Department of Agronomy and USDA-ARS, Cornell University, 14853, Ithaca, NY, USA.
Theor Appl Genet. 1989 Apr;77(4):473-81. doi: 10.1007/BF00274266.
Yield trials serve research purposes of estimation and selection. Order statistics are used here to quantify the successes or problems to be expected in selection tasks commonly encountered in breeding and agronomy. Greater accuracy of yield estimates implies greater selection success. A New York soybean yield trial serves as a specific example. The Additive Main effects and Multiplicative Interaction (AMMI) statistical model is used to increase the accuracy of these soybean yield estimates, thereby increasing the probability of successfully selecting, on the basis of the empirical yield data, that genotype which has the maximum true mean. The statistical strategy for increasing accuracy is extremely cost effective relative to the alternative strategy of increasing the number of replications. Better selections increase the speed and effectiveness of breeding programs, and increase the reliability of variety recommendations. Selection tasks are frequently more difficult than may be suspected.
产量试验服务于估计和选择的研究目的。在这里,顺序统计量用于量化在通常在育种和农学中遇到的选择任务中预期的成功或问题。产量估计的更高准确性意味着更高的选择成功率。纽约大豆产量试验就是一个具体的例子。使用加性主效应和乘法交互(AMMI)统计模型来提高这些大豆产量估计的准确性,从而提高基于经验产量数据成功选择具有最大真实均值的基因型的概率。与增加复制数量的替代策略相比,提高准确性的统计策略具有极高的成本效益。更好的选择可以提高育种计划的速度和效率,并提高品种推荐的可靠性。选择任务通常比预期的要困难。