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首页> 外文期刊>Australian Journal of Crop Science >Geostatistical approach for testing wheat lines using a non-replicated design
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Geostatistical approach for testing wheat lines using a non-replicated design

机译：使用非复制设计测试小麦品系的地统计学方法

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Seed availability is a limiting factor in early generations of wheat breeding programs, creating difficulties for the performance of replicated trials and leading to selection errors attributed to environmental effects. Thus, the objectives of this study were to determine the percentage and spatial distribution of check plots in the experimental area and to propose criterion based on a geostatistical analysis for selecting promising non-replicated wheat lines based on their grain yield. In this study, grain yield data (GYo) were obtained from 300 plots, arranged in a 15 row × 20 column matrix, from a uniformity trial (one genotype). Multiple scenarios were generated by varying the percentage of check plots, which were randomly determined with 1000 re-samplings to estimate grain yield (GYe) for non-sampled plots using an ordinary kriging method. The efficiency of the estimation method was assessed by calculating the Pearson's correlation coefficient and the mean square error between the GYo and GYe values for each re- sampling. Various spatial distributions of the check plots were evaluated using distinct models for semivariogram fitting. The correlation between the observed and the ordinary kriging-estimated values in the test area plots demonstrates that this approach can be used to identify superior lines for allocation with non-check plots. The estimated results (generated from the check plots) can be used as a reference point for the observed values of a given line. A systematic distribution of check plots in which the entries are alternated with and without checks in the sequence of rows or columns was the best geostatistical approach.
机译：种子的供应是早期小麦育种计划的限制因素，给重复试验的实施造成困难，并导致归因于环境影响的选择错误。因此，本研究的目的是确定试验区检查区的百分比和空间分布，并基于地统计学分析提出基于谷物产量选择有前途的非复制小麦品系的标准。在这项研究中，从均匀性试验（一种基因型）中，以15行×20列矩阵排列的300个样地获得了谷物产量数据（GYo）。通过改变检查图的百分比来生成多种情况，这些检查图是使用常规克里格法通过1000次重新抽样随机确定的，以估计非抽样图的谷物产量（GYe）。通过计算每次重新采样的皮尔逊相关系数和GYo和GYe值之间的均方误差，可以评估估计方法的效率。使用半变异函数拟合的不同模型评估了检查图的各种空间分布。在测试区域图中，观察到的克里金估计值与普通克里金估计值之间的相关性表明，该方法可用于识别用于非检查图分配的优良线。估计的结果（从检查图生成）可以用作给定线的观察值的参考点。最好的地统计学方法是系统地分布检查图，在其中按行或列的顺序在有无检查的情况下交替输入项。

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