Volume 16, Issue 4 (11-2024)
J Crop Breed 2024, 16(4): 129-141 |
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Akbari N, Darvishzadeh R. (2024). A Study on the Yield Stability of Oilseed Sunflower Genotypes under Drought Stress. J Crop Breed. 16(4), 129-141. doi:10.61186/jcb.16.4.129
URL: http://jcb.sanru.ac.ir/article-1-1549-en.html
URL: http://jcb.sanru.ac.ir/article-1-1549-en.html
1- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, Iran
2- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, , Iran,
2- Department of Plant Production and Genetics, Faculty of Agriculture, Urmia University, Urmia, , Iran,
Abstract: (372 Views)
Extended Abstract
Background: The process of selecting and introducing compatible genotypes with high yield potential requires evaluation in different years and places. Due to the severe and rapid changes in climate, which confront crops with all kinds of stress, especially drought stress, it is expected that the cultivated area of crops, such as sunflower, which is highly desirable for planting due to its special characteristics, will decrease. Undoubtedly, improving drought tolerance and developing high-yielding cultivars is one of the most important goals in breeding programs. On the other hand, in the selection and introduction of varieties, performance, the most important feature of the breeding program, due to its polygenic nature, is strongly affected by biotic and abiotic stresses. Therefore, taking into account the quantitative control, and the effects of the environment and the interaction of the genotype × environment, selection for this trait is complex, costly, and time-consuming. Therefore, understanding the genotype × environment interaction is essential for the development of high-yielding and stable genotypes. Crop stability in the agricultural concept means no deviation from the expected product response. Based on this, several methods have been introduced for selection with optimal efficiency and high accuracy. Stability indices are divided into two main groups: parametric and non-parametric stability indices. Each of these two groups has advantages and disadvantages. Thus, if parametric methods are more capable of evaluating the interaction effects of the genotype × environment and analysis of stability, non-parametric methods have a higher ability to analyze non-crossed interactions. However, it seems that the purpose of the plant breeder and the size of the studied sample are decisive in the superiority of these statistics. If the purpose of the plant breeder is only to rank genotypes among environments, non-parametric statistics are more suitable. If the sample size is small, the use of parametric statistics will be more appropriate than non-parametric ones, but if the sample size is large, the efficiency of both types of stability indices will be equal. It seems that using both stability indices helps in selecting genotypes with stable performance. In this research, it was tried to obtain comprehensive information about the studied genotypes using both groups of stability indices.
Methods: One hundred oilseed sunflower genotypes were evaluated in a 10 × 10 simple lattice design under two normal and drought stress (irrigation limitation) conditions during 2012 and 2013 (four environments) in terms of seed yield in Qezeljeh village in West Azerbaijan, Iran. For this purpose, cultivation was done in lines with 5-meter long. The distance between the lines was 60 cm, and the distance between the plants on the lines was 50 cm. The criterion for applying the treatment was the rate of evaporation from the class A evaporation pan. In both years, the field was irrigated up to the 8-leaf stage in both normal and limited irrigation experiments after 90 mm of evaporation from the Class A evaporation pan. From the 8-leaf stage onwards in the normal irrigation experiment, irrigation continued in the same way until the end of the growing season. In limited irrigation, irrigation was done after 180 mm of evaporation from the Class A evaporation pan. Parametric and non-parametric stability indices were used to select genotypes with high and stable performance. In this regard, the analysis of variance (ANOVA) was done with a mixed linear model, considering the environment and genotype as fixed effects and the year and replication as random effects. SAS software version 4.9 was used for ANOVA, and the STABILITYSOFT program under the R environment was used for stability analysis. Stability analysis was done with seven different parametric methods (based on ANOVA and regression analysis) and 11 non-parametric methods. Moreover, the STABILITYSOFT program was used to show the relationship between different stability indices in the form of a heat map plot.
Results: Based on the results of combined ANOVA, the effects of the genotype and genotype × environment were significant. Considering the variability observed among genotypes and the different reactions of genotypes from one environment to another, stability analysis was done with different parametric and non-parametric methods to select stable genotypes. Based on the correlation results, the average yield (MY) with S(3) statistics at the 5% probability level and with S(6), NP(2), NP(3), NP(4), GE (θ(i)), and Kang statistics at the 1% probability level showed a negative correlation and with NP(1), Wi2, σi2, Reg, MV (θi) and Sdi2 statistics at the 1% level showed positive and significant correlations. In particular, the three Shukla's statistics (σi2), Wick's equivalence (Wi2), and MV (θi) parameters showed a positive correlation with yield. Based on all parametric and non-parametric stability parameters, the AS613 genotype was introduced as a genotype with high yield and stability.
Conclusion: The stability indices, which evaluate the stability of genetic materials, can be beneficial to a large extent in the optimal and efficient selection of parental genotypes for developing high-yielding and stress-tolerant cultivars.
Background: The process of selecting and introducing compatible genotypes with high yield potential requires evaluation in different years and places. Due to the severe and rapid changes in climate, which confront crops with all kinds of stress, especially drought stress, it is expected that the cultivated area of crops, such as sunflower, which is highly desirable for planting due to its special characteristics, will decrease. Undoubtedly, improving drought tolerance and developing high-yielding cultivars is one of the most important goals in breeding programs. On the other hand, in the selection and introduction of varieties, performance, the most important feature of the breeding program, due to its polygenic nature, is strongly affected by biotic and abiotic stresses. Therefore, taking into account the quantitative control, and the effects of the environment and the interaction of the genotype × environment, selection for this trait is complex, costly, and time-consuming. Therefore, understanding the genotype × environment interaction is essential for the development of high-yielding and stable genotypes. Crop stability in the agricultural concept means no deviation from the expected product response. Based on this, several methods have been introduced for selection with optimal efficiency and high accuracy. Stability indices are divided into two main groups: parametric and non-parametric stability indices. Each of these two groups has advantages and disadvantages. Thus, if parametric methods are more capable of evaluating the interaction effects of the genotype × environment and analysis of stability, non-parametric methods have a higher ability to analyze non-crossed interactions. However, it seems that the purpose of the plant breeder and the size of the studied sample are decisive in the superiority of these statistics. If the purpose of the plant breeder is only to rank genotypes among environments, non-parametric statistics are more suitable. If the sample size is small, the use of parametric statistics will be more appropriate than non-parametric ones, but if the sample size is large, the efficiency of both types of stability indices will be equal. It seems that using both stability indices helps in selecting genotypes with stable performance. In this research, it was tried to obtain comprehensive information about the studied genotypes using both groups of stability indices.
Methods: One hundred oilseed sunflower genotypes were evaluated in a 10 × 10 simple lattice design under two normal and drought stress (irrigation limitation) conditions during 2012 and 2013 (four environments) in terms of seed yield in Qezeljeh village in West Azerbaijan, Iran. For this purpose, cultivation was done in lines with 5-meter long. The distance between the lines was 60 cm, and the distance between the plants on the lines was 50 cm. The criterion for applying the treatment was the rate of evaporation from the class A evaporation pan. In both years, the field was irrigated up to the 8-leaf stage in both normal and limited irrigation experiments after 90 mm of evaporation from the Class A evaporation pan. From the 8-leaf stage onwards in the normal irrigation experiment, irrigation continued in the same way until the end of the growing season. In limited irrigation, irrigation was done after 180 mm of evaporation from the Class A evaporation pan. Parametric and non-parametric stability indices were used to select genotypes with high and stable performance. In this regard, the analysis of variance (ANOVA) was done with a mixed linear model, considering the environment and genotype as fixed effects and the year and replication as random effects. SAS software version 4.9 was used for ANOVA, and the STABILITYSOFT program under the R environment was used for stability analysis. Stability analysis was done with seven different parametric methods (based on ANOVA and regression analysis) and 11 non-parametric methods. Moreover, the STABILITYSOFT program was used to show the relationship between different stability indices in the form of a heat map plot.
Results: Based on the results of combined ANOVA, the effects of the genotype and genotype × environment were significant. Considering the variability observed among genotypes and the different reactions of genotypes from one environment to another, stability analysis was done with different parametric and non-parametric methods to select stable genotypes. Based on the correlation results, the average yield (MY) with S(3) statistics at the 5% probability level and with S(6), NP(2), NP(3), NP(4), GE (θ(i)), and Kang statistics at the 1% probability level showed a negative correlation and with NP(1), Wi2, σi2, Reg, MV (θi) and Sdi2 statistics at the 1% level showed positive and significant correlations. In particular, the three Shukla's statistics (σi2), Wick's equivalence (Wi2), and MV (θi) parameters showed a positive correlation with yield. Based on all parametric and non-parametric stability parameters, the AS613 genotype was introduced as a genotype with high yield and stability.
Conclusion: The stability indices, which evaluate the stability of genetic materials, can be beneficial to a large extent in the optimal and efficient selection of parental genotypes for developing high-yielding and stress-tolerant cultivars.
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