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Evaluation of seed yield stability of soybean (Glycine max L. Merr) genotypes using nonparametric statistics methods
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Amir Gholizadeh   , Bahram Masoudi , Parsto Majidian , Kamal Payghamzadeh , Ebrahim Hezarjaribi , Nasrin Razmi |
| Assistant Prof., Field and Horticultural Crops Science Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran |
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Abstract: (178 Views) |
Introduction: Soybean is an important oilseed crop that its oil has nutritional and high economic value. Soybean (Glycine max L.) is an annual, self-pollinating, diploid plant and is one of the most important oilsed plants in the world (Smith and Huyser, 1987). Evaluating of promising genotypes of soybean under different environmental conditions is essential for identifying and selecting superior genotypes with high and stable seed yield potential. Genotype × environment interaction effects are important and challenge in selection and release of new cultivars. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The nonparametric statistics are suitable method with high efficiency to investigate the interaction effect of genotype × environment and provides useful information about the studied genotypes (Mehmet et al., 2019). The purpose of this experiment was to investigate genotype × environment interaction effect using some nonparametric statistics to identify soybean genotypes with high seed yield and yield stability under different environmental conditions.
Material and Methods: Thirteen promising soybean lines along with two cultivars Saba and Amir were evaluated using randomized complete block design with three replications in four experimental field stations including Karaj, Sari, Gorgan and Moghan in 2020–2021 growing seasons. Some nonparametric statistics were used to study yield stability of soybean genotypes. Plots were harvested at maturity and then seed yield was recorded for each genotype.
Results: The results of combined analysis of variance indicated that year, location and genotype effect and genotype × year, gewnotype × location and genotype × year × location interaction effects were significant on seed yield. Cluster analysis based on the nonparametric stability statistics showed that there were three main clusters. According to mean rank of nonparametric stability parameters, Hamilton × Karbin, Hamilton×TMS and Sari × Charleston promising lines, and Saba cultivar with the lowest mean rank had seed yield stability. Also, the results indicated that the nonparametric statistics NPi(4) and RS were associated with mean seed yield and the dynamic concept of yield stability. Therefore, these methods were suitable for selecting high yielding soybean genotypes with seed yield stability. Sari × Charleston, Hamilton × Karbin and Hamilton × TMS promising lines with wide adaptation were selected as superior lines, for being released as new commercial cultivars. The results of cluster analysis showed that Gorgan and Sari locations located in the same group, which indicated these locations had high predictability and repeatability.
Conclusion: The results of this study, Sari × Charleston, Hamilton × Karbin and Hamilton × TMS promising lines were identified superior lines with high seed yield and yield stability. Therefore, these lines can be considered for further studies and as cndidates for release as new commercial soybean cultivars.
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| Keywords: Genotype × environment interaction, Rank sum, Seed yield, Soybean and Superior lines |
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Full-Text [PDF 440 kb]
(91 Downloads)
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Type of Study: Scientific & Research |
Subject:
Special
Received: 2024/06/9 | Accepted: 2024/09/26 | Published: 2024/11/30
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