Department of Dairy Science, University of Wisconsin, Madison 53706, USA.
J Dairy Sci. 2012 Aug;95(8):4683-98. doi: 10.3168/jds.2011-5214.
This study contributes to the research literature by providing a new formulation for the cow replacement problem, and it also contributes to the Extension deliverables by providing a user-friendly decision support system tool that would more likely be adopted and applied for practical decision making. The cow value, its related values of a new pregnancy and a pregnancy loss, and their associated replacement policies determine profitability in dairy farming. One objective of this study was to present a simple, interactive, dynamic, and robust formulation of the cow value and the replacement problem, including expectancy of the future production of the cow and the genetic gain of the replacement. The proven hypothesis of this study was that all the above requirements could be achieved by using a Markov chain algorithm. The Markov chain model allowed (1) calculation of a forward expected value of a studied cow and its replacement; (2) use of a single model (the Markov chain) to calculate both the replacement policies and the herd statistics; (3) use of a predefined, preestablished farm reproductive replacement policy; (4) inclusion of a farmer's assessment of the expected future performance of a cow; (5) inclusion of a farmer's assessment of genetic gain with a replacement; and (6) use of a simple spreadsheet or an online system to implement the decision support system. Results clearly demonstrated that the decision policies found with the Markov chain model were consistent with more complex dynamic programming models. The final user-friendly decision support tool is available at http://dairymgt.info/ → Tools → The Economic Value of a Dairy Cow. This tool calculates the cow value instantaneously and is highly interactive, dynamic, and robust. When a Wisconsin dairy farm was studied using the model, the solution policy called for replacing nonpregnant cows 11 mo after calving or months in milk (MIM) if in the first lactation and 9 MIM if in later lactations. The cow value for an average second-lactation cow was as follows: (1) when nonpregnant, (a) $897 in MIM = 1 and (b) $68 in MIM = 8; (2) when the cow just became pregnant,(a) $889 for a pregnancy in MIM = 3 and (b) $298 for a pregnancy in MIM = 8; and (3) the value of a pregnancy loss when a cow became pregnant in MIM = 5 was (a) $221 when the loss was in the first month of pregnancy and (b) $897 when the loss was in the ninth month of pregnancy. The cow value indicated pregnant cows should be kept. The expected future production of a cow with respect to a similar average cow was an important determinant in the cow replacement decision. The expected production in the rest of the lactation was more important for nonpregnant cows, and the expected production in successive lactations was more important for pregnant cows. A 120% expected milk production for a cow with MIM = 16 and 6 mo pregnant in the present lactation or in successive lactations determined between 1.52 and 6.48 times the cow value, respectively, of an average production cow. The cow value decreased by $211 for every 1 percentage point of expected genetic gain of the replacement. A break-even analysis of the cow value with respect to expected milk production of an average second-parity cow indicated that (1) nonpregnant cows in MIM = 1 and 8 could still remain in the herd if they produced at least 84 and 98% in the present lactation or if they produced at least 78 and 97% in future lactations, respectively; and (2) cows becoming pregnant in MIM = 5 would require at least 64% of milk production in the rest of the lactation or 93% in successive lactations to remain in the herd.
本研究通过为奶牛替换问题提供新的配方,为研究文献做出了贡献,并且通过提供用户友好的决策支持系统工具,为扩展成果做出了贡献,该工具更有可能被采用并应用于实际决策。奶牛的价值、其新怀孕和怀孕损失的相关价值及其相关的替换政策决定了奶牛养殖的盈利能力。本研究的一个目标是提出一个简单、互动、动态和强大的奶牛价值和替换问题的配方,包括对奶牛未来生产和替代的遗传增益的预期。本研究的已证实假设是,所有上述要求都可以通过使用马尔可夫链算法来实现。马尔可夫链模型允许:(1)计算研究奶牛及其替换的向前预期价值;(2)使用单个模型(马尔可夫链)计算替换策略和牛群统计信息;(3)使用预定义的、预先确定的农场生殖替换策略;(4)包括农民对奶牛未来表现的预期评估;(5)包括农民对替代的遗传增益的评估;(6)使用简单的电子表格或在线系统来实现决策支持系统。结果清楚地表明,与更复杂的动态编程模型相比,马尔可夫链模型找到的决策策略是一致的。最终用户友好的决策支持工具可在以下网址获得:http://dairymgt.info/→Tools→The Economic Value of a Dairy Cow。该工具可以即时计算奶牛的价值,并且具有高度的互动性、动态性和健壮性。当使用模型研究威斯康星州的一个奶牛场时,解决方案策略规定,如果奶牛处于第一次泌乳期,则在产后 11 个月或泌乳月(MIM)内替换非怀孕奶牛,如果处于后期泌乳期,则在 9 个月的 MIM 内替换非怀孕奶牛。一头平均二胎奶牛的奶牛价值如下:(1)当非怀孕时,(a)MIM=1 时为 897 美元,(b)MIM=8 时为 68 美元;(2)当奶牛刚刚怀孕时,(a)MIM=3 时的怀孕价值为 889 美元,(b)MIM=8 时的怀孕价值为 298 美元;(3)当奶牛在 MIM=5 时怀孕损失的价值为(a)怀孕的头一个月损失时为 221 美元,(b)怀孕的第九个月损失时为 897 美元。奶牛的价值表明应保留怀孕的奶牛。奶牛替换决策的一个重要决定因素是奶牛相对于类似平均奶牛的预期未来生产。非怀孕奶牛的剩余泌乳期的预期生产更为重要,而怀孕奶牛的后续泌乳期的预期生产更为重要。MIM=16 且目前泌乳期或后续泌乳期怀孕 6 个月的奶牛预期产奶量增加 120%,分别确定为平均产奶牛价值的 1.52 至 6.48 倍。每增加 1 个百分点的预期替代遗传增益,奶牛的价值就会减少 211 美元。奶牛价值相对于第二胎平均奶牛预期产奶量的盈亏平衡分析表明,(1)MIM=1 和 8 的非怀孕奶牛如果在本泌乳期的产奶量至少为 84%和 98%,或者如果在未来泌乳期的产奶量至少为 78%和 97%,则仍可保留在牛群中;(2)在 MIM=5 时怀孕的奶牛需要在剩余泌乳期的产奶量至少为 64%或在后续泌乳期的产奶量至少为 93%,才能留在牛群中。