نوع مقاله : مقاله مروری
نویسندگان
1 گروه تولید و ژنتیک گیاهی دانشکده کشاورزی دانشگاه ارومیه، ارومیه، ایران
2 دانشگاه ارومیه
3 گروه تولید و ژنتیک گیاهی دانشکده علوم کشاورزی دانشگاه گیلان، رشت، ایران
4 انستیتو علوم اعصاب تولوز، فرانسه.
5 گروه تولید و ژنتیک گیاهی دانشکده کشاورزی دانشگاه مراغه، مراغه، ایران
6 گروه تولید و ژنتیک گیاهی دانشکده کشاورزی مجتمع آموزش عالی سراوان، سراوان، ایران.
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Introduction: Genotype-environment interaction (GEI) significantly affects the performance of various genotypes under different environmental conditions, posing challenges for agricultural researchers focused on improving crop varieties. The selection and introduction of genotypes, as a key stage in breeding programs, is complex and time-consuming due to the impacts of biotic and abiotic stresses. An ideal genotype should not only have high yield but also remain stable across varying conditions. This dynamic concept of stability aids in identifying suitable genotypes; however, none of the existing methods can explain all dimensions of performance across different environments on their own. Therefore, for the effective selection of superior genotypes and understanding the genotype-environment interaction, it is essential to analyze multiple datasets from multi-environment trials (METs) from various aspects of performance stability.
Materials and Methods: Several statistical methods have been proposed for selecting stable genotypes with high accuracy, which can be divided into two main groups: parametric and non-parametric stability indices. This paper analyzes and compares the effectiveness of these two types of assessments and comprehensively reviews various stability analysis methods.
Result: This paper explains the fundamental concepts of GEI, its causes, its importance, and how to evaluate the stability and performance of genotypes in METs. The results indicate that stability analysis methods, including parametric methods based on regression analysis and analysis of variance as well as non-parametric methods, each have their specific advantages and disadvantages. Furthermore, the findings show that parametric methods are more effective in analyzing genotype × environment interactions, while non-parametric methods are more suitable for analyzing non-crossing interactions. Sample size and the breeder's objective are key factors in method selection. In small sample conditions, parametric methods have an advantage; however, as sample size increases, the effectiveness of both methods becomes nearly equal. Combining these two types of indices can assist researchers in selecting superior and stable genotypes.
Conclusion: This paper examines and compares the effectiveness of non-parametric and parametric assessments in evaluating stability and performance in METs. Utilizing diverse analytical methods enables researchers and breeders to select promising genotypes based on performance and stability, ultimately contributing to enhanced production sustainability and food security.
کلیدواژه‌ها [English]
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