• Animal Bioscience
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• v.37 no.2
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• pp.173-183
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• 2024

Objective: This study aimed to evaluate whether the methane (CH₄) to carbon dioxide (CO₂) ratio (CH₄/CO₂) and methane-related traits obtained by the sniffer method can be used as indicators for genetic selection of Holstein cows with lower CH₄ emissions. Methods: The sniffer method was used to simultaneously measure the concentrations of CH₄ and CO₂ during milking in each milking box of the automatic milking system to obtain CH₄/CO₂. Methane-related traits, which included CH₄ emissions, CH₄ per energy-corrected milk, methane conversion factor (MCF), and residual CH₄, were calculated. First, we investigated the impact of the model with and without body weight (BW) on the lactation stage and parity for predicting methane-related traits using a first on-farm dataset (Farm 1; 400 records for 74 Holstein cows). Second, we estimated the genetic parameters for CH₄/CO₂ and methane-related traits using a second on-farm dataset (Farm 2; 520 records for 182 Holstein cows). Third, we compared the repeatability and environmental effects on these traits in both farm datasets. Results: The data from Farm 1 revealed that MCF can be reliably evaluated during the lactation stage and parity, even when BW is excluded from the model. Farm 2 data revealed low heritability and moderate repeatability for CH₄/CO₂ (0.12 and 0.46, respectively) and MCF (0.13 and 0.38, respectively). In addition, the estimated genetic correlation of milk yield with CH₄/CO₂ was low (0.07) and that with MCF was moderate (-0.53). The on-farm data indicated that CH₄/CO₂ and MCF could be evaluated consistently during the lactation stage and parity with moderate repeatability on both farms. Conclusion: This study demonstrated the on-farm applicability of the sniffer method for selecting cows with low CH₄ emissions.

• Animal Bioscience
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• v.34 no.8
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• pp.1283-1289
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• 2021

Objective: The progestogen-associated endometrial protein (PAEP) gene encodes the main whey protein in milk, β-lactoglobulin. The aim of the study was to investigate polymorphism in the PAEP gene and its association with milk yield, composition, and quality. Methods: Test-day records for 782 dairy cows were analysed. A total of 10 single nucleotide polymorphisms (SNP) within the PAEP gene were investigated. The following parameters were recorded: milk yield (MY, kg/d), percent milk fat (%), protein (PP, %), dry matter (DMP, %) and lactose (LP, %), urea content (UC, mg/L) as well as natural logarithm for somatic cell count (LnSCC, ln). Effect on genomic estimated breeding values accuracy was evaluated with pedigree and single step model. Results: Results show that only three SNPs were polymorphic, creating 5 composite genotypes: P1 to P5. Differences in MY between composite genotypes were noted in the two tested herds. Cows with P5 composite genotypes were characterised by the highest PP and LnSCC and the lowest LP and UC (p<0.05). P4 was linked to an increased DMP and UC, while P3 to an increase in LP and decrease in PP and LnSCC. Both factors are important markers in herd management and have high influences on the herds economics. For 5 out of 7 traits the accuracy of prediction was improved by including the haplotype as a fixed effect. Conclusion: Presented results may suggest a new way to optimise breeding programmes and demonstrate the impact of using genomic data during that process.

• Journal of Animal Science and Technology
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• v.55 no.5
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• pp.343-349
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• 2013

Data including 1,372,050 milk records pertaining to 438,019 cows from 1983 to 2011 collected during performance tests conducted by the National Livestock Cooperative Dairy Improvement Center were used to calculate milk income and profit of individuals and investigate the effects of production levels of early lactation (parity 1 and 2, respectively). Individuals with a moderate level of early lactation stayed longer in herds. Among parity 1, the 9,000 kg or higher group had a lower mean number of lactations than the overall mean of 3.13. The 7,000 kg or lower and 10,000 kg or higher groups had lower mean life time milking days than the overall mean of 1,076.8 days. Standard deviations of lifetime traits tended to decrease as production levels increased. For parity 2, the 11,000 kg or higher group had a lower mean number of lactation than the overall mean of 3.43. The lifetime milking days was highest in the 12,000 kg group (1,212.0 days), and generally smaller in the lower groups. Profit increased as the production level of groups increased for both parity 1 and 2. In groups with low production levels, profit of parity 1 was higher than that of parity 2, while the reverse was true in groups with high production levels. These results suggest that individuals in the low production groups had a greater likelihood to be culled due to reproductive or other problems. Furthermore, the accuracy of the prediction of lifetime profit of individuals with a milk yield of 305 days seems to be higher for parity 2 than parity 1; therefore, it is desirable to predict lifetime profit using the 305d milk yield of parity 2. In conclusion, breeding goals are based on many factors in functions for the estimation of profit; however, production levels during early lactation (parity 1 and 2) can be used as indicators of profit to extend profitability.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.1
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• pp.1-6
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• 2010

The objectives of this study were to i) investigate genetic performance for linear type traits of individual Holstein dairy cows, especially focusing on comparative traits, and to estimate genetic variances for these traits using actual data, and ii) compare genetic performance and improvement of progeny by birth country of the cows. Linear type traits defined with five comparative traits on this study were general stature composite (GSC), dairy capacity composite (DCC), body size composite (BSC), foot and leg composite (FLC), and udder composite (UDC). These traits were scored from 1 to 6 with 1 = poor, 2 = fair, 3 = good, 4 = good plus, 5 = very good and 6 = excellent. Final scores (FS) were also included in this study. Data used was collected from the years 2000 to 2004 by the Korea Animal Improvement Association (KAIA). Only data of more than five tested cows by herd appraisal date and by sires having more than ten daughters were included to increase the reliability of the data analyses. A total of 30,204 records of the selected traits, which was collected from 26,701 individuals having pedigree information were used. Herd appraisal date, year of age, lactation stage (grouped by month), and time lagged for milking (in hours) were assumed as fixed effects on the model. Animal additive genetic effects considering pedigree relationship and residual errors were assumed with random effects. Year of age at appraisal date was classified from one to nine years of age, assigning the value of nine years of age for animals that were greater than or equal to nine years of age. From our results, the estimate for heritability was 0.463, 0.346, 0.473, 0.290, and 0.430 on GSC, DCC, BSC, FLC and UDC, respectively. The estimate for FS heritability was 0.539. The greatest breeding values for GSC were estimated for Canada, with the breeding values for American lines increasing for 10 years starting in 1989 but tending to decrease after that until 2004. For DCC, the breeding values for American and Canadian lines showed similar patterns until 1999, after which the breeding values for the American lines declined sharply. For BSC, data from Korea, Canada and the USA followed similar trends overall except when the breeding values of the American lines decreased starting in 1999. Overall, the methods used to evaluate genetic performance in this study were acceptable and allowed for the discovery of differences by country of genetic origin, likely due in part to the American use of selection indexes based primarily on milk yield traits until methods for evaluating other traits began to emerge.

• Animal Bioscience
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• v.35 no.11
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• pp.1656-1665
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• 2022

Objective: Water buffalo, an important domestic animal in tropical and subtropical regions, play an important role in agricultural economy. It is an important source for milk, meat, horns, skin, and draft power, especially its rich milk that is the great source of cream, butter, yogurt, and many cheeses. In recent years, long noncoding RNAs (lncRNAs) have been reported to play pivotal roles in many biological processes. Previous studies for the mammary gland development of water buffalo mainly focus on protein coding genes. However, lncRNAs of water buffalo remain poorly understood, and the regulation relationship between mammary gland development/milk production traits and lncRNA expression is also unclear. Methods: Here, we sequenced 22 samples of the milk somatic cells from three lactation stages and integrated the current annotation and identified 7,962 lncRNA genes. Results: By comparing the lncRNA genes of the water buffalo in the early, peak, and late different lactation stages, we found that lncRNA gene lnc-bbug14207 displayed significantly different expression between early and late lactation stages. And lnc-bbug14207 may regulate neighboring milk fat globule-EGF factor 8 (MFG-E8) and hyaluronan and proteoglycan link protein 3 (HAPLN3) protein coding genes, which are vital for mammary gland development. Conclusion: This study provides the first genome-wide identification of water buffalo lncRNAs and unveils the potential lncRNAs that impact mammary gland development.

• Animal Bioscience
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• v.37 no.4
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• pp.576-590
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• 2024

Objective: The objective of this study was to identify genes associated with 305-day milk yield (MY) and fat yield (FY) that also influence the adaptability of the Thai multibreed dairy cattle population to tropical conditions. Methods: A total of 75,776 imputed and actual single nucleotide polymorphisms (SNPs) from 2,661 animals were used to identify genomic regions associated with MY and FY using the single-step genomic best linear unbiased predictions. Fixed effects included herd-year-season, breed regression, heterosis regression and calving age regression effects. Random effects were animal additive genetic and residual. Individual SNPs with a p-value smaller than 0.05 were selected for gene mapping, function analysis, and quantitative trait loci (QTL) annotation analysis. Results: A substantial number of QTLs associated with MY (9,334) and FY (8,977) were identified by integrating SNP genotypes and QTL annotations. Notably, we discovered 17 annotated QTLs within the health and exterior QTL classes, corresponding to nine unique genes. Among these genes, Rho GTPase activating protein 15 (ARHGAP15) and catenin alpha 2 (CTNNA2) have previously been linked to physiological traits associated with tropical adaptation in various cattle breeds. Interestingly, these two genes also showed signs of positive selection, indicating their potential role in conferring tolerance to trypanosomiasis, a prevalent tropical disease. Conclusion: Our findings provide valuable insights into the genetic basis of MY and FY in the Thai multibreed dairy cattle population, shedding light on the underlying mechanisms of tropical adaptation. The identified genes represent promising targets for future breeding strategies aimed at improving milk and fat production while ensuring resilience to tropical challenges. This study significantly contributes to our understanding of the genetic factors influencing milk production and adaptability in dairy cattle, facilitating the development of sustainable genetic selection strategies and breeding programs in tropical environments.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.5
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• pp.470-474
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• 1998

Data on the first lactation performance traits of $F_1$, $F_2$ and $F_3$ crosses covering the period from 1972 to 1995 of a total of 803 dairy cows of three genetic grades maintained at Livestock Production Research Farm, Indian Veterinary Research Institute, Izatnagar were analysed. Three genetic grades were 1/2 Friesian + 1/2 Hariana (FH), 1/2 Friesian + 1/4 Brown Swiss and 1/4 Hariana (FBH) and 1/2 Friesian+ 1/4 Jersey + 1/4 Hariana (FJH). Age at first calving increased by 7% and 8% in $F_2$ and $F_3$, respectively, over the $F_1$ in FH. The reduction in age at first calving at $F_2$ and $F_3$ levels by 2-7% over the $F_1$ was observed in FBH and FJH. The lactation milk yield of $F_1$, $F_2$ and $F_3$ crosses was $1,943{\pm}100.3$, $2202{\pm}120.5$ and $1,925{\pm}123.2kg$ in FH; $2,014{\pm}76.7$, $2,264{\pm}91.5$ and $2,096{\pm}123.9kg$ in FBH and $2,005{\pm}87.0$, $2,414{\pm}94.4$ and $2,093{\pm}121.1kg$ in FJH, respectively. The lactation milk yield improved by 12-20% in $F_2$ crosses in various genetic grades. The performance of $F_1$ was, however, maintained in FH $F_3$ crosses, it improved by 4% in FBH and FJH $F_3$ crosses. The lactation lengths and calving intervals were nearly the same for $F_1$, $F_2$ and $F_3$ crosses in FH while lactation lengths and calving intervals were reduced by 3-11% in $F_2$ and $F_3$ crosses in FBH and FJH genetic grades. The milk yield/day of lactation length and milk yield/day of calving interval increased by 16-35% in $F_2$ and 2-14% in $F_3$ over the $F_1$ in various genetic grades. It is recommended that a sufficiently large effective population size of these three genetic grades be maintained by inter se matings and rigorous selection of sires so for developing a genetic base population for new breed development.

• Journal of agriculture & life science
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• v.46 no.1
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• pp.113-121
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• 2012

A total of 150,624 records of Holstein milk production collected from 2005 to 2009 were analyzed to investigate the effects of two different contemporary group definitions, parity and somatic cell score (SCS). The first definition (H BY S) of contemporary group was milking cows and heifers born in the same year and season. And the second thing (H CY S) was milking cow and heifers that delivered calves in the same year and season. Effects of contemporary group, parity and regression effect on SCS from two models were highly significant sources of variation. Coverage of variation ($R^2$) was somewhat higher in models with H BY S as contemporary group. From multivariate models with H BY S, phenotypic correlation coefficients of milk components were estimated high and positive. However, the phenotypic correlation coefficient between milk yield and SCS was -0.09, which was low enough to evidence no correlation between them. Phenotypic correlation between SCS and butter fat or between SCS and protein were also negligible but negative. From multivariate models with H CY S as contemporary group, phenotypic correlation among milk traits and SCS were similar to the estimates from models with H BY S. However, SCS in these models were lowly but negatively correlated with milk yield, milk protein, butter fat or SNF, and the phenotypic correlation coefficients of which were -0.10, -0.08, -0.08, -0.11, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.2
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• pp.170-175
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• 2016

The objective of this study was to assess variance components and genetic parameters for fat and protein content in Tsigai sheep using multivariate animal models in which fat and protein content in individual months of lactation were treated as different traits, and univariate models in which fat and protein content were treated as repeated measures of the same traits. Test day measurements were taken between the second and the seventh month of lactation. The fixed effects were lactation number, litter size and days in milk. The random effects were animal genetic effect and permanent environmental effect of ewe. The effect of flock-year-month of test day measurement was fitted either as a fixed (FYM) or random (fym) effect. Heritabilities for fat content were estimated between 0.06 and 0.17 (FYM fitted) and between 0.06 and 0.11 (fym fitted). Heritabilities for protein content were estimated between 0.15 and 0.23 (FYM fitted) and between 0.10 and 0.18 (fym fitted). For fat content, variance ratios of permanent environmental effect of ewe were estimated between 0.04 and 0.11 (FYM fitted) and between 0.02 and 0.06 (fym fitted). For protein content, variance ratios of permanent environmental effect of ewe were estimated between 0.13 and 0.20 (FYM fitted) and between 0.08 and 0.12 (fym fitted). The proportion of phenotypic variance explained by fym effect ranged from 0.39 to 0.43 for fat content and from 0.25 to 0.36 for protein content. Genetic correlations between individual months of lactation ranged from 0.74 to 0.99 (fat content) and from 0.64 to 0.99 (protein content). Fat content heritabilities estimated with univariate animal models roughly corresponded with heritability estimates from multivariate models: 0.13 (FYM fitted) and 0.07 (fym fitted). Protein content heritabilities estimated with univariate animal models also corresponded with heritability estimates from multivariate models: 0.18 (FYM fitted) and 0.13 (fym fitted).

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.5
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• pp.639-643
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• 2003

The data on 283 Sahiwal cows, sired by 16 bulls, maintained at Cattle Breeding Farm of Nagpur Veterinary College and Dairy Farm of Agricultural College, Nagpur, were considered for the estimation of genetic parameters. Variance and covariance estimates of first lactation traits were obtained using restricted maximum likelihood technique (REML). When first lactation milk yield (FLMY), first lactation length (FLL) and average daily yield (ADY) traits were considered for REML analysis, the heritabilities were $0.184{\pm}0.146$, $0.132{\pm}0.131$ and $0.141{\pm}0.133$, respectively. While, genetic and phenotypic correlations between them were medium to high except phenotypic correlations between FLL and ADY (-0.025). REML procedure considering FLMY, age at first calving (AFC) and first service period (FSP) combination exhibits heritabilities as $0.274{\pm}0.173$, $0.506{\pm}0.233$ and $0.274{\pm}0.172$, respectively. Genetic correlations were $-0.120{\pm}0.376$, $0.225{\pm}0.423$ and $0.365{\pm}0.331$ between FLMY and AFC, FLMY and FSP, AFC and FSP, respectively. Phenotypic correlations were 0.057, 0.289 and 0.123, respectively. Considering all five traits REML combination heritabilities estimated were $0.238{\pm}0.162$, $0.160{\pm}0.139$, $0.136{\pm}0.132$, $0.409{\pm}0.209$ and $0.259{\pm}0.168$ for FLMY, FLL, ADY, AFC and FSP, respectively. The genetic correlations were positive except FLMY and AFC. The phenotypic correlations were also positive except FLL and ADY, ADY and FSP. Almost all estimates were associated with high standard error.