中国北方荷斯坦奶牛乳成分及相关指标的季节性与胎次变化规律研究  

Study on Seasonal and Parity Variation Characteristics of Raw Milk Composition and Related Traits of Chinese Holstein in the North of China

作　　者：熊本海[1,2] 易渺[1,2] 杨琴[1,2] 庞之洪[1,2] 杨亮[1,2] 

机构地区：[1]中国农业科学院北京畜牧兽医研究所 [2]中国饲料数据库情报网中心,北京100193

出　　处：《畜牧兽医学报》2013年第1期31-37,共7页ACTA VETERINARIA ET ZOOTECHNICA SINICA

基　　金："973"基础研究课题(2011CB100805);"863"研究团队任务(2012AA101905-01)

摘　　要：为满足对奶牛饲养管理的季节性及胎次调控,探索乳成分及相关指标的变化规律,基于中国北方荷斯坦泌乳奶牛群的DHI测定数据及派生数据,按胎次及自然月份对DHI原始数据进行分组,剔除异常数据后获得包括乳产量(DMP)、乳干物质率(MSP)、乳脂率(MFP)、乳蛋白率(MPP)、乳糖率(MLP)、体细胞数(SCC)、体况评分(BCS)、奶损失量(LMP)及脂肪蛋白比(FPR)等9项指标的完整观察数据6 520套,以自然月份、胎次及两者的互作作为影响上述指标变化的因素,SAS软件GLM过程进行的方差分析表明:自然月份及胎次分别极显著或显著影响9项观察指标(P<0.000 1,或P<0.001,或P<0.05)。但是,两者的互作对MFP、MPP、MSP、SCC及FPR的变化影响不显著(P>0.05),对DMP影响极显著(P<0.000 1),对MLP、BCS及LMP影响显著(P<0.05)。进行牛群自然月份下乳成分的Duncan多重比较显示,DMP、MSP、MPP及MFP均在6月份表现最低,依次为23.58kg·d-1,12.35%,3.02%及3.81%。SCC在8月份达到最高(385.3×1 000.mL-1),而LMP在11月份最高(1.12kg·d-1)。FPR在2月份最高(1.32),预示着该月份奶牛在快速动用体脂。进行牛群不同胎次性状指标的多重比较表明,MSP、MPP及MLP到第4胎显著下降(P<0.05),而SCC在第4胎显著上升,LMP也随胎次显著增加(P<0.05),意味着随着胎次增加,乳的品质逐渐下降,乳品的卫生指标随之恶化,LMP在增加。其次,对9项指标的典型相关分析表明,BCS与SCC、LMP呈高度正相关(0.830 6,0.836 0),而SCC与LMP也表现高度相关(0.786 1)。最后,利用Wood模型,建立了不同胎次混合牛群的乳干物质率(MSP)及乳糖率(MLP)与自然月份之间的关系方程(MSP=12.862x-0.031 7*e0.004 59x,MLP=4.982 4x-0.019 6*e0.001 06x,式中x代表月份)。通过数据挖掘获得的乳成分及相关性状在自然月份及不同胎次之间的变化规律及模型,为准确调控牛群的饲养管理和营养供给提供了决策依据。To meet the seasonal regulation of production management and to explore the variation features of milk compositions and some related traits, based on the DHI data and derived data of Chinese Holstein lactating cows in the north of China, the data were grouped by parities and the natural months and the abnormal ones are deleted to obtain complete data 6 520 sets which con- tain 9 traits-daily milk yield（DMP）, milk solid percentage（MSP）, milk fat percentage（MFP）, milk protein percentage（MPP）, milk lactose percentage（MLP）, somatic cell count（SCC）, body condition score（BCS）, lossed milk production（LMP） and fat-to-protein rate（FPR）. The naturalmonth, parity and their interaction were assumed as factors affecting the 9 traits. A GLM vari- ance analysis method of SAS software showed that both of the natural months and lactation pari- ties affected the above 9 traits significantly （P〈0. 000 1, or P〈0. 001, or P〈0.05）. However, the interaction between parities and the natural months showed no significant effect on MFP, MPP, MSP, SCC and FPR（P〉0.05）while their interaction showed significant effect on DMP （P〈0.000 1）, MLP, BCS and LMP（P〈0.05）. The Duncan multiple comparison of natural months showed that DMP（23.58 kg·d-l）, MSP（12.35%）, MPP（3. 02%） and MFP（3.81%） all were the lowest in June and SCC was the highest （385.2×1 000· mL- 1） in August and LMP was the highest （1.12 kg · d-1） in November and FPR was the highest （1.32） in February which means the cows consumed the body fat quickly. The Duncan multiple comparison of parity showed that MSP, MPP and MLP dropped rapidly in parity 4 （P〈O. 05）. The SCC went up significantly in parity 4 and LMP increased significantly following the parity （P〈O. 05）, and this means that the quality of the milk and sanitation indexes of milk production deteriorated and the milk loss pro- duction increased following the parity. Secondly, the canonical correlation analysis of the 9 traits s

关 键 词：荷斯坦奶牛 乳成分 自然月份 胎次 模型 

分 类 号：S823[农业科学—畜牧学] S813.1[农业科学—畜牧兽医]