• Asian-Australasian Journal of Animal Sciences
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• v.25 no.5
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• pp.653-658
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• 2012

This study was conducted to estimate the potential acid production value (PAPV) of major diets and to determine the relationship between dietary PAPV and dairy production traits. Estimation of PAPV of major cattle feeds was based on an in vitro technique, which determined the degree of Ca dissociation from $CaCO_3$. Data on feeds and production traits were collected on 744 multiparous lactating Holstein dairy cows from five different farms. Grains had high PAPV with variable protein sources and by-products. High PAPV feedstuffs had a higher total gas production and lower pH compared to those with low PAPV. Dietary PAPV had a positive correlation with intake of dry matter, NDF, ADF, milk yield and milk solid production but a negative correlation with milk protein and milk fat concentration. Current results indicate that dietary PAPV can be utilized in predicting dairy production traits.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.9
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• pp.1242-1246
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• 2003

Data pertained to 335 crossbred cows comprising of 1/2 Friesian (F) + 1/2 Hariana (H), 1/2 F + 1/4 Jersey (J) + 1/4 H, 1/2 F + 1/4 Brown Swiss (BS) + 1/4 H, 1/2 F + 1/4 Red Dane (R) + 1/4 H, FR (I) and FRH (I) genetic groups extending over a period of 21 years (1970-1990) maintained at Animal Farm of CCS HAU, Hisar. The averages for first lactation milk yield was $2,486.24{\pm}80.26kg$ and peak yield of first three lactation were $11.35{\pm}0.72kg$, $13.97{\pm}0.60kg$ and $16.02{\pm}0.42kg$, respectively. The lifetime milk production was observed as $11,305.16{\pm}1,004.52kg$ in crossbred cattle. The average first lactation fat yield was observed as $102.06{\pm}0.01kg$ and peak fat yield of first three lactation were $0.458{\pm}0.01$, $0.490{\pm}0.01$ and $0.500{\pm}0.02kg$, respectively. The lifetime fat production was estimated as $502.31{\pm}45.90kg$. LTMP and LTFP had reasonably good additive genetic variance which could be exploited either through mass selection/combined with family or pedigree selection. FLMY, peak yields and LTMP had significant positive phenotypic correlation with FLFY and LTFP and the correlation at the genetic level were also higher and positive for these traits. Finally, peak week milk yield of first lactation (PMY1) was the earliest available trait having desirable and significant correlation at phenotypic and positive at genetic level with FLFY, PFY1 and PFY2, PFY3 and LTFP and selection for this trait will help in early evaluation of sires and dams and will increase genetic advancement per unit of time.

• Asian-Australasian Journal of Animal Sciences
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• v.9 no.6
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• pp.685-693
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• 1996

A total of 3,610 Ayrshire and 1,711 Jersey cows were phenotyped for the genetic variants of ${\alpha}_{s1}$-casein, ${\beta}$-casein, $\chi$-casein, ${\beta}$-lactoglobulin and ${\alpha}$-lactalbumin. Least squares analyses showed possible associations between milk protein phenotypes and lactational production traits. Depending on lactation number, ${\beta}$-casein phenotypes in Ayrshires were associated with milk production ($A^2A^2$ > $A^1A^2$ > $A^1A^1$), and with milk protein content. In the third lactation, Ayrshire cows with ${\beta}$-casein $A^1A^1$ produced milk with 3.43% fat compared to 3.37% fat for ${\beta}$-casein $A^2A^2$. In Ayrshire, $\chi$-casein phenotypes affected the protein content during the three lactations (BB > AB > AA) and ${\beta}$-lactoglobulin phenotypes significantly influenced the milk fat during the first lactation (4.06% for AA and 3.97% for BB). In Jerseys, protein content of milk was influenced by phenotypes of ${\alpha}_{s1}$-casein(3.98% for CC v/s 3.86% for BB in the first lactation). In the third lactation, $\chi$-casein AA of Jersey milk contained 5.35% fat compared to 4.82% for phenotype BB. The effects of ${\beta}$-lactoglobulin phenotypes on protein content were apparent in Jerseys during the second lactation with the A variant being superior to the B (4.00% for AA v/s 3.87% for BB).

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.1
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• pp.14-22
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• 2019

Objective: The aim of the study was to find a possible association between the ${\beta}-$ and ${\kappa}-casein$ and ${\beta}-lactoglobulin$ genotypes and important milk physiochemical and technological characteristics such as acidity, alcohol stability, the contents of some minerals and the parameters of acid fermentation ability (FEA) in Czech Fleckvieh Cattle. Methods: Milk and blood samples were collected from 338 primiparous Czech Fleckvieh cows at the same stage of lactation. The genotypes of individual cows for ${\kappa}-casein$ (alleles A, B, and E) and ${\beta}-lactoglobulin$ (alleles A and B) were ascertained by polymerase chain reaction-restriction fragment length polymorphism, while their ${\beta}-casein$ (alleles $A^1$, $A^2$, $A^3$, and B) genotype was determined using melting curve genotyping analysis. The data collected were i) milk traits including active acidity (pH), titratable acidity (TA), alcohol stability (AS); calcium (Ca), phosphorus (P), sodium (Na), magnesium (Mg), and potassium (K) contents; and ii) yoghurt traits including active acidity (Y-pH), titratable acidity (Y-TA), and the counts of both Lactobacilli and Streptococci in 1 mL of yoghurt. A linear model was assumed with fixed effects of herd, year, and season of calving, an effect of the age of the cow at first calving and effects of the casein and lactoglobulin genotypes of ${\beta}-CN$ (${\beta}-casein$, CSN2), ${\kappa}-CN$ (${\kappa}-casein$, CSN3), and ${\beta}-LG$ (${\beta}-lactoglobulin$, LGB), or the three-way interaction between those genes. Results: The genetic polymorphisms were related to the milk TA, AS, content of P and Ca, Y-pH and Lactobacilli number in the fresh yoghurt. The CSN3 genotype was significantly associated with milk AS (p<0.05). The effect of the composite CSN2-CSN3-LGB genotype on the investigated traits mostly reflected the effects of the individual genes. It significantly influenced TA (p<0.01), Y-pH (p<0.05) and the log of the Lactobacilli count (p<0.05). Conclusion: Our findings indicate that the yoghurt fermentation test together with milk proteins genotyping could contribute to milk quality control and highlight new perspectives in dairy cattle selection.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1684-1688
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• 2017

Objective: From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes ${\kappa}-casein$ (CSN3) and ${\beta}-lactoglobulin$ (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh. Methods: The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255). Results: Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 ($6.01%{\pm}0.19%$ and $5.98%{\pm}0.22%$), and LGB ($6.02%{\pm}0.19%$ and $5.70%{\pm}0.22%$) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, $6.04%{\pm}0.22%$ and $5.59%{\pm}0.31%$ than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, $6.05%{\pm}0.20%$ and $5.60%{\pm}0.19%$, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh. Conclusion: Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.9
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• pp.1237-1246
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• 2013

The objective of this study was to estimate variance components and genetic parameters for lactation milk yield (LY), lactation length (LL), average milk yield per day (YD), initial milk yield (IY), peak milk yield (PY), days to peak (DP) and parameters (ln(a) and c) of the modified incomplete gamma function (MIG) in an Ethiopian multibreed dairy cattle population. The dataset was composed of 5,507 lactation records collected from 1,639 cows in three locations (Bako, Debre Zeit and Holetta) in Ethiopia from 1977 to 2010. Parameters for MIG were obtained from regression analysis of monthly test-day milk data on days in milk. The cows were purebred (Bos indicus) Boran (B) and Horro (H) and their crosses with different fractions of Friesian (F), Jersey (J) and Simmental (S). There were 23 breed groups (B, H, and their crossbreds with F, J, and S) in the population. Fixed and mixed models were used to analyse the data. The fixed model considered herd-year-season, parity and breed group as fixed effects, and residual as random. The single and two-traits mixed animal repeatability models, considered the fixed effects of herd-year-season and parity subclasses, breed as a function of cow H, F, J, and S breed fractions and general heterosis as a function of heterozygosity, and the random additive animal, permanent environment, and residual effects. For the analysis of LY, LL was added as a fixed covariate to all models. Variance components and genetic parameters were estimated using average information restricted maximum likelihood procedures. The results indicated that all traits were affected (p<0.001) by the considered fixed effects. High grade $B{\times}F$ cows (3/16B 13/16F) had the highest least squares means (LSM) for LY ($2,490{\pm}178.9kg$), IY ($10.5{\pm}0.8kg$), PY ($12.7{\pm}0.9kg$), YD ($7.6{\pm}0.55kg$) and LL ($361.4{\pm}31.2d$), while B cows had the lowest LSM values for these traits. The LSM of LY, IY, YD, and PY tended to increase from the first to the fifth parity. Single-trait analyses yielded low heritability ($0.03{\pm}0.03$ and $0.08{\pm}0.02$) and repeatability ($0.14{\pm}0.01$ to $0.24{\pm}0.02$) estimates for LL, DP and parameter c. Medium heritability ($0.21{\pm}0.03$ to $0.33{\pm}0.04$) and repeatability ($0.27{\pm}0.02$ to $0.53{\pm}0.01$) estimates were obtained for LY, IY, PY, YD and ln(a). Genetic correlations between LY, IY, PY, YD, ln(a), and LL ranged from 0.59 to 0.99. Spearman's rank correlations between sire estimated breeding values for LY, LL, IY, PY, YD, ln(a) and c were positive (0.67 to 0.99, p<0.001). These results suggested that selection for IY, PY, YD, or LY would genetically improve lactation milk yield in this Ethiopian dairy cattle population.

• Korean Journal of Animal Reproduction
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• v.10 no.1
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• pp.83-90
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• 1986

This study was conducted to determine the main effects of year, month, sire and parity on certain reproduction and lactation traits on the basis of the data obtained from 1,510 head of Holstein cows at National Animal Breeding Institute from 1971 to 1981. The results obtained in this study are summarized as follows; 1. The conception interval and number of services per concetption were 124.10 days and 2.19 times, respectively. The effects of year, month and sire on the above traits were significant. 2. The birth weight and gestation length were 42.20kg and 281.52 days, respectively. The effects of year, month and parity on the birth weight, and year, sire and parity on gestation length were significant. 3. The yields of milk and milk fat in 305 days, and the fat percent were 4937.05kg, 174.43kg and 3.56%, respectively. The effects of year, month, sire and parity on the above traits were significant. 4. The peak yield and days reaching the peak yield were 26.46kg and 49.17 days, respectively. The effects of the sire and parity on above traits were significant.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.1
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• pp.1-5
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• 2008

To analyze genetic effects on milk production traits, 164 unrelated Italian Jersey cows reared in 15 farms located in Southern Italy were characterized at the growth hormone locus. Using a Polymerase Chain Reaction-Restriction Fragment Length Polymorphism protocol all three possible genotypes for the Leucine/Valine polymorphism were identified even if in the considered population the number of homozygous animals (Leucine/Leucine = 36; Valine/Valine = 28) was smaller than Leucine/Valine (n = 100) cows; the Hardy-Weinberg equilibrium was verified. Statistical analysis showed that daily milk yield in the Leucine/Leucine genotype was higher (p<0.01) than in Leucine/Valine (22.76 kg vs. 16.96 kg ); cows with Leucine/Valine genotype differed significantly from Leucine/Leucine and Valine/Valine genotypes particularly in fat (4.95% vs. 4.13% and 4.82%, respectively) and protein content (4.00% vs. 3.47% and 3.79%, respectively). No significant effect on lactation length was observed.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.3
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• pp.311-317
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• 1998

A total of 1033 Brown Swiss and 610 Canadienne cows were phenotyped for the genetic variants ${\alpha}_{s1}$-casein, ${\beta}$-casein, ${\kappa}$-casein, ${\beta}$-lactoglobulin and ${\alpha}$-lactalbumin. In Brown Swiss, frequency distributions were: 97.3% B and 2.7% C variant of ${\alpha}_{s1}$-casein; 31.6% $A^1$, 51.8% $A^2$, 0.5% $A^3$ and 16.1% B variant of ${\beta}$-casein; 70.4% A, 29.3% B, and 0.3% C variant of ${\kappa}$-casein; 41.7% A and 58.3% B variant of ${\beta}$-lactoglobulin; and 100% B variant of ${\alpha}$-lactalbumin. Corresponding frequencies in Canadienne for those five milk proteins were: 98.6 and 1.4%;58.5, 33.5, 0.08 and 7.9%; 78.8, 21.1 and 0.1%, 42.4 and 57.6%; and 100%. Analysis of variance by least squares showed possible association between milk protein phenotypes and some lactational production traits. There were no significant association of phenotypes of ${\alpha}_{s1}$-casein, ${\beta}$-casein and ${\beta}$-lactoglobulin with milk yield, fat yield, protein yield, fat percentage and protein percentage in both breeds during the three lactations. In the Brown Swiss, ${\kappa}$-casein phenotype was associated with 305-day fat yield and protein yield during the first lactation. ${\kappa}$-Casein AB was associated with higher milk, fat and protein yield during the second lactation. During the third lactation, ${\beta}$-lactoglobulin AA in Canadienne cows was associated with higher protein content in the milk (3.70%) when compared to phenotypes AB (3.54%) and BB (3.64%).

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.5
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• pp.661-668
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• 2007

Data on 1,037 Nili-Ravi buffaloes from four institutional herds were used to study lifetime milk yield, herd life, productive life and breeding efficiency. A general linear model was used to study the environmental effects while an animal model having herd, year of birth and age at first calving (as covariate) along with random animal effect was used to estimate breeding values. The lifetime milk yield, herd life, productive life and breeding efficiency averaged $7,723{\pm}164$ kg, $3,990{\pm}41$ days, $1,061{\pm}19$ days and 64 percent, respectively. All the traits were significantly (p<0.01) affected by the year of birth and herd of calving, while the herd life was also affected (p<0.01) by the age at first calving. The heritabilities for lifetime milk yield, herd life, productive life and breeding efficiency were $0.093{\pm}0.056$, $0.001{\pm}0.055$, $0.144{\pm}0.079$ and 0.001, respectively. The definition for productive life, where each lactation gets credit upto 10 months had slightly better heritability and may be preferred over the definition where no limit is placed on lactation length. The genetic correlation between productive life and lifetime milk yield was low but high between productive life and herd life. The selection for productive life will increase herd life while lifetime milk yield will also improve. The overall phenotypic trend during the period under the study was negative for lifetime milk yield (-280 kg/year), herd life (-93 days), productive life (-42 days/year) and breeding efficiency (-0.36 percent/year), whereas the genetic trend was positive for lifetime milk yield (+15 kg/year) and productive life (+4 days/year).