• Asian-Australasian Journal of Animal Sciences
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• v.21 no.8
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• pp.1088-1096
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• 2008

Data from milk performance testing were used to analyze genetic and environmental trends for purebred Tsigai, Improved Valachian and Lacaune sheep. 103,715 (Tsigai), 212,962 (Improved Valachian) and 2,196 (Lacaune) test-day records gathered by the State Breeding Institute of the Slovak Republic entered the analyses. The respective pedigree data comprised 23,724 (Tsigai), 51,401 (Improved Valachian) and 438 (Lacaune) records. The multiple-trait, mixed model methodology was used to predict the breeding values for daily milk yield, fat and protein content and to estimate the fixed and remaining random effects assumed to affect the above mentioned traits, separately for each breed. The breeding values for daily milk yield were adjusted for 150-day standardized lactation length by multiplying with the constant 150, as the breeding goal of the selection scheme in Slovakian sheep is to increase 150-day milk production and constant heritability throughout the whole lactation is assumed. The genetic trends were expressed as changes in averages of breeding values across birth years of animals. For Tsigai and Lacaune breeds, cumulative genetic changes over the analyzed period were 3.8 and 5.1 kg for 150-day milk, 0 and -0.16% for fat content and 0 and -0.12% for protein content. For Improved Valachian breed, either a low (1.6 kg for 150-day milk yield) or zero (fat and protein content) cumulative genetic change was found. The environmental trends were calculated as averages of solutions for flock-test day effect across years and months in which measurements were taken. A distinctive cyclical pattern which reflected short-time variation in milk production traits was found. Possible explanations for this phenomenon are given and discussed.

• 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.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.

• Journal of Animal Science and Technology
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• v.58 no.10
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• pp.38.1-38.6
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• 2016

Background: Despite the importance of relationships between somatic cell score (SCS) and currently selected traits (milk, fat and protein yield) of Holstein cows, there was a lack of comprehensive literature for it in Iran. Therefore we tried to examine heritabilities and relationships between these traits using a fixed-regression animal model and Bayesian inference. The data set consisted of 1,078,966 test-day observations from 146,765 primiparous daughters of 1930 sires, with calvings from 2002 to 2013. Results: Marginal posterior means of heritability estimates for SCS ($0.03{\pm}0.002$) were distinctly lower than those for milk ($0.204{\pm}0.006$), fat ($0.096{\pm}0.004$) and protein ($0.147{\pm}0.005$) yields. In the case of phenotypic correlations, the relationships between production and SCS were near zero at the beginning of lactation but become increasingly negative as days in milk increased. Although all environmental correlations between production and SCS were negative ($-0.177{\pm}0.007$, $-0.165{\pm}0.008$ and $-0.152{\pm}0.007$ between SCS and milk, fat, and protein yield, respectively), slightly antagonistic genetic correlations were found; with posterior mean of relationships ranging from $0.01{\pm}0.039$ to $0.11{\pm}0.036$. This genetic opposition was distinctly higher for protein than for fat. Conclusion: Although small, the positive genetic correlations suggest some genetic antagonism between desired increased milk production and reduced SCS (i.e., single-trait selection for increased milk production will also increase SCS).

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.5
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• pp.607-614
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• 2016

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3-L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of $polynomials{\times}3$ types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

• Asian-Australasian Journal of Animal Sciences
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• v.22 no.12
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• pp.1693-1702
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• 2009

Economic values of 14 production and functional traits for two Slovak dairy sheep breeds (Improved Valachian and Tsigai) were calculated. Semi-extensive production systems with one lambing per year were simulated using a bio-economic deterministic computer model. The marginal economic value of a trait was defined as the partial derivative of the profit function with respect to that trait. The relative economic value expressed the percentage proportion of standardized economic value (marginal economic value${\times}$genetic standard deviation) of a trait in the sum of the absolute values of the standardized economic values over all traits. Milk yield was of highest relative importance (26% and 32% in Improved Valachian and Tsigai) followed by productive lifetime and conception rate of ewes (16% and 15% in Improved Valachian and Tsigai, in both traits). Conception rate of female lambs and litter size had nearly the same relative economic importance in both breeds (9% to 11%). Survival rate of lambs at lambing and till weaning reached slightly lower economic values (4% to 7%). The economic importance of all remaining traits was less than 4%.

• 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.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.28 no.4
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• pp.476-484
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• 2015

The objective of this study was to estimate genetic and phenotypic parameters for linear type traits, as well as milk yield (MY), fat yield (FY) and protein yield (PY) in 18,831 Holstein cows reared in 495 herds in Brazil. Restricted maximum likelihood with a bivariate model was used for estimation genetic parameters, including fixed effects of herd-year of classification, period of classification, classifier and stage of lactation for linear type traits and herd-year of calving, season of calving and lactation order effects for production traits. The age of cow at calving was fitted as a covariate (with linear and quadratic terms), common to both models. Heritability estimates varied from 0.09 to 0.38 for linear type traits and from 0.17 to 0.24 for production traits, indicating sufficient genetic variability to achieve genetic gain through selection. In general, estimates of genetic correlations between type and production traits were low, except for udder texture and angularity that showed positive genetic correlations (>0.29) with MY, FY, and PY. Udder depth had the highest negative genetic correlation (-0.30) with production traits. Selection for final score, commonly used by farmers as a practical selection tool to improve type traits, does not lead to significant improvements in production traits, thus the use of selection indices that consider both sets of traits (production and type) seems to be the most adequate to carry out genetic selection of animals in the Brazilian herd.

• Journal of Animal Science and Technology
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• v.65 no.3
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• pp.588-595
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• 2023

The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.