牛场奶牛乳房炎的发病因素探究及其判别分析方程的建立

The establishment of discriminant analysis equation for main cause of mastitis

利用2011年1月至2014年12月山东地区某牛场的奶牛生产性能测定(DHI)数据库及其乳房炎发病记录为数据集,通过sas统计分析软件,对胎次、泌乳天数、采样季节、采样年份、体细胞数、产奶量、乳脂率、乳蛋白率与乳房炎发病记录做逐步判别(Stepdisc)和glm相关性方差分析。结果显示:胎次、泌乳天数、采样季节、采样年份和体细胞数与乳房炎的发生显著相关。因此,综合与奶牛乳房炎发病密切相关的胎次、泌乳天数、采样季节、采样年份和体细胞评分建立了直观、相对准确的判定奶牛乳房炎发生的判别分析方程Y_0(未患乳房炎)和Y_1(患乳房炎),通过比较Y_0和Y_1的大小对未知个体牛是否患有乳房炎做出初步判断。此判断虽然不能对乳房炎的发生做出确诊,但能够帮助奶牛场管理者对奶牛群体进行宏观监测,从奶牛群体中筛选出发生乳房炎概率较大的作为重点监测对象。由此奶牛场能够尽早发现乳房炎,节约乳房炎检测成本,为乳房炎的及时控制与治疗提供科学理论依据,对DHI的推广和DHI报告的充分利用也具有重要意义。

The DHI databases and mastitis records（2011 to 2014） from a farm in Shandong area were used in this s valuate a relation s tudy. GLM correlation analysis using in SAS statistical analysis softwareto ehip between mastitis records and parities, stage of lactation, sample seasons, sample years, milk yield, SCC, milk fat content, milk protein content . The results showed that parity,stage of lactation, sample seasons, sample years and SCC all havd a significant effect on mastitis occurrence. Therefore, the intuitive and relatively accurate discriminant equation Y0 （not suffering from mastitis） and Y1 （mastitis） were established. This equation was combined with parity,stage of lactation,sample seasons,sample years and SCC. Compared with Y0 and Y1 ,we could make a judgment on the unknown individual cows. Although the equation can not make a explicit diagnosis,it is helpful to macro monitoring for the herds. Utilizing the equation, mastitis cases suspicion most will he detected.