نوع مقاله : مقاله پژوهشی
نویسندگان
1 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی،خرم آباد، ایران
2 مدیریت جهاد کشاورزی شهرستان کوهدشت، لرستان، ایران
3 مدیریت جهاد کشاورزی شهرستان دلفان، لرستان، ایران
4 بخش تحقیقات گیاهپزشکی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرمآباد، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Introduction: Nowadays, conservation agriculture in dryland areas has gained great importance due to its potential to minimize climate hazards, reduce soil erosion, improve soil quality and increase available moisture. Few studies have been reported on genotype × tillage interaction for chickpea yield in dryland areas. The aim of this study was to evaluate the efficiency of the models used in stability analysis, including different AMMI indices, a combination of the two AMMI and BLUP methods, WAASB and WAASBY indices, and also to draw different diagrams to better understand the interaction of genotype × tillage (environment) and identify high-yielding chickpea genotypes adapted to the climatic conditions of rainfed regions in different tillage systems.
Materials and methods: Sixteen chickpea genotypes were evaluated under three tillage systems including conventional tillage with complete residue removal (CT), reduced tillage (ploughing with a chisel plough into the remaining vegetation cover at a depth of 10 to 15 cm of soil - RT), and no-till with vegetation remaining on the soil surface (CA) in farmer's fields in Delfan county, Lorestan province, during two cropping years (2019-2020). Statistical analyses were performed to determine the stability of genotypes in different tillage systems using the Metan and GGE multi-environmental experiment analysis packages in R software. AMMI statistical parameters as well as AMMI statistical-based parameters including ASV, SIPC, EV, ZA, SSI, WAASB, and WAASBY were used on the genotype × environment (tillage) interaction matrix obtained from the best linear unbiased prediction (BLUP).
Results and discussion: The results of the likelihood ratio test showed that the effect of genotype and genotype × tillage interaction was significant on grain yield. Therefore, the unbiased best linear prediction (BLUP) analysis was considered appropriate for these data. Based on the AMMI Stability Value Index (ASV), genotypes 10, 4, 9, 14 and 12 had more stable yield. The simultaneous selection index (SSIASV) based on ASV identified genotypes 9, 4, 13, 10 and 6 as superior genotypes in terms of grain yield and yield stability. The AMMI2 biplot diagram based on the first two principal components identified genotypes 11, 2 and 6 as genotypes with yield stability. Considering that not all principal components contribute to the AMMI2 biplot calculation and only the first-two principal components are used, accounting for 18.47 and 25.26 percent of the genotype × tillage (environment) interaction, the WAASBY genotypic stability index was used, which allows simultaneous interpretation based on average yield and yield stability in a two-dimensional graph. Based on the WAASBY index based on BLUP analysis, genotypes 4, 5, 6, 8, 9, 11, and 15 were identified as high-yielding with stable yield. The results of the mosaic plot showed that the contribution of genotype and genotype × tillage (environment) interaction was 38.5 and 62.94 percent of the total variation, respectively.
Conclusion: Overall, it seems that using the WAASBY chart with variable weighting from 0 to 100 for the WAASB index and average grain yield can lead to more reliable results from stability analysis using analyses such as factor analysis, BLUP, and AMMI in identifying selected genotypes. Considering that the mixed model and all components were used in calculating the WAASBY index, it seems that this index is superior to other indices.
کلیدواژهها [English]
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