Inchaisri C, De Vries A, Jorritsma R, Hogeveen H
Department of Veterinary Medicine, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand.
Reprod Domest Anim. 2012 Oct;47(5):820-6. doi: 10.1111/j.1439-0531.2011.01975.x. Epub 2012 Jan 2.
The conception rate in dairy cows is dependent on a number of cow factors such as days in milk and insemination number. Unfortunately, some of these factors were not accounted for in optimal insemination and replacement decision models. By using wrong estimates of the conception rate, the calculated optimal insemination and replacement policy might differ from the real optimal insemination and replacement policy. The objective of this study was to evaluate different sets of conception rates with an increasing level of accuracy to determine the insemination policy. An existing dynamic program for optimal insemination and replacement was used to compare three different scenarios in the estimation of conception rates, based on the reproductive performance of Dutch dairy cattle: (i) constant conception rate throughout lactation, (ii) conception rate dependent on parity and months in milk, and (iii) conception rate dependent on parity, months in milk and insemination number. The time step of the model was 30.4 days (1 month). The discounted future cash flow of culling a cow at each time step (replace a heifer immediately) was compared with keeping that cow under optimal future decisions. The difference between immediate culling and optimal decisions is defined as the retention pay-off. The insemination value was calculated as the difference between the future cash flow between immediate insemination of a cow and waiting one time-step. The results show that the difference in the insemination values and the optimal time to stop insemination depend on parity, lactation stage and the relative milk yield. In older cows with equal milk yields and at the same months in milk, the insemination value was lower than in younger cows. Within a parity, the insemination value was higher for cows with a higher milk yield. On individual cow level, using more accurate conception rate as input in the optimal insemination and replacement model might reduce miscalculation of the economic consequences for at least of €20-€38 per cow per year. Basing insemination decisions on less accurate input of the probabilities of conception, however, did not have an economic consequence at the herd level. In conclusion, using the appropriate conception rate as input in the optimal insemination and replacement model would increase the precise decision for the optimal time to stop insemination and hence improve the reproductive management efficacy.
奶牛的受孕率取决于许多奶牛自身因素，如泌乳天数和输精次数。遗憾的是，一些此类因素在最优输精和淘汰决策模型中并未得到考虑。由于受孕率估计错误，计算得出的最优输精和淘汰策略可能与实际的最优输精和淘汰策略有所不同。本研究的目的是评估不同精度水平的受孕率集，以确定输精策略。基于荷兰奶牛的繁殖性能，利用现有的最优输精和淘汰动态规划程序，在受孕率估计中比较三种不同情景：（i）整个泌乳期受孕率恒定；（ii）受孕率取决于胎次和泌乳月数；（iii）受孕率取决于胎次、泌乳月数和输精次数。模型的时间步长为30.4天（1个月）。将每个时间步长淘汰一头奶牛（立即替换一头后备母牛）的贴现未来现金流与在最优未来决策下保留该奶牛的情况进行比较。立即淘汰与最优决策之间的差异定义为保留收益。输精价值计算为立即对奶牛进行输精与等待一个时间步长之间的未来现金流差异。结果表明，输精价值的差异以及停止输精的最优时间取决于胎次、泌乳阶段和相对产奶量。在产奶量相同且泌乳月数相同的老龄奶牛中，输精价值低于年轻奶牛。在同一胎次内，产奶量较高的奶牛输精价值更高。在个体奶牛层面，在最优输精和淘汰模型中使用更准确的受孕率作为输入，可能会将每头奶牛每年至少20欧元至38欧元的经济后果误算减少。然而，基于受孕概率不太准确的输入做出输精决策，在畜群层面并没有经济后果。总之，在最优输精和淘汰模型中使用适当的受孕率作为输入，将增加停止输精最优时间的精确决策，从而提高繁殖管理效率。
