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Modelling temperature effects on milk production: a study on Holstein cows at a Japanese farm.

ABSTRACT: Milk yield and its composition vary according to individual cows as well as to a variety of different environment conditions, such as temperature. Previous studies suggest that heat exerts considerable negative effects on milk production and its composition, especially during summer months. We investigate the production and fat composition of milk from individual dairy cows and develop a modelling framework that investigates the effect of temperature by extending a traditional lactation curve model onto a more flexible statistical modelling framework, a generalised additive model (GAM). The GAM simultaneously copes with multiple different conditions (temperature, parity, days of lactation, etc.), and, importantly, their non-linear relationships. Our analysis of retrospective data suggests that individual cows respond differently to heat; cows producing relatively high quantities of milk tend to be particularly sensitive to heat. Our model also suggests that most dairy cows studied fall into three distinct cases that underpin the variation of the milk fat ratio by different mechanisms.

SUBMITTER: Yano M

PROVIDER: S-EPMC3979979 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Modelling temperature effects on milk production: a study on Holstein cows at a Japanese farm.

Yano Machiko M Shimadzu Hideyasu H Endo Toshiki T

SpringerPlus 20140307

Milk yield and its composition vary according to individual cows as well as to a variety of different environment conditions, such as temperature. Previous studies suggest that heat exerts considerable negative effects on milk production and its composition, especially during summer months. We investigate the production and fat composition of milk from individual dairy cows and develop a modelling framework that investigates the effect of temperature by extending a traditional lactation curve mo ...[more]

PMID: 24741472

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Project description:Milk oligosaccharides (MOs) can be prebiotic and antiadhesive, while fatty acids (MFAs) can be antimicrobial. Both have been associated with milk microbes or mammary gland inflammation in humans. Relationships between these milk components and milk microbes or inflammation have not been determined for cows and could help elucidate a novel approach for the dairy industry to promote desired milk microbial composition for improvement of milk quality and reduction of milk waste. We aimed to determine relationships among milk microbiota, MFAs, MOs, lactose, and somatic cell counts (SCC) from Holstein cows, using our previously published data. Raw milk samples were collected at three time points, ranging from early to late lactation. Data were analyzed using linear mixed-effects modeling and repeated-measures correlation. Unsaturated MFA and short-chain MFA had mostly negative relationships with potentially pathogenic genera, including Corynebacterium, Pseudomonas, and an unknown Enterobacteriaceae genus but numerous positive relationships with symbionts Bifidobacterium and Bacteroides. Conversely, many MOs were positively correlated with potentially pathogenic genera (e.g., Corynebacterium, Enterococcus, and Pseudomonas), and numerous MOs were negatively correlated with the symbiont Bifidobacterium. The neutral, nonfucosylated MO composed of eight hexoses had a positive relationship with SCC, while lactose had a negative relationship with SCC. One interpretation of these trends might be that in milk, MFAs disrupt primarily pathogenic bacterial cells, causing a relative increase in abundance of beneficial microbial taxa, while MOs respond to and act on pathogenic taxa primarily through antiadhesive methods. Further research is needed to confirm the potential mechanisms driving these correlations. IMPORTANCE Bovine milk can harbor microbes that cause mastitis, milk spoilage, and foodborne illness. Fatty acids found in milk can be antimicrobial and milk oligosaccharides can have antiadhesive, prebiotic, and immune-modulatory effects. Relationships among milk microbes, fatty acids, oligosaccharides, and inflammation have been reported for humans. To our knowledge, associations among the milk microbial composition, fatty acids, oligosaccharides, and lactose have not been reported for healthy lactating cows. Identifying these potential relationships in bovine milk will inform future efforts to characterize direct and indirect interactions of the milk components with the milk microbiota. Since many milk components are associated with herd management practices, determining if these milk components impact milk microbes may provide valuable information for dairy cow management and breeding practices aimed at minimizing harmful and spoilage-causing microbes in raw milk.

Project description:Milk production traits are the most important quantitative economic traits in dairy cow production; improving the yield and quality of milk is an important way to ensure the production efficiency of the dairy industry. This study carried out a series of in-depth statistical genetics studies and molecular analyses on the Chinese Holstein cows in the Jiangsu Province, such as descriptive statistics and copy number variation analysis. A genetic correlation, phenotypic correlation, and descriptive statistical analysis of five milk production traits (milk yield, milk fat percentage, milk fat yield, milk protein percentage, and milk protein yield) of the dairy cows were analyzed using the SPSS and DMU software. Through quality control, 4173 cows and their genomes were used for genomic study. Then, SNPs were detected using DNA chips, and a copy number variation (CNV) analysis was carried out to locate the quantitative trait loci (QTL) of the milk production traits by Perl program software Penn CNV and hidden Markov model (HMM). The phenotypic means of the milk yield, milk fat percentage, milk fat mass, milk protein percentage, and milk protein mass at the first trimester were lower than those at the other trimesters by 8.821%, 1.031%, 0.930%, 0.003%, and 0.826%, respectively. The five milk production traits showed a significant phenotypic positive correlation (p < 0.01) and a high genetic positive correlation among the three parities. Based on the GGPBovine 100 K SNP data, QTL-detecting research on the fist-parity milk performance of dairy cows was carried out via the CNV. We identified 1731 CNVs and 236 CNVRs in the 29 autosomes of 984 Holstein dairy cows, and 19 CNVRs were significantly associated with the milk production traits (p < 0.05). These CNVRs were analyzed via a bioinformatics analysis; a total of 13 gene ontology (GO) terms and 20 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched (p < 0.05), and these terms and pathways are mainly related to lipid metabolism, amino acid metabolism, and cellular catabolic processes. This study provided a theoretical basis for the molecular-marker-assisted selection of dairy cows by developing descriptive statistics on the milk production traits of dairy cows and by locating the QTL and functional genes that affect the milk production traits of first-born dairy cows. The results describe the basic status of the milk production traits of the Chinese Holstein cows in Jiangsu and locate the QTL and functional genes that affect the milk production traits of the first-born cows, providing a theoretical basis for the molecular-marker-assisted selection of dairy cows.

Dataset Information

Modelling temperature effects on milk production: a study on Holstein cows at a Japanese farm.

Publications

Modelling temperature effects on milk production: a study on Holstein cows at a Japanese farm.

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