Response and yield stability of canola (Brassica napus L.) genotypes to multi-environments using GGE biplot analysis

IF 0.6 4区农林科学 Q4 AGRONOMY

Bioagro Pub Date : 2021-04-29 DOI:10.51372/bioagro332.4

M. Sincik, A. Goksoy, Emre Senyigit, Y. Ulusoy, M. Acar, Sahin Gizlenci, Gulhan Atagun, Sami Suzer

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引用次数: 5

Abstract

he GxE interaction (GEI) provides essential information for selecting and recommending cultivars in multi-environment trials. This study aimed to evaluate genotype (G) and environment (E) main effects and GxE interaction of 15 canola genotypes (10 canola lines and 5 check varieties) over 8 environments and to examine the existence of different mega environments. Canola yield performances were evaluated during 2015/16 and 2016/17 production season in three different locations (Southern Marmara, Thrace side of Marmara, and Black Sea regions) of Turkey. The trial in each location was arranged in a randomized complete block design with four replications. The seed yield data were analyzed using GGE biplot and the yield components data were analyzed using ANOVA. The agronomical traits revealed that environments, genotypes, and GEI were significant at 1 % probability for all of the characters. The variance analysis exhibited that genotypes, environments, and GEI explained 21.6, 21.7, and 25.7 % of the total sum of squares for seed yield, respectively. The GGE biplot analysis showed that the first and second principal components explained 57.3 and 18.3 % of the total variation in the data matrix, respectively. GGE biplot analysis showed that the polygon view of a biplot is an excellent way to visualize the interactions between genotypes and environments.

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油菜基因型对不同环境的响应及产量稳定性研究

GxE相互作用（GEI）为在多环境试验中选择和推荐品种提供了重要信息。本研究旨在评估15种油菜基因型（10个油菜品系和5个对照品种）在8个环境中的基因型（G）和环境（E）的主要影响和GxE相互作用，并考察不同巨型环境的存在。在土耳其的三个不同地点（马尔马拉南部、马尔马拉色雷斯一侧和黑海地区），对2015/16年和2016/17年生产季节的皮划艇产量表现进行了评估。每个地点的试验采用随机完全区组设计，四次重复。使用GGE双批次分析种子产量数据，并使用ANOVA分析产量组成数据。农艺性状表明，环境、基因型和GEI对所有性状都有显著性，概率为1%。方差分析表明，基因型、环境和GEI分别解释了21.6%、21.7%和25.7%的种子产量平方和。GGE双批次分析表明，第一和第二主成分分别解释了数据矩阵总变化的57.3%和18.3%。GGE双图分析表明，双图的多边形视图是可视化基因型和环境之间相互作用的极好方法。

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来源期刊

Bioagro Agricultural and Biological Sciences-General Agricultural and Biological Sciences

CiteScore

1.40

自引率

37.50%

发文量

期刊介绍： Bioagro es una revista científica del Decanato de Agronomía de la Universidad Centroccidental “Lisandro Alvarado” (UCLA). Su periodicidad es cuatrimestral y se publica en los meses de enero, mayo y septiembre. Cada trabajo es revisado por al menos dos especialistas en el área, externos a la revista, de cuya opinión depende la aceptación definitiva. Se utiliza sistema de arbitraje doble ciego. La revista va dirigida, fundamental pero no exclusivamente, a profesionales y técnicos del área agrícola. Su objetivo es publicar trabajos científicos originales e inéditos en ciencias agrícolas que enfoquen aspectos de agronomía, botánica y propagación de plantas, entomología y zoología, suelos, fitopatología y protección vegetal, ingeniería agrícola, genética y mejoramiento de plantas, ecología, procesamiento de productos agrícolas, biotecnología y sociales. También pueden ser publicados artículos cortos en los que se presenten descubrimientos científicos, desarrollos tecnológicos y resultados de diagnósticos integrales, en la modalidad de Notas Técnicas. En Venezuela, se encuentra en las bibliotecas de todas las universidades e institutos de educación superior que ofrecen carreras agronómicas, así como de los entes oficiales de investigación agropecuaria. En el exterior, la revista llega a universidades y/o institutos de investigación agrícolas de todos los países de América Latina así como Estados Unidos, Canadá y España.