• 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.

• 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.7 no.2
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• pp.239-248
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• 1994

To study the relationship between certain hormones and metabolites and between hormones and milk yield during different stage of lactation, six lactating Karan Swiss cows and six Murrah buffaloes were maintained. Growth hormone, insulin, $T_3$, $T_4$, glucose, BHBA, NEFA and milk yield were studied. Highly negative relationship of growth hormone with insulin and triiodothyronine in cows and marginally negative in buffaloes suggest that insulin and triiodothyronine aid in the process of partitioning of nutrients towards milk production through reducing the demands of nutrients by peripheral tissue. The significant and negative correlation of growth hormone with dry matter intake in both the species suggest that the availability of nutrients from the digestive tract play a role in the regulation of growth hormone secretion. Positive relationship of growth hormone with non esterified fatty acids in both the species suggest that high growth hormone levels may result in fat mobilization and thereby increase the availability of energy precursors for milk synthesis. Insulin was negatively correlated with milk yield and lactose content and positively with milk fat and protein but the degree of relationship varied. In both the species the relationship between triiodothyronine and milk yield was negative and between thyroxine and milk yield was positive. However, it was significant only in cows and not in buffaloes. Thyroxine was positively correlated with beta-hydroxybutyrate and non-esterified fatty acids with milk yield in both the species.

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.3
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• pp.217-233
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• 1998

Milk yield and its composition is governed by level of nutrition and the composition of diet. Higher concentrate input improves milk yield, whereas its input at moderate levels improves yield of milk fat. High level of dietary protein improves dry matter intake and milk production, however, CP content above 14% has less advantage. Milk yield is enhanced by the feeding of cottonseed and soyabean meal, whereas milk fat increases by the supplementation of cottonseed. Dietary fat increases energy intake, production of milk and milk fat. Quality and quantity of feeds consumed affect fermentation patterns in rumen. Among the rumen metabolites, volatile fatty acids (VFA) content and propionate proportion have been related positively with milk yield, whereas proportion of acetate and butyrate have been related positively with milk fat content. Dietary carbohydrates through the source of sugar, starch, roughage and fibre affect VFA concentration in rumen. Therefore, concentration of volatile fatty acids could be altered to the advantage of consumer through judicious manipulation of diet.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.725-730
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• 2003

This study was conducted to evaluate the adequacy of an alternative a.m.-p.m. testing scheme for milk yield in comparison with the official test method based on weighing two milkings within 24 h. A total of 8,309 p.m. milking weights and 6,767 a.m. milking weights from 72 Holstein cows raised at N.L.R.I. were collected between October 2000 and November 2001. Ratios were computes for daily milk yield to a.m. and p.m. milking weights(direct yield ratios) and ratios of a.m. and p.m. milking weights to daily milk yield (inverse yield ratios). Analysis of variance indicated that the milking interval is the most important source of variation for yield ratios. Adjustment factors for estimating daily milk yield from single milking weights were derived through regression analysis of direct and inverse yield ratios on the length of the milking interval. Daily milk yield was estimated more precisely and accurately when adjustment factors were used than when single milking weights were doubled. In conclusion, alternative recording of a.m. and p.m. milking weights led to reliable estimates of milk yields.

• Asian-Australasian Journal of Animal Sciences
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• v.19 no.7
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• pp.915-921
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• 2006

Various random regression models with different order of Legendre polynomials for permanent environmental and genetic effects were constructed to predict future milk yield of Holstein cows in Korea. A total of 257,908 test-day (TD) milk yield records from a total of 28,135 cows belonging to 1,090 herds were considered for estimating (co)variance of the random covariate coefficients using an expectation-maximization REML algorithm in an animal mixed model. The variances did not change much between the models, having different order of Legendre polynomial, but a decreasing trend was observed with increase in the order of Legendre polynomial in the model. The R-squared value of the model increased and the residual variance reduced with the increase in order of Legendre polynomial in the model. Therefore, a model with $5^{th}$ order of Legendre polynomial was considered for predicting future milk yield. For predicting the future milk yield of cows, 132,771 TD records from 28,135 cows were randomly selected from the above data by way of preceding partial TD record, and then future milk yields were estimated using incomplete records from each cow randomly retained. Results suggested that we could predict the next four months milk yield with an error deviation of 4 kg. The correlation of more than 70% between predicted and observed values was estimated for the next four months milk yield. Even using only 3 TD records of some cows, the average milk yield of Korean Holstein cows would be predicted with high accuracy if compared with observed milk yield. Persistency of each cow was estimated which might be useful for selecting the cows with higher persistency. The results of the present study suggested the use of a $5^{th}$ order Legendre polynomial to predict the future milk yield of each cow.

• Asian-Australasian Journal of Animal Sciences
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• v.7 no.2
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• pp.231-237
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• 1994

Three concentrations of P (0.33, 0.43 and 0.54%) and two concentrations of Ca (0.60 and 0.97%) in ration dry matter were evaluated for effects on dry matter intake and on milk yield and composition using 24 Holstein cows. Cows were arranged in a $3{\times}2$ factorial experiment as an incomplete randomized block design with three 28-day periods. Each cow consumed at least one ration with each concentration of Ca. Dry matter intake, yield of 3.5% Fat Corrected Milk, and milk composition were not affected by concentration of P, but milk yield was greater when lowest concentration of P was fed (22.8 vs. 22.1 kg/day; p<0.07). Cows fed rations containing 0.60% Ca had greater milk (22.7 vs. 21.9 kg/day; p<0.02) and 3.5% Fat Corrected Milk yields (p<0.03) and slightly greater protein content than when fed 0.97% Ca. Dietary Ca:P ratios between 1.1:1 and 2.9:1 had no effect on dry matter intake, milk yield, or composition. Concentrations of P in plasma were within the normal range for all rations. Because cows had high dry matter intake, mean daily intakes of both P and Ca were greater than required for their level of milk yield.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.1
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• pp.92-95
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• 2001

The Baghabarighat Milk Shed Area (BMSA), in Bangladesh belonging to the Bangladesh Milk Producers Cooperative Union Limited (BMPCUL) was selected to study the qualitative and quantitative aspects of dairy milk and to establish a trend throughout the year (July 1995 to June 1990) of milk collected at morning and evening, and daily. The average fat, solids-not-fat (SNF) and total solid (TS) contents of the morning milk were 4.58, 7.75 and 12.33%, respectively, and evening milk contained 5.41, 7.81 and 13.23%. The values for the quality varied (p<0.01) throughout the year without a specific trend. Higher milk collection occured at morning (52.77%) than evening (47.24%), but total yield of fat from morning milk was lower (48.74%) than evening milk (51.26%) due to a lower fat value (4.58%). Yield of SNF (52.57% morning, 47.37% evening) followed the values of the amount of milk collected due to their similar value at morning (7.75) and evening (7.81). Overall, TS yield was 51 and 49% from morning and evening. There was not a significant (p>0.01) relationship between fat and TS values of morning milk with those of evening milk, but there was a correlation (p<0.01) between milk yield at morning and all other parameters for evening. Solids-not-fat value of morning milk was related with yield and SNF value of milk from evening, but not with fat and TS evening milk. It may be concluded that evening milk contains higher amounts of fat, SNF and TS, but yields were higher at morning, except fat. Milk collected at morning showed a relationship with all the parameters found at evening.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.6
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• pp.567-570
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• 1997

A multiple trait animal model having milk yield and lactation length was used to estimate genetic parameters using data from four institutional herds and four field recording centers. Response to selection for milk yield alone and in combination with lactation length was estimated by using principles of genetic theory. Lactation records (n = 2,353) adjusted for age at calving to 60 months were utilized. Milk yield was 17% heritable with repeatability of 0.44. Lactation length had a low heritability of 0.06 with repeatability of 0.16. Genetic correlation between the two traits was 0.70. Selection response in milk yield can be improved slightly (103.8 vs 102.8 kg) when information on covariance with lactation length is used together with the information on milk yield.