• Animal Bioscience
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• v.35 no.3
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• pp.377-384
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• 2022

Objective: This study was conducted to estimate multi-trait genetic parameters for somatic cell score (SCS), milk yield and type traits in Nigerian Dwarf (ND) goats from the United States. Methods: Data from 1,041 ND goats in the United States with kiddings in 95 herds were used to estimate multi-trait genetic parameters for SCS, milk (MILK), fat (FAT), and protein (PROT) yields, and 14 type traits. An 18-trait mixed linear animal model for lactation mean SCS (Log₂), MILK, FAT, PROT, and 14 type traits was applied. A factor analytic approach (FA1) in ASReml software was used to obtain convergence. Results: Averages for SCS were low (2.85±1.29 Log₂), and were 314±110.6, 20.9±7.4, and 14±4.9 kg, respectively, for MILK, FAT, and PROT. Heritabilities for SCS, MILK, FAT, and PROT were 0.32, 0.16, 0.16, and 0.10, respectively. The highest heritabilities for type traits were for stature (0.72), teat diameter (0.49), and rump width (0.48), and the lowest estimates were for dairyness (0.003) and medial suspensory ligament (0.03). Genetic correlations of SCS with MILK, FAT, and PROT were positive but low (0.25, 0.18, and 0.23, respectively). Genetic and phenotypic correlations between MILK, FAT, and PROT were high and positive (≥0.66). Absolute values of genetic correlations involving SCS with type traits were generally low or no different from zero. Most of the phenotypic correlations involving SCS with type traits were low. No serious unfavorable genetic correlations between milk yield traits and SCS or between milk yield traits or SCS and type traits were found. Conclusion: Genetic variation exists in the ND breed for most studied traits. The development of selection programs based on these estimates may help accelerate favorable multi-trait genetic changes in this breed.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.12
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• pp.1813-1821
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• 2002

The aim of this study was to identify useful secondary traits for estimating genetic ability of milk production traits. We investigated the value of using plasma metabolites concentrations. Two hundred and nineteen cattle out of 271 had only milk production traits records (G1), 33 had only metabolites records (G2), and 19 had both milk production traits and metabolites records (G3). Fifty two calves with metabolites records (G2 and G3) were born from 1992 to 1997. Forty three calves (29 females, 14 males) were used from 10 to 90 d of age and the others (3 females, 6 males) from 10 to 60 d of age. A total of 566 records of milk yield, fat yield and protein yield for 240 to 305 d on 238 heads (G1 and G2) were collected The collected blood samples were divided into three age groups: AG1, 10 to 30 d; AG2, 40 to 60 d; and AG3, 70 to 90 d. Heritabilities of milk yield, fat yield and protein yield were $0.45{\pm}0.04$, $0.50{\pm}0.04$ and $0.38{\pm}0.04$, respectively. Heritability of plasma glucose concentration at AG1 was $0.45{\pm}0.08$. Genetic correlations between plasma glucose concentration and milk yield, fat yield and protein yield were -$0.35{\pm}0.28$, $0.64{\pm}0.24$ and $0.36{\pm}0.35$, respectively. When the plasma glucose concentration at AG1 was used to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 8.2%, fat yield increased 24.2% and protein yield increased 9.5%. Heritability of plasma total cholesterol concentration at AG3 was $0.83{\pm}0.04$. Genetic correlation between plasma total cholesterol concentration and milk yield, fat yield and protein yield were $0.58{\pm}0.21$, $0.42{\pm}0.20$ and $0.45{\pm}0.22$, respectively. When the plasma total cholesterol concentration at AG3 was using to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 19.0%, fat yield increased 9.6%, and protein yield increased 13.5%. The annual genetic gain is in proportion to the reliability of selection. These results show that the plasma metabolite concentrations would be useful for improvement of genetic ability for milk production traits in the genetic improvement in herd of cows, where half of the animals selected are from a herd without its own milk record.

• Animal Bioscience
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• v.35 no.10
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• pp.1499-1511
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• 2022

Objective: This study was aimed to estimate the genetic parameters, including genetic and phenotypic correlations, of milk yield, lactation curve traits and milk composition of Thai dairy cattle from three government research farms. Methods: The data of 25,789 test-day milk yield and milk composition records of 1,468 cattle from lactation 1 to 3 of Holstein Friesian (HF) and crossbred HF dairy cattle calved between 1990 and 2015 from three government research farms in Thailand were analysed. 305-day milk yield was estimated by the Wood model and a test interval method. The Wood model was used for estimating cumulative 305-day milk yield, peak milk yield, days to peak milk yield and persistency. Genetic parameters were estimated using linear mixed models with herd, breed group, year and season of calving as fixed effects, and animals linked to a pedigree as random effects, together with a residual error. Univariate models were used to estimate variance components, heritability, estimated breeding values (EBVs) and repeatability of each trait, while pairwise bivariate models were used to estimate covariance components and correlations between traits in the same lactation and in the same trait across lactations. Results: The heritability of 305-day milk yield, peak milk yield and protein percentage have moderate to high estimates ranging from 0.19 to 0.45 while days to peak milk yield, persistency and fat percentage have low heritability ranging from 0.08 to 0.14 in lactation 1 cows. Further, heritability of most traits considered was higher in lactation 1 compared with lactations 2 and 3. For cows in lactation 1, high genetic correlations were found between 305-day milk yield and peak milk yield (0.86±0.07) and days to peak milk yield and persistency (0.99±0.02) while estimates of genetic correlations between the remaining traits were imprecise due to the high standard errors. The genetic correlations within the traits across lactation were high. There was no consistent trend of EBVs for most traits in the first lactation over the study period. Conclusion: Both the Wood model and test interval method can be used for milk yield estimates in these herds. However, the Wood model has advantages over the test interval method as it can be fitted using fewer test-day records and the estimated model parameters can be used to derive estimates of other lactation curve parameters. Milk yield, peak milk yield and protein percentage can be improved by a selection and mating program while days to peak milk yield, persistency and fat percentage can be improved by including into a selection index.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.3
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• pp.305-308
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• 2006

A genetic study was conducted to elucidate the effect of alpha-Lactalbumin (${\alpha}$-LA) gene polymorphism on milk production traits involving total milk yield and daily milk yield during first lactation in two breeds of water buffaloes namely, Murrah and Bhadawari. Single strand conformation polymorphism (SSCP) was carried out to explore genetic polymorphism present at this locus. For this study, exon 1 region of ${\alpha}$-LA was analyzed. Finally, polymorphism data was associated with milk production traits by employing least square analysis. In Murrah buffalo, five genotypes such as AB, BB, BC, CC and CD and four alleles A, B, C and D were detected whereas in Bhadawari buffalo two genotypes namely, AB and BC and three alleles namely, A, B and C were found. Genotypes showed significant effects ($p{\leq}0.05$) on total milk yield and daily milk yield in Bhadawari buffalo but had non-significant effects on these traits in Murrah buffalo.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.2
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• pp.179-184
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• 2005

First lactation records (174) of Jersey${\times}$Sahiwal and Holstein Friesian${\times}$Sahiwal half breds under 9 sires maintained at Chandra Shekher Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh, India from 1975-1983, were used to estimate the genetic parameters and to predict herd life milk yield and average milk yield per day of herd life from first lactation traits. The traits included were: age at first calving, first service period, first lactation period, first calving interval, first lactation milk yield, milk yield per day of first calving interval, herd life milk yield, herd life and average milk yield per day of herd life. Most of the production and reproduction traits were found to have positive and significant correlations between them on genetic as well as phenotypic scales. Total twelve regression equations were fitted. The prediction equation of herd life milk yield in both the genetic groups showed linear relationship with AFC, FSP, FLP, FLMY and MY/DCI and was apparent and significant. Similarly, polynomials for milk yield per day of herd life for J${\times}$S and HF${\times}$S half breds also showed linear trend, which was found highly significant. The highest and lowest $R^2$ values were found for FCI and AFC, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.3
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• pp.309-314
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• 2006

The present investigation was undertaken to study the milkability characteristics of Holstein cows. Out of 6,660 initial records 4,607 records were finally included in the analysis after deleting some records with an abnormal range of values for the traits considered. These 4,607 Holstein cows belonged to a total of 122 herds located in a province in Korea. The 'LactoCorder' instrument was used to electronically record the milkability traits at the milking parlor. A total of 19 traits were studied which were broadly classified into milk yield, milking speed, milking time and the electrical conductivity related traits. The SAS 9.1 statistical software was used to carry out analyses. The average maximum milk flow per minute was 3.21 kg/min, while the average milking speed during the main milking process (DMHG) had a mean value of 2.30 kg/min. The total milk yield was 14.14 kg, 62% of which was milked during the first three minutes of the milking. The average total milking time was 8.23 min. Among the three phases of the main milking process, the time of stable milk flow had the longest time (2.97 min) followed by the time at the decline phase (2.62 min). The average time taken to reach the plateau phase was 1.08 min, which can still be reduced further through improved managemental practices. Among milk yield traits, milk yield during the first two (MG2) and three (MG3) minutes of milking had high positive correlation with milking speed traits and negative correlations with almost all the milking time traits except time of incline in milk flow from 0.5 kg/min till the attainment of the plateau phase (tAN). Milking speed traits had negative correlations with total milking time, time at main milking process, time at plateau and with the time at decline. Since there was medium to high negative correlation between the milking speed and the time at plateau, there is a need for selection of cows which have intermediate milking speed so that it could require less milking time and also the optimum (higher and longer) plateau time. Proper pre-stimulation and avoiding over milking will help in further reducing the milking time and thus will add to the net profit of the farmer.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.6
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• pp.747-753
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• 2001

In this study, the Italian milk recorded buffalo population from 1974 to 1996 was analysed with the purpose to estimate genetic and environmental variability and provide genetic parameters for the most important economic traits. High variability between herds was evident due to the poor knowledge of feeding requirements and husbandry technology in this species compared to cattle. Age at first calving was reduced by 57 days during the considered years following efforts made in better feeding and management from 1990; on the contrary, calving interval has increased by 17 days as a consequence of forcing buffaloes to calve in spring, in order to have the peak milk yield when milk is much better paid. Average milk yield increased by 1853 kg during these years, while lactation duration was reduced by 30 days. Season of calving has no effect on all traits. Calving order has a positive effect on milk yield especially because older cows produce more milk in shorter lactations. Heritability for the age at first calving and calving interval was 0.26 and 0.05 respectively. Heritability of productive traits, milk yield and duration of the lactation was 0.19 and 0.13 respectively, with repeatabilities of 0.40 and 0.26. Genetic trend for milk yield was 2.1 kg milk/year for the bulls and 1 kg for all population. The high genetic variability of milk production as well as duration of the lactation, indicates that there are good opportunities for genetic improvement when including these traits in a selection scheme. The low genetic trend registered over 15 years of recording activity can be explained by the fact that neither progeny testing was performed or selection schemes were implemented, due to the difficulties to use artificial insemination in buffalo.

• Food Science of Animal Resources
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• v.25 no.3
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• pp.328-332
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• 2005

The effect of k-casein (k-CN) variant on milk production traits (milk yield, fat yield, protein yield, fat percentage and protein percentage) was estimated for 568 Holstein cows in the first lactation. The k-CN valiant were determined by PCR-RFLP (restriction fragment length polymorphism) technique at the DNA level. Single trait linear model was used for the statistical analysis of the data. Result of this study indicated that k-CN variant affected significantly milk yield (P<0.05) and protein yield (P<0.01). Animals with the BB variant produced 622kg milk more and had protein yield higher by 32kg compared with animals with the AA variant No associations between the k-CN variants and other milk production trait were found. Therefore, milk and protein yield may be improved through milk protein typing by increasing the frequencies of k-CN B variant in dairy cattle population. In cheese making, it will be also preferable to have milk with the B variant of k-CN, which gives higher yield having a better quality than the A variant milk.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.6
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• pp.769-774
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• 2006

Fractions of herd-year-season, sire by herd interaction, additive genetic and dominance genetic variances were estimated for milk production traits in Holsteins of Japan using Method R. Inbreeding depressions for milk production traits were also estimated. Estimated fractions of herd-year-season variances ranged from 0.056 to 0.074 for yield traits and from 0.033 to 0.035 for content traits. Estimated fractions of additive genetic variances to phenotypic variances (heritabilities across a herd in the narrow sense) were 0.306, 0.287, 0.273, 0.255, 0.723, 0.697 and 0.663 for milk, fat, SNF and protein yields, and fat, SNF and protein contents, respectively. Estimated fractions of dominance genetic variances ranged from 0.019 to 0.022 for yield traits and from 0.014 to 0.018 for content traits. Fractions of variances for sire by herd interaction were estimated to range from 0.020 to 0.025 for yield traits and 0.011 to 0.012 for content traits. Estimates of inbreeding depression for milk, fat, SNF and protein yields were -36.16 kg, -1.42 kg, -3.24 kg and -1.15 kg per 1% inbreeding for milk, fat, SNF and protein yields, respectively. Estimates of depression per 1% inbreeding for content traits were positive at $0.39{\times}10^{-3}%$, $0.31{\times}10^{-3}%$ and $0.82{\times}10^{-3}%$ for fat, SNF and protein contents, respectively.

• Food Science of Animal Resources
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• v.26 no.1
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• pp.121-126
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• 2006

Major milk proteins have considerable variane which comes from substitution and deletions in their amino arid sequences. Variants in genes that code for milk proteins, such as ${\beta}$-lactoglobulin (${\beta}-LG$) have been established as genetic markers for milk production and milk protein composition in dairy cattle. The effect of ${\beta}-LG$ variant on milk production traits, such as milk yield. fat yield, protein yield, fat percentage and protein percentage, was estimated for 482 Holstein cows in the first lactation. The ${\beta}-LG$ variants were determined by PCR-RFLP technique at the DNA level. Single trait linear model was used for the statistical analysis of the data. Results of this study indicated that ${\beta}-LG$ variants affected significantly protein yield (p<0.05) and fat percentage (p<0.05). Animals with the AA variant produced 31kg of milk protein more than animals with the BB variant. On the contrary, cows with the BB variant had fat percentage higher by 0.35 and 0.32% compared with cows with the AA and AB variants, respectively. No associations between the ${\beta}-LG$ variants and milk yield, protein percentage and fat yield were found Therefore, milk production traits could be improved through ${\beta}-LG$ typing by increasing the frequency of A variant for protein yield or the frequency of B variant for fat content in Holstein dairy cattle population.