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Assessment of the adaptation of oilseed rape (Brassica napus L.) genotypes using non-parametric statistical methods
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Zahra Veisizadeh   , Raheleh Khademian , Bahram Alizadeh |
| Imam Khomeini International University, Qazvin, Iran |
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Abstract: (998 Views) |
| One of the most important challenges for plant breeding has always been genotype × environment interaction. In present study, genotype × environment interaction was invesitigated for 13 winter oilseed rape genotypes in six cold and temperate cold locations in Iran using non- parametric statistical methods during 2014-2017 growing seasons. Four methods; Hildebrand, Bredenkamp, Kubinger, and De Kroon/van der Laan to verify the main effect of genotype and environment as well as gennotype ×environment interaction effect. Also, Nassar and Huhn, and Thennarasu as well as Fox's superiority index and summation rank of Kang methods were used for assessment of dadaptability of ghenotypes. Determination of significant main and interaction effect revealed that all effects were significance with the exception of interaction effect in Kubinger method. By using plot from the first method of Nassar and Huhn and Thennarasu, genotype BAL921 with mean seed yield of 4078.6 kg.ha-1 was superior to the other genotypes. Fox and sum of ranks of Kang methods identified cv. Nafis and cv. Nima with mean of 4336 and 3902.4 kg.ha-1 seed yield as adapted cultivars. Identification of superior genotype(s) is more reliable by method that considers high yield and yield stability of genotype(s). In this study, Fox and sum of ranks of Kang methods was more efficient than other non-parametric statistical methods used due to having the features, therefore the genotypes selected using these methods were identified as the most suitable genotypes. |
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| Keywords: Adpatation, Genotype × environment, Oilseed rape, Seed yield and Yield stability. |
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Full-Text [PDF 631 kb]
(664 Downloads)
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Type of Study: Scientific & Research |
Subject:
Special
Received: 2020/07/6 | Accepted: 2020/11/25 | Published: 2021/05/31
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