Uni- and multivariate methods applied to the study of the adaptability and stability of white oat

Abstract: The objective of this work was to compare uni- and multivariate biometric methods to evaluate the adaptability and stability of an important group of white oat (Avena sativa) cultivars grown in Southern Brazil. The used experimental design was a randomized complete block, in a factorial arrangement of 12 environments x 7 cultivars, with three replicates. The analysis of variance and the methods of Eberhart & Russel, Annicchiarico, and the harmonic mean of the relative performance of predicted genetic values (MHPRVG) were assessed. In the general comparison of the methods, the 'UPFA Gaudéria' and 'URS Guapa' genotypes were more stable regarding grain yield. The 'UPFA Gaudéria' and 'URS-21' genotypes stood out for hectoliter weight, presenting the best performances by the methods of Annicchiarico and the MHPRVG. For thousand-grain weight, all methods showed similar results, indicating that the 'UPFA Gaudéria' genotype presented the best results. The 'URS Guapa' genotype was superior when using the methods of Eberhart & Russel, Annicchiarico, and the MHPRVG. The uni- and multivariate methods evaluated are suitable to estimate with high confidence the adaptability and stability of cultivars for each targeted grain production, yield, and quality.

摘要：本研究旨在比较单变量与多变量生物统计方法，以评估巴西南部种植的重要白燕麦（*Avena sativa*）品种群的适应性与稳定性。试验采用完全随机区组设计，设置12个环境×7个品种的析因处理组合，重复3次。分析方法涵盖方差分析，以及埃伯哈特-拉塞尔（Eberhart & Russel）法、安尼基亚里科（Annicchiarico）法，还有预测遗传值相对性能调和均值（MHPRVG）法。在各方法的综合比较中，‘UPFA Gaudéria’与‘URS Guapa’基因型的籽粒产量稳定性更优。‘UPFA Gaudéria’与‘URS-21’基因型在容重性状上表现突出，经安尼基亚里科法与MHPRVG法评估，二者表现最佳。对于千粒重性状，所有方法均得到一致结果，表明‘UPFA Gaudéria’基因型表现最优。采用埃伯哈特-拉塞尔法、安尼基亚里科法及MHPRVG法评估时，‘URS Guapa’基因型表现更优异。本研究所评估的单变量与多变量方法，均可高置信度地估算针对各目标籽粒产量、产量性能与品质性状的各品种适应性与稳定性。