Comparison of Spatial Models for Sugar Beet and Barley Trials
Comparison of Spatial Models for Sugar Beet and Barley Trials
复制标题
甜菜和大麦试验的空间模型比较
DOI：
10.2135/cropsci2009.03.0153
复制
发表时间：
2010
期刊：
影响因子：
2.3
通讯作者：
H. Piepho
中科院分区：
文献类型：
--
作者：
B. U. Müller;Kathrin Kleinknecht;J. Möhring;H. Piepho
存在多种用于调整一维局部趋势的空间方法。本研究的目的是评估和比较不同空间方法的精度。为此，使用基线模型对两家德国植物育种公司的 293 项甜菜 (Beta vulgaris) 和 64 项多环境大麦 (Hordeum vulgare) 试验进行了分析，该模型包括块和重复效应以及增强基线模型的不同一维空间模型。使用 Akaike 信息标准 (AIC)、两个环境之间调整后的基因型平均值的表型相关性以及相对效率来评估模型拟合度。对于甜菜和大麦试验，基线模型在大多数情况下优于空间模型，而在某些情况下，添加空间组件被证明是有益的。基于这些结果，我们提出了一种保守的空间建模方法，从基线模型开始，然后检查添加空间组件是否可以改善拟合。在研究的替代模型中，线性方差和一阶自回归模型是最有希望的候选模型。
Several spatial methods exist for the adjustment of local trend in one dimension. The aim of this study was to evaluate and compare the precision of different spatial methods. For this purpose, 293 sugar beet (Beta vulgaris) and 64 multienvironment barley (Hordeum vulgare) trials of two German plant breeding companies were analyzed using a baseline model, which comprised a block and replicate effect, and different one-dimensional spatial models augmenting the baseline model. Model fi t was assessed using the Akaike Information Criterion (AIC), the phenotypic correlation of the adjusted genotype means between two environments, and the relative effi ciency. For the sugar beet and barley trials the baseline model outperformed the spatial models in the majority of cases, while in some cases the addition of a spatial component proved benefi cial. Based on these results we propose a conservative approach to spatial modeling that starts with a baseline model and then checks whether adding a spatial component improves the fi t. Among the alternative models studied, the linear variance and the fi rst-order autoregressive models were the most promising candidates.