【摘要】 本文作者应用不完全函数计算和分析了上海金山县黑白花乳牛175个泌乳期的资料,其结果如下: 1.不完全函数估计的月平均产乳量泌乳曲线与实际泌乳曲线比较,RMS为0.716±0.274公斤,偏差为0.68公斤,误差很小,说明用不完全部函数分析曲线是可行的。 2.模型的各月RMS分布,以第二和第九个泌乳月稍高,第三至第八个泌乳月较低,尤以第六至第八个泌乳月RMS很低且平稳。 3.采用模型以204天实际产乳量预测305天产乳量,绝对误差很小。根据对二个样本60个泌乳期的计算,误差分别为40.01和36.00公斤,均小于0.8％。 4.方差分析表明,影响参数b的主要因素是牧场(P<0.001)和产犊月份(P<0.05);影响参数C的主要因素是牧场(P<0.05);产犊月份对泌乳持久力的影响显著(P<0.01);牧场对泌乳出现高峰的时间影响显著(P<0.01)。 5.参数b的遗传力为0.0976,C为0.018,b和c的表型相关很显著(P<0.001)。更多还原

【Abstract】 The authors of the present paper applied the incomplete gamma function in calculating and analysing 175 lactation periods of Holstein-Friesian in Jinshan, Shanghai. The results are given as fallows:1. As the lactation curves in the average month milk production com-ared with the actual lactation curves were estimated by the incomplelte gamma function, RMS was 0.716± 0.274Kg, and the bias was -0.68Kg. It was because the error was inconsiderable that the lactation curves might be analysed by the incomplete gamma function.2. RMS per month on mathematical model was distributed thus: slightly high in the second and ninth milking month, comparatively low from the third to the eighth milking month and low and steady especially from the sixth to the eighth milking month.3. The absolute error would be litte if the 305 days of the milk yield was predicted by means of the mathematical model calculating the 240 days of the milk yield. The errors were 40.01Kg and 36.00Kg respectively, both two values being less than 0.8% according to the calculation of 60 lactation periods of two samples.4. The variance analysis showed that the main factors affecting parameter b were the dairy farm ( P<0.001 ) and the calving month ( P<0.05 ) , while the main factor affecting parameter c was the dairy farm ( P<0.05 ) . The calving month had a significant effect on the milking persistency ( P <0.01 ) , and the dairy farm had a significant effect on the arising of peak milk production period ( P<0.01 ) .5. The heritability of the parameter b was 0.0976, and that of the parameter cwas 0.018. The phenotypic carrelation was very significant between b and c ( P<0.001 ) .更多还原