• Asian-Australasian Journal of Animal Sciences
• /
• v.19 no.7
• /
• pp.915-921
• /
• 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
• /
• v.25 no.9
• /
• pp.1338-1350
• /
• 2012

This review focuses on the nutritional effects from birth until age at first calving on growth, mammary developmental changes, and first-lactation milk yield in heifer calves. The advancement in the genetic potential and the nutritional requirements of the animals has hastened the growth rate. Genetic selection for high milk yield has suggested higher growth capacity and hence increasing nutritional inputs are required. Rapid rearing by feeding high energy or high concentrate diets not only reduces the age of sexual maturity but also lowers the time period of attaining the age of first calving. However, high energy diets may cause undesirable fat deposition thereby affecting future milk yield potential. Discrepancies exist whether overfed or overweight heifers at puberty can influence the mammary development and future milk yield potential and performance. The data on post-pubertal nutritional management suggested that body weight at calving and post-pubertal growth rate is important in first lactation milk yield. There is a continuous research need for strategic feeding that accelerates growth of dairy heifers without reduction in subsequent production. Nutritional management from birth, across puberty and during pregnancy is critical for mammary growth and for producing a successful cow. This review will mostly highlight studies carried out on dairy breeds and possible available opportunities to manipulate nutritional status from birth until age at first calving.

• Asian-Australasian Journal of Animal Sciences
• /
• v.30 no.8
• /
• pp.1093-1098
• /
• 2017

Objective: The aim of the current study was to describe the relationship between milk yield and lactation number, stage, length and milking frequency in Korean Holstein dairy cows using an automatic milking system (AMS). Methods: The original data set consisted of observations from April to October 2016 of 780 Holstein cows, with a total of 10,751 milkings. Each time a cow was milked by an AMS during the 24 h, the AMS management system recorded identification numbers of the AMS unit, the cow being milking, date and time of the milking, and milk yield (kg) as measured by the milk meters installed on each AMS unit, date and time of the lactation, lactation stage, milking frequency (NoM). Lactation stage is defined as the number of days milking per cows per lactation. Milk yield was calculated per udder quarter in the AMS and was added to 1 record per cow and trait for each milking. Milking frequency was measured the number of milkings per cow per 24 hour. Results: From the study results, a significant relationship was found between the milk yield and lactation number (p<0.001), with the maximum milk yield occurring in the third lactation cows. We recorded the highest milk yield, in a greater lactation length period of early stage (55 to 90 days) at a $4{\times}$ milking frequency/d, and the lowest milk yield was observed in the later stage (>201 days) of cows. Also, milking frequency had a significant influence on milk yield (p<0.001) in Korean Holstein cows using AMS. Conclusion: Detailed knowledge of these factors such as lactation number, stage, length, and milking frequency associated with increasing milk yield using AMS will help guide future recommendations to producers for maximizing milk yield in Korean Dairy industries.

• Animal Bioscience
• /
• v.34 no.9
• /
• pp.1466-1478
• /
• 2021

Objective: Ruminants are completely dependent on their microbiota for rumen fermentation, feed digestion, and consequently, their metabolism for productivity. This study aimed to evaluate the rumen bacteria of lactating yaks with different milk protein yields, using high-throughput sequencing technology, in order to understand the influence of these bacteria on milk production. Methods: Yaks with similar high milk protein yield (high milk yield and high milk protein content, HH; n = 12) and low milk protein yield (low milk yield and low milk protein content, LL; n = 12) were randomly selected from 57 mid-lactation yaks. Ruminal contents were collected using an oral stomach tube from the 24 yaks selected. High-throughput sequencing of bacterial 16S rRNA gene was used. Results: Ruminal ammonia N, total volatile fatty acids, acetate, propionate, and isobutyrate concentrations were found to be higher in HH than LL yaks. Community richness (Chao 1 index) and diversity indices (Shannon index) of rumen microbiota were higher in LL than HH yaks. Relative abundances of the Bacteroidetes and Tenericutes phyla in the rumen fluid were significantly increased in HH than LL yaks, but significantly decreased for Firmicutes. Relative abundances of the Succiniclasticum, Butyrivibrio 2, Prevotella 1, and Prevotellaceae UCG-001 genera in the rumen fluid of HH yaks was significantly increased, but significantly decreased for Christensenellaceae R-7 group and Coprococcus 1. Principal coordinates analysis on unweighted UniFrac distances revealed that the bacterial community structure of rumen differed between yaks with high and low milk protein yields. Furthermore, rumen microbiota were functionally enriched in relation to transporters, ABC transporters, ribosome, and urine metabolism, and also significantly altered in HH and LL yaks. Conclusion: We observed significant differences in the composition, diversity, fermentation product concentrations, and function of ruminal microorganisms between yaks with high and low milk protein yields, suggesting the potential influence of rumen microbiota on milk protein yield in yaks. A deeper understanding of this process may allow future modulation of the rumen microbiome for improved agricultural yield through bacterial community design.

• Asian-Australasian Journal of Animal Sciences
• /
• v.12 no.8
• /
• pp.1316-1323
• /
• 1999

Extensive emphasis on milk and milk fat yields with no diversion for beef performance increased the yield efficiency of North American dairy cattle. Heavy demand for North American genetics followed national strain comparison trials in Poland, and US and Canadian dairy cattle and germplasm still are an important source of genetics for many countries. Genetic improvement has accelerated in many countries because of the implementation of sampling programs for young bulls and improved evaluation procedures. Rapid access to information and more frequent calculation of genetic information also are having a positive impact on genetic improvement. Traits other than yield should be considered in a breeding program, but those traits mist have a reasonable opportunity for improvement and sufficient economic worth. Because of ever increasing efficiency, the world's milk supply comes from fewer cows each year. However, no decline in the rate of genetic improvement is apparent under current genetic practices; estimates of heritability are increasing, and a decline in yield efficiency is unlikely in the near future. As management improves, especially for subtropical conditions, many of the selection principles used in temperate climates will be adopted for more adverse environmental conditions.

• Asian-Australasian Journal of Animal Sciences
• /
• v.11 no.5
• /
• pp.580-585
• /
• 1998

The study was conducted to determine if variation in protein yield can be explained by expressions of early lactation somatic cell score (SCS) and if prediction can be improved by including SCS among the predictors. A data set was prepared (n = 663,438) from Wisconsin Dairy Improvement Association (USA) records for protein yield with sample days near 20. Stepwise regression was used requiring F statistic (p < .01) for any variable to stay in the model. Separate analyses were run for 12 combinations of four seasons and first three parities. Selection of SCS variables was not consistent across seasons or lactations. Coefficients of detennination ($R^2$) ranged from 51 to 61% with higher values for earlier lactations. Including any expression of SCS in the prediction equations improved $R^2$ by < 1 %. SCS was associated with milk yield on the sample day, but the association was not strong enough to improve the prediction of future yield when other expressions of milk yield were in the model.

• Asian-Australasian Journal of Animal Sciences
• /
• v.11 no.2
• /
• pp.117-120
• /
• 1998

Relationships of breeding values of sires for first lactation milk yield with pedigree information or indices were examined to identify the optimal criteria of selecting young dairy bulls for future use in artificial insemination (AI). Records of performance data on 1087 crossbred daughters (Holstein - Friesian, Jersey and Brown Swiss with Hariana) of 147 sires, generated at Livestock Production Research (Cattle and Buffaloes) Farm, IVRI, Izatnagar, U.P., during 1972 - 1995 were used to obtain the estimates of sire's breeding values (EBV) using the Best Linear Unbiased Prediction Procedures. The correlations between young bull's EBV and the dam's first lactation milk yield was non-significantly different from zero. However, the young bull's EBV was negatively and significantly related (r = - 0.275 ; P < 0.05) to the dam's best lactation milk yield, suggesting that the selection of young dairy bulls from high yielding elite dams is not a suitable criteria for genetic improvement. The correlations of sire's and paternal grandsire's EBV's with young bull's EBV were high and positive (0.532, 0.844; P < 0.01). The maternal grandsire's EBV was positively but non-significantly related to grandson's EBV. The pedigree index incorporating dam's milk records and sire's EBV's showed a negative and non-significant correlation with young bull's EBV. However, the correlation of a pedigree index $(I_3)$ combining information on sire's and paternal grand-sire's EBV's with young bull's EBV's was considerably high and positive (0.797; P < 0.01). The regression coefficients of young bull's EBV on pedigree index $I_3$, was higher than those on other pedigree information. These results revealed that there was no advantage in basing selection on dam's performance or maternal grand-sire's EBV and that sire's and paternal grandsire's EBV's were reliable pedigree information for selection of young dairy bulls for future use in AI.

• Animal Bioscience
• /
• v.37 no.4
• /
• pp.576-590
• /
• 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
• /
• v.19 no.9
• /
• pp.1252-1256
• /
• 2006

This study estimated the effects of parity (1-3) and stage of lactation (early, mid and late) on daily milk yield (DMY), somatic cell score (SCS), milk urea nitrogen (MUN), blood glucose, and immunoglobulin G (IgG), their heritabilities and genetic correlations between them in Holsteins (n = 200). Means and standard deviations of DMY, SCS, MUN, blood glucose, and IgG in the experimental herd were $23.35{\pm}7.75kg$, $3.81{\pm}2.00$, $13.99{\pm}5.68mg/dl$, $44.91{\pm}13.12mg/dl$, and $30.36{\pm}6.72mg/ml$, respectively. DMY was the lowest in first parity, and in late lactation. SCS increased with parity; however, it was lowest in mid-lactation. MUN was lowest in first parity, and no difference was noted across stage of lactation. Blood glucose was similar between parities, however the highest blood glucose was observed during mid lactation. IgG level was significantly different between first and second parity; however, stage of lactation did not affect its level. Heritability of DMY was 0.16. Its genetic correlations with SCS and with blood glucose were -0.67 and 0.98, respectively. Heritability of SCS was 0.15. Genetic correlations of SCS with MUN, glucose, and IgG were -0.72, -0.59, and 0.68, respectively. Heritability of MUN was estimated to be 0.39 and had a genetic correlation of -0.35 with IgG. Heritabilities of blood glucose and IgG were 0.21 and 0.33, respectively. This study suggested that MUN, blood glucose and IgG could be considered important traits in future dairy selection programs to improve milk yield and its quality with better animal health and welfare. However, further studies are necessary involving more records to clarify the relationship between metabolic and immunological traits with DMY and its quality.

• Journal of Animal Environmental Science
• /
• v.15 no.1
• /
• pp.29-36
• /
• 2009

The authors of this study have developed a robot milking system composed of a multi-articular manipulator, a teat-cup attachment system, and an image processing system. In order to verify the efficacy of this system, we have conducted a performance analysis and measurement experiment of milk yield, using dairy cattle. It was concluded that teat recognition using the image processing system, teat-cup attachment, and detachment system did not binder milking. The milking yield of the robot milking system was analyzed based on a lactation curve. As a result, it was determined that the use of a robot milking system had no significant effects on milking yields. The robot milking system described in this study is designed specifically with a focus on teat-cup attachment and detachment performance, as well as the effect of these factors on milking yield. In the future, in-depth studies regarding the washing of the teats prior to milking, teat massage, pre-treatment and post-treatment processes after milking, and disinfection processes shall be conducted, in order to render this system feasible for use in an actual milking parlor.