 0.31 to 0.12. Unfavorable strong genetic correlations were observed between production and reproductive traits (CI and DO) with values ranged from 0.5 to 0.7. Phenotypic correlations among 305-DMY, LMY, and LL were generally positive and high. The moderate heritability estimates and potential genetic variation for 305-DMY, TMY, and AFC suggested that genetic gain can be obtained for these traits through genetic selection. Low heritability estimates found for LL, CI and DO, indicating that the possibility of changing these traits through genetic selection is small. High genetic correlation observed between productive and fertility traits were unfavorable. The existed strong genetic and phenotypic correlation estimates between CI and DO indicates that recording only one of them would be sufficient in the herd. As the multi-trait model showed slight improvements in the h2 as well as r estimates for both productive and reproductive traits over univariate analysis, future selection with a multi-trait animal model applying Bayesian approach would be recommended.

Identifying quantitative trait loci for steviol glycoside production in Stevia rebaudiana using transcriptome-derived SSRs

Stevia (Stevia rebuadiana Bertoni) is a perennial shrub grown for the extraction of sweet tasting, nonnutritive compounds called steviol glycosides (SGs) from the leaves, which are up to 300 times sweeter than sugar. The most abundant SGs, stevioside and rebaudioside (Reb) A, have undesirable taste characteristics that have limited their acceptance as a sugar substitute. The SGs Reb D and Reb M offer a similar sweetening intensity to Reb A, but with a superior taste profile. However, these compounds are produced in much lower concentrations than Reb A. The genetic control of SG biosynthesis is only partially understood, hampering efforts to develop new varieties producing high concentrations of desired SGs. Here we report development of a reference transcriptome from a diverse set of stevia tissues. Simple sequence repeat (SSR) markers were mined from the transcriptome, and a genetic linkage map for a pseudo test-cross F1 stevia population was generated with 97 SSRs. This population exhibited transgressive segregation and high broad-sense heritability estimates for many leaf biomass yield and SG content-related traits across two field locations. Two quantitative trait loci (QTL), each explaining 14.0–16.6 % of the observed variation, were identified for Reb D concentration. Additional QTL were identified for Reb A concentration, vigor, and plant height. This study represents the first report of QTL in stevia and will aid future efforts for molecular marker development and gene discovery for economically important traits in stevia.

Genetic Variation for Biomass Yield and Predicted Genetic Gain in Lowland Switchgrass “Kanlow”

Switchgrass (Panicum virgatum L.) is a warm-season, perennial grass valued as a promising candidate species for bioenergy feedstock production. Biomass yield is the most important trait for any bioenergy feedstock. This study was focused on understanding the genetics underlying biomass yield and feedstock quality traits in a “Kanlow” population. The objectives of this study were to (i) assess genetic variation (ii) estimate the narrow sense heritability, and (iii) predict genetic gain per cycle of selection for biomass yield and the components of lignocelluloses. Fifty-four Kanlow half-sib (KHS) families along with Kanlow check were planted in a randomized complete block design with three replications at two locations in Tennessee: Knoxville and Crossville. The data were recorded for two consecutive years: 2013 and 2014. The result showed a significant genetic variation for biomass yield (p &lt; 0.05), hemicellulose concentration (p &lt; 0.05), and lignin concentration (p &lt; 0.01). The narrow sense heritability estimates for biomass yield was very low (0.10), indicating a possible challenge to improve this trait. A genetic gain of 16.5% is predicted for biomass yield in each cycle of selection by recombining parental clones of 10% of superior progenies.

Multi-trait animal model based estimation of direct and correlated responses in Frieswal cattle

The study was undertaken to estimate the genetic parameters, direct and correlated responses for the test day and lactation milk yield in Frieswal cattle. Data on 9,955 daily milk yield records of 973 Frieswal cows calved during 2005 to 2014 at Ambala and Meerut dairy farms were utilized. The variance components, heritability estimates, genetic and phenotypic correlations for all the 11 traits were estimated simultaneously by fitting multi-trait animal model using the Wombat program of Meyer (2006) with contemporary groups as fixed effect, the additive genetic random effects, linear and quadratic regressions of covariate age at first calving and linear regression of covariate first lactation length. The expected genetic gain (DG), correlated response (CR) in cumulative 305-day yield and vice versa and the relative efficiency (RE %) of selection based on different test day yields were estimated. The results revealed lower additive genetic variance and heritability estimates for different test days and cumulative 305-day yield. The genetic correlations between the test days up to 225 and cumulative 305-days were higher which indicated the positive relationship between these traits. The higher correlated responses in cumulative 305- day yield estimated through the selection for TD135, TD165 and TD45, in that order indicated that early selection of sires using test day records would be efficient in genetic improvement for lactational milk yield in Frieswal breed of cattle.

The use of dijkstra mechanistic model for genetic analysis of the lactation curve characteristics and their relationships with age at first calving and somatic cell score of Iranian dairy cows

The objective of this study was to estimate lactation curve parameters with Dijkstra mechanistic model and to evaluate genetic and phenotypic relationships between the parameters and the average somatic cell count in primiparous cows. The finding indicated that heritability estimates for partial milk yield (PMY1, PMY2 and PMY3), total 305-day milk yield (TMY305), decay parameter (λ2), age at first calving (AFC) and peak yield (PY) were moderate while the heritability of persistency (PS%), average somatic cell score (AVGSCS), time to peak yield (TP), initial milk production (λ0), specific rate of cell proliferation at parturition (λ1), and specific rate of cell death (λ3) were quite low. Genetic correlations between both AFC and PS% traits with average somatic cell scores was negative (-0.047 and -0.060) but low positive genetic correlation were between partial milk yields (PMY1 and PMY3) while negative genetic correlation (-0.06) was obtained between TMY305 and AVGSCS. Differences between TMY305 of cows with less than 100000 cells mL-1 and cows with &gt;1,500,000 cells mL-1 was approximately 708 Kg and is equivalent to 8% loss of milk yield/cow during lactation period and also loss of persistency (11.1 %( was shown for the extreme classes of SCC in this study.

Analiza predkomisijskih pokusa kukuruza i germplazme razvijene u oplemenjivačkoj stanici u Altınovi od 2015. do 2018. godine

Main goal of the most breeding programs is to develop highly adaptive hybrids in various environments, and the most important limitation are complex interactions between genotype, environment and management. Every hybrid breeding program follows certain strategy for new hybrid development. One possible strategy is to develop hybrids with lower adaptability, achieving best performance in “high input” environments (breeding for “race-horses”). However, another approach is to breed for hybrids with higher adaptability and stable performance across a wide range of environments (breeding for “work-horses”). High stability needs to be accompanied by high yield performance to insure profits, so stability should be monitored along with performance in breeding trials. Aim of this research was to analyze the new germplasm developments and their performances in the pre-registration trials in Turkey by the means of BLUP and GGE models. Heritability estimates for grain yield ranged from 0.58 to 0.85, and relative stability of all hybrids and checks is detected across all years. Cause of the high estimates of G×L interaction were crossovers of genotype performances across locations. The location Altinova was the least stable location across years. One hybrid was selected as a future check based on stability parameters across environments. As G×E interaction remains the greatest challenge in modern maize breeding, more research is needed in this field. Therefore mixed-model based approach is a valuable tool for analysis of genotype performances in maize breeding trials.

Variation in avenanthramide content in spring oat over multiple environments

Avenanthramides (AVNs), a group of phytochemicals which are unique to oats, provide health benefits through antioxidant activity and other bioactivities. In this study, we explored genotype-by-environment interactions and heritability for AVN concentrations in oats. Avenanthramide concentrations were quantified for 100 breeding lines and cultivars at three locations over two years. While year and environment had an influence on AVN concentrations, with the influence of year being more apparent than that of environment within a year, genotype had the largest impact on AVN concentration. All three major AVNs were found to be heritable. Two methods of calculating heritability on a line mean basis were used. The statistical method yielded heritability estimates of 0.34, 0.39, and 0.41 for AVN 2c, AVN 2p, and AVN 2f, respectively. By comparison the traditional plant breeding method yielded heritability estimates of 0.82, 0.88, and 0.89 for AVN 2c, AVN 2p, and AVN 2f, respectively, indicating that expected gains will be dependent on the scale of the breeding program, the number of target environments, and climate variability. The estimated heritabilities and the 11-fold range in AVN concentrations in the 100 genotypes studied provided evidence that variability for AVN concentration should allow breeding progress for higher AVN concentration.

First breeding program of the Portuguese oyster Crassostrea angulata demonstrated significant selection response in traits of economic importance

The Portuguese oyster Crassostrea angulata is one of the economically important mollusc species but to date there has been no genetic improvement program conducted for this species. The principal aim of this study was to assess genetic gains achieved from a selection program for improved whole weight at harvest over three generations from 2015 to 2017. A total of 30,212 oysters had performance data recorded; they were the offspring of 323 sires and 461 dams. Linear mixed models were used to estimate genetic parameters of the traits studied. Selection for improved harvest whole weight achieved significant direct response by 17.4% after three generations. There were also positively correlated changes in soft tissue weight and shell shape traits (3.67% and 3.98%, respectively). The genetic gains in harvest whole weight and favourably correlated changes in meat yield and shell shape traits were consistent with the positive genetic correlations of whole weight with these traits (0.08–0.50). There is abundant genetic variation in the selection criterion (heritability for whole weight = 0.24), suggesting that the present population of Portuguese oysters will continue showing responses to future selection. The estimates of heritability for meat yield and shell shape traits were low (0.10–0.16). Hence, a multi-trait selection program can be used to enhance overall productivity and economic return for oyster producers.

Genetic and Physiological Aspects of Drought Tolerance in Smooth Bromegrass

ABSTRACTThe genetic basis of physiological traits and their association with forage yield and drought tolerance is poorly understood in smooth bromegrass (Bromus inermis Leyss). In this study, half‐sib families from a polycross population were evaluated in the field under normal and water deficit conditions during 2012 and 2013. Water deficit greatly influenced physiological traits and forage production. Under water deficit conditions, most of physiological traits decreased, whereas carotenoid content, proline content, and ratio of chlorophyll a/ chlorophyll b increased. Moderate to high estimates of heritability and genetic variation for yield and physiological traits indicated that selection in this germplasm would be useful in achieving genetic progress. Heritability estimates were slightly decreased for agromorphological traits under water deficit conditions, but the heritability of physiological traits increased in response to water deficit conditions. Significant associations between drought tolerance index and chlorophyll a, chlorophyll b, total chlorophyll content, carotenoids, and proline content showed the importance of these traits to confer drought tolerance in smooth bromegrass. Several genotypes with relatively higher tolerance and forage yield were identified under both moisture regimes that can be used in further breeding programs of smooth bromegrass.

Evaluation of reference lactation length in Chios dairy sheep

Definition and establishment of a fixed reference lactation length could provide useful tools for on-farm comparison of ewes and flock management as well as genetic evaluations for the breeding programme. The objectives of this study were to (i) evaluate different reference lactation lengths for the Chios dairy sheep and (ii) define the most suitable reference length for the breed. A total of 260 042 test-day milk records from 24 474 ewes in 130 flocks collected between 2003 and 2014 were used; 15 different lactation lengths were evaluated ranging from 120 to 260 days, defined at 10-day intervals as reference for the Chios sheep. The evaluation criteria included: (a) heritability and repeatability of milk yield in each reference lactation, (b) genetic correlation of reference lactation milk yield with actual lactation milk yield and yield at first test-day record and (c) correlated response in reference lactation milk yield from selection based on first test-day milk yield. The latter emulates genetic gains achieved for milk yield based on early lactation selection. Heritability and repeatability estimates of reference lactation milk yield and genetic correlation with actual lactation yield favoured long reference lactations (180 to 230 days). On the contrary, correlation with first test-day record milk yield was higher for short lactations (120 to 170 days). Moreover, selection on first test-day record milk yield would lead to a correlated response in reference yield in 220 days equal to 85% of the highest estimate achieved in the maximum reference length of 260 days (190 days when only considering first lactation milk yield). Based on the results of the present study, an overall reference lactation length for the Chios breed of 220 days post-lambing and a first lactation reference length of 190 days post-lambing are recommended.

Random regression animal models for genetic evaluation of test-day milk yield and milking duration in Saudi dairy goats

Random regression animal model was applied for analyzing the relationships between daily milk yield (MK) and milking duration (DR) in dairy goats comparing with reviewed estimates in dairy cows. The current analyzed data involved 17345 sample test-day records from multiparous Saudi dairy goats. A cubic random regression was applied for representing additive genetic variances in all studied traits across all different days in milk (12 groups). Based on multi-lactation random regression data-set analysis, the role of inheritance was greatest during the later stages of lactation. Heritability estimates of daily milk yield (h2MK) ranged from 0.15 to 0.54. While estimates of heritability for milking duration (h2DR) were very low during the first 60 days of lactation, being not more than 0.04. During the 2nd half of lactation the estimates of h2DR ranged from 0.35 to 0.39. Results of genetic variations for lactation records during early production life showed that highest milk harvest with intermediate milking rate could be achieved. Estimates of expected breeding values for milk yield and milking duration increased in different rates with progressing days in milk groups. These results indicated that individual selection results would be favorably achieved during the late part of lactation. Additive genetic correlations between measures of all traits at different lactation months continuously decreased as the interval between test days increased. Additive genetic correlations between milking duration and milk yield were positive and considerably high. Correlations between expected breeding values of both traits ranged from 0.41 to 0.83 (mean = 0.69) across different lactation months. More details on estimates of breeding values, estimates of permanent environmental and additive genetic correlations for all traits were tabulated.

ESTIMATION OF GENETIC PARAMETERS OF SOME PRODUCTIVE AND REPRODUCTIVE PERFORMANCE ASPECTS IN FRIESIAN CATTLE

34 Friesian cows records were analyzed reared at AL-Iśhagi dairy cattle station (50 km north of Baghdad) during the period 1996-2005. Heritability estimates for milk yield 305 day (MY305d), the period between calving and first estrous, services per conceptions, day open, lactation period , dry period , gestation period and calving interval were 0.17, 0.06, 0.07, 0.05, 0.07, 0.24, 0.02 and 0.03 respectively. Repeatability estimates for the same traits were 0.20, 0.12, 0.07, 0.11, 0.15, 0.15, 0.14, and 0.05 respectively. Genetic Correlation between (MY305d) and productive & reproductive traits were negative and highly significant (p>0.01(, and ranged between -0.30 and -0.73. While Phenotypic Correlation between (MY305d) and other traits were positive and high. Most Genetic and Phenotypic Correlations between studied traits except gestation period were positive and highly significant (p>0.01). Breeding Value (BV) estimated of sire for (MY305d) were ranged between 14.720 and -8.106. The highest and lowest values of Breeding Values of cows for (MY305d) were ranged between 352.224 and -159.705. Real Producing Ability (RPA) of cows for (MY305d) were predicted between 674.051 and -365.234 as a deviation from overall mean of flock.

Estimation of the genetic milk yield parameters of Holstein cattle under heat stress in South Korea.

ObjectiveThe objective of this study was to investigate the genetic components of daily milk yield and to re-rank bulls in South Korea by estimated breeding value (EBV) under heat stress using the temperature-humidity index (THI).MethodsThis study was conducted using 125,312 monthly test-day records, collected from January 2000 to February 2017 for 19,889 Holstein cows from 647 farms in South Korea. Milk production data were collected from two agencies, the Dairy Cattle Genetic Improvement Center and the Korea Animal Improvement Association, and meteorological data were obtained from 41 regional weather stations using the Automated Surface Observing System (ASOS) installed throughout South Korea. A random regression model using the THI was applied to estimate genetic parameters of heat tolerance based on the test-day records. The model included herd-year-season, calving age, and days-in-milk as fixed effects, as well as heat tolerance as an additive genetic effect, permanent environmental effect, and direct additive and permanent environmental effect.ResultsBelow the THI threshold (≤72; no heat stress), the variance in heat tolerance was zero. However, the heat tolerance variance began to increase as THI exceeded the threshold. The covariance between the genetic additive effect and the heat tolerance effect was −0.33. Heritability estimates of milk yield ranged from 0.111 to 0.176 (average: 0.128). Heritability decreased slightly as THI increased, and began to increase at a THI of 79. The predicted bull EBV ranking varied with THI.ConclusionWe conclude that genetic evaluation using the THI function could be useful for selecting bulls for heat tolerance in South Korea.