天津市中国荷斯坦奶牛乳成分变化规律及模型

目的]为满足对奶牛饲养管理的季节性调控,探索乳成分的变化规律.方法]基于中国北方荷斯坦泌乳奶牛牛群生乳DHI测定数据,按第1胎到第4胎对泌乳奶牛的乳成分(乳蛋白率、乳脂肪率)进行分组,将原始数据经过预处理后获得乳蛋白率观察数据6 114个,乳脂肪率观察数据5 871个；假设以自然月份、泌乳胎次及两者的互作作为影响乳蛋白率及乳脂肪率变化的因素,采用SAS软件的GLM过程,建立统计分析模型.结果]①在不分胎次(仅对1-4胎)对牛群自然月份乳成分的Duncan多重比较显示,不同月份之间的乳成分数据总体呈现显著差异(P＜0.05)(尽管有些月份之间的数据差异不显著)；乳蛋白率在9月最高(3.187％),在7月最低(3.016％)；乳脂肪率在2月最高(4.137％),在7月最低(3.845％)；②在不分月份(1-12个月)对牛群不同胎次乳成分的Duncan多重比较显示,不同胎次之间乳成分数据也呈现显著差异(P＜0.05)(尽管有些胎次之间的数据差异不显著)；乳蛋白率在第2胎最高(3.114％),在第4胎最低(3.066％)；乳脂肪率在第2和第3胎分别达到最高(3.98 3％和3.973％),在第4胎最低(3.923％)；③利用wood模型,建立了不同胎次混合牛群的乳蛋白率(MPP,％)及乳脂肪率(MFP,％)与自然月份之间的关系方程,即MPP=3.094x-0.0464× e0.0117x和MFP=4.2116x-0.0344×e0.0276x(x代表月份).结论]自然月份、泌乳胎次及两者的互作均极显著影响乳蛋白率及乳脂肪率(P＜0.001),而且乳蛋白率及乳脂肪率分别与自然月份存在wood模式的变化规律.获得的研究结果为准确调控牛群的饲养管理和营养供给,保证在特定月份的生乳品质达到收购标准提供了决策依据.

Study on Variation Characteristics of Raw Milk Composition and Curve Models of Chinese Holstein in the City of Tianjin

【Objective】 To fulfill the need of seasonal management modification of lactating cows. 【Method】 the effect of natural month, parity, and their interaction on milk components were analyzed in the present study. Data were collected from a DHI database of lactating Chinese Holstein cows in the north part of china. Original data were screened and group according to parity (1-4). A total of 6114 milk protein content records and 5871 milk fat content records were analyzed by GLM procedure of SAS. 【Result】The Duncan multiple comparison of natural months, regardless of parity (only parity 1 to 4), demonstrated that the milk compositions of different months showed significant difference (P＜0.05), although the data between some different months showed no significant difference. The milk protein percentage in September reached the highest (3.187%), and in July the lowest (3.016%). Milk fat percentage in February was the highest (4.137%), and in July the lowest (3.845%).The same multiple comparison of different parity, also regardless of different months (1-12 months), demonstrated that the milk composition data of different parities showed significant difference (P＜0.05), although the data between some parities showed no significant difference. The milk protein percentage reached the highest in parity 2 (3.114%), and the lowest in parity 4 (3.066%). The milk fat percentage reached highest in parity 2 (3.983%) and parity 3 (3.973%), respectively; and the lowest in parity 4 (3.923%). In addition, the relation equation between the milk protein percentage (MPP, %) or the milk fat percentage (MFP, %) of different parities and the natural months in mixed cow herd was built using Model Wood, i.e. MPP=3.094x-0.0464×e0.0117x, MFP=4.2116x-0.0344×e0.0276x, x as month. 【Conclusion】The natural months, milking parities and their interaction had significant affects on milk composition including milk protein percentage and milk fat percentage, and milk composition had wood pattern changing relationship with natural months respectively.