ESTIMATING SPATIAL VARIATION IN ANALYSIS OF DATA FROM YIELD TRIALS - A COMPARISON OF METHODS
ESTIMATING SPATIAL VARIATION IN ANALYSIS OF DATA FROM YIELD TRIALS - A COMPARISON OF METHODS
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DOI：
10.2134/agronj1993.00021962008500060028x
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发表时间：
1993-11-01
期刊：
影响因子：
2.1
通讯作者：
BURTON, JW
中科院分区：
文献类型：
--
作者：
BROWNIE, C;BOWMAN, DT;BURTON, JW
在大型产量试验中，土壤肥力（或更一般地说，产量潜力）的变化可能导致区块内的大量异质性，从而导致处理估计的精确性差。使用统计分析可以提高精确度，其中在估计治疗或入组平均值时考虑了这种空间变化。三种类型的空间分析是趋势分析、Papadakis方法和基于相关误差模型的分析（通过相邻地块产量之间的相关性来解释空间变异）。我们回顾了这些空间分析的理论和实证表现，并将其与经典分析进行了比较。经典分析可以仅根据随机化进行证明;空间分析取决于产量潜力变异的指定模型。性能取决于趋势分析中用于描述产量潜力的多项式、Papadakis分析中用于估计生育力的邻近地块以及相关误差模型中的相关结构。以11种玉米（Zea mays L.）产量试验和T大豆（Glycine mar L.）试验，每一个都显示出块内异质性的证据。与经典的随机区组分析相比，趋势分析和趋势加相关误差分析的精度最好，Papadakis方法居中。条目的排名在不同的分析中不同，因为每个分析以不同的方式调整空间变化。使用空间分析技术可以提高精度，但为给定数据集选择最合适的分析可能很困难。
In large yield trials, variation in soil fertility (or, more generally, yield potential) can result in substantial heterogeneity within blocks and, thus, poor precision in treatment estimates. Precision may be improved using statistical analyses in which this spatial variation is accounted for in estimation of treatment or entry means. Three such types of spatial analysis are trend analysis, the Papadakis method, and analyses based on correlated errors models (which account for spatial variation through correlations between yields of neighboring plots). We reviewed the theory and empirical performance of these spatial analyses and compared them with the classical analyses. The classical analyses can be justified solely on the basis of randomization; spatial analyses depend on the model specified for the variation in yield potential. Performance depends on the polynomial used to describe yield potential in trend analysis, an the neighboring plots used to estimate fertility in the Papadakis analysis, and on the correlation structure in the correlated errors models. Empirical comparisons were based on data from 11 corn (Zea mays L.) yield trials and T soybean (Glycine mar L.) trial, each showing evidence of heterogeneity within blocks. Is comparison with the classical randomized blocks analysis, precision tended to be best for the trend and the trend plus correlated errors analyses, with the Papadakis method intermediate. Ranking of entries differed across analyses, because each analysis adjusts for spatial variation in a different way. Using a spatial analysis technique can improve precision, but selecting the most appropriate analysis for a given data set can be hard.