區域試驗不均衡資料之穩定性子集合分析

本省區域試驗一般採用的穩定性介量多以最受廣泛使用的直線迴歸分析法為主。該法僅適用於每一基因型與環境組合都有資料之場合，因此一旦含有缺區，便無法正確估得環境指標，並進行穩定性分析；過去一般處理缺區的方式，係將含缺區的品系或環境全部刪除，使其呈均衡資料後，再進行穩定性分析，如此在缺區數多時勢必會造成品系或環境數減少，反而降低了評估結果的準確度。對此，本研究利用子集合分析法以擴大穩定性分析之應用範圍至不均衡的區域試驗資料。子集合分析可處理含交感模式之不均衡資料，在觀念上相當簡單直接，係就所分割成的兩個不同子集台均衡資料各進行穩定性分析，並利用兩子集合重疊部份，對共存環境下之品系進行穩定性選拔。惟該法在使用上必須注意，所有品系的共存環境數不得太少。

關鍵字

子集合分析；穩定性；區域試驗；不均衡資料；迴歸

並列摘要

Linear regression analysis is the most common and useful method to assess the varietal stability in a regional trial. However, a major practical limition to date, stability analysis have been a requirement of no missing data, that is, data for every genotype and environment combination or treatment have been necessary. The precison of stability analysis can be unduly influenced by removing all the data of the genotypes or environments which contain missing plot, because of the reduction in number of genotypes and environments. This study proposed a subset method for analyzing stability of unbalanced data in regional trials. Subset analyses for unbalanced data with interaction model were simple and straightforward. The set of unbalanced data was divided into two subsets of balanced data, then one used the stability analysis for these subsets. The analyses of overlapping subsets of the data revealed available information to selecting superior genotypes with common environments. This subset method for stability analysis of unbalanced regional trial data performed well when there were many common environments for genotypes.

並列關鍵字

Subset analysis ； Stability ； Regional trial ； Unbalanced data ； Regression

國際替代計量

區域試驗不均衡資料之穩定性子集合分析

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