Variation Regulation and Models of Raw Milk Composition of Chinese Holstein Cattle in Tianjin

Liang Yang, Yi Ma, Zhihong Pang, Miao Yi, Qin Yang and Benhai Xiong

Asian Agricultural Research, 2013, vol. 05, issue 07, 5

Abstract: Based on raw milk DHI data of Chinese Holstein cattle in northern China, milk composition (milk protein percentage and milk fat percentage) of lactating cow is grouped into parity 1 to 4. After preprocessing original data, 6114 data records of milk protein percentage and 5871 data records of milk fat percentage were obtained. This study discusses effects of natural months, lactation parity and their interaction on changes of milk protein percentage and milk fat percentage, and the model is established using GLM procedure of SAS software. At last, results are as follows: (1) Duncan multiple comparison of natural months, regardless of parity (only parity 1 to 4), indicated that milk composition takes on significant difference between different months (P＜0.05). And milk protein percentage reaches highest in September (3.187%), drops to the lowest in July (3.016%); the milk fat percentage reaches highest in February (4.137%), and drops to the lowest in July (3.845%). (2) Duncan multiple comparison of different parity, regardless months (January to December), shows that milk composition of different parity also takes on significant difference (P＜0.05) although the difference between parities are not significant; milk protein percentage reaches highest point in the 2nd parity (3.114%) and drops to the lowest in the 4th parity (3.066%); milk fat percentage reaches highest in the 2nd and 3rd parity (3.983% and 3.973%), and drops to the lowest in the 4th parity (3.923%). (3) Using Wood model, the relational expression between milk protein percentage (MPP, %) and milk fat percentage (MFP, %) of different parity and natural month, i.e. MPP=3.094x-0.0464×e0.0117x , and MFP=4.2116 x-0.0344×e0.0276 x (x stands for month). According to the above results, it is concluded that natural months, lactation parity and their interaction significantly influenced milk protein percentage and milk fat percentage (P＜0.001), and milk protein percentage and milk fat percentage take on Wood model change characteristics with natural months respectively. This study is intended to explore change regulation of milk composition, and to provide decision reference for properly regulating feeding management and nutrition supply of cattle, and thereby guaranteeing the quality of raw milk in certain month reach sales standard.

Keywords: Agribusiness (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:ags:asagre:155875

DOI: 10.22004/ag.econ.155875

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