تجزيه پايداري عملكرد دانه در ژنوتيپ‌هاي گلرنگ

Stability analysis of seed yield in safflower genotypes

هدف از اين تحقيق بررسي پايداري عملكرد دانه 30 ژنوتيپ گلرنگ با استفاده از تجزيه مدل آثار اصلي افزايشي و ضرب پذير (AMMI) و آماره هاي پايداري و اكووالانس ريك مي باشد. آزمايشات در شش محيط (دو شهرستان طي سال زراعي 1391-93) اجرا شدند. نتايج حاصل از تجزيه امي نشان داد كه آثار اصلي ژنوتيپ، محيط، آثار متقابل (E×G) و چهار مولفه اول اثر متقابل معني دار بودند. نمودار باي پلات قادر به تفكيك ژنوتيپ هاي پايدار و محيطهاي با قدرت تفكيك بالا از محيطهاي ضعيف بود. براساس نتايج تجزيه امي و پارامترهاي پايداري مورد بررسي ژنوتيپ هاي 2 و 4 با ميانگين عملكرد بالاتر از ميانگين كل داراي پايداري مطلوب بودند در صورتي كه ژنوتيپ هاي 20 و 21 با بيشترين تاثير در اثر متقابل ناپايدار ترين ژنوتيپ ها بودند.

Introduction: One of the greatest challenges encountered by plant breeders is the existence of interaction effects between genotype (G) and environment (E). Interpretation of the interaction, identification of target environments and introduction of suitable genotypes with narrow and broad sense adaptability as well as determining stable genotypes across different locations and years are of the important goals pursued in the studies concerning genotype-environment interaction. GE interaction phenomenon aids breeders in eliminating unnecessary testing locations, which results in a major cost reduction (Kang and Magari, 1996). Safflower (Carthamus tinctorius L.) is an annual plant that is adapted for growth in hot and dry environments with a considerable drought resistance due to its deep roots. Safflower has been used for many purposes such as, a dye, food coloring, a medicinal, a vegetable side dish, hay and forage, birdseed, edible oil and both fresh-cut and dried flowers. Genetic variation is the most important factor in successful genotype selection and breeding programs. Therefore, evaluation of germplasm collections is one of the most important methods to recognize suitable genotypes, which can help breeders to release new varieties. Spatial variability is inherent in all field experiments. The relative performance of lines varies with environment, and this G×E interaction hampers selection of lines for cultivation over a wide region. The additive main effects and multiplicative Interaction (AMMI) model is a multivariate statistical method that entirely justifies genotype and environment main effects as well as multiplicative G×E interaction effects. This method provides a clear interpretation of G×E interaction effect (Ebdon and Gauch, 2002). The objectives of this study were to analyze genotype by environment (GE) interactions on the seed yield of 30 safflower genotypes by AMMI model and to evaluate genotype (G), environment (E) and genotype × environment (GE) interactions using statistics parameter i.e. AMMI stability value (ASV) and ecovalence (W2 i). Materials and Methods: Thirty safflower genotypes were evaluated over a three-year period (2012-15) across two research stations in Iran. There were 6 growing environments in total. The individual trials were conducted using a randomized complete block design with 3 replications. The experiments were planted in early autumn of each year. Each genotypes was sown in plots (9 m2) of 6 rows, 5-m long with spacing of 30-cm between rows. Normal agronomic operations like weed and pest control were done. Four rows of each plot were harvested leaving 50 cm on both ends of the rows in order to exclude border effects. Simple analyses of variance in all environments were done for seed yield, separately. Combined analysis of variance was performed assuming genotype effect as fixed, environment effect as random factor. Results and Discussion: The results of combined analysis of variance showed that there were highly significant differences (P<0.01) among genotypes, environments and interaction effects for seed yield. The analysis of data from safflower trials showed that 28.70% of the total sum of squares was attributable to environmental effects, 55.91% to genotypic effects, and 15.39% to genotype ´ environment interaction effects. Main effects due to environment, genotype, and genotype ´ environment interactions as well as four first interaction principal components (IPCA1-4) were found to be significant, indicating that the agro-climatic environmental conditions were different, and that there was a differential response of the genotypes to the environments. The first two IPCA components of the GE interaction explained 83.57% of the GE interaction. Estimates of six genotypic parameters and their ranking for seed yields of safflower genotypes are given in Tables 2 and 3. According to IPCA1, G7 and G2 had the lowest scores and were the most stable genotypes whereas G21 and G20 with the highest scores were found to be unstable. The lowest ASV was observed for G2 and G4 that were the most stable genotypes whose mean yield was higher than the grand mean. However, the highest ASV scores were achieved by G21, G20 and G27. AMMI biplot was used to visualize mean seed yield performance and stability of safflower genotypes. AMMI biplot was able to distinguish stable genotypes with broad sense and narrow sense adaptation and environments with high and low genotype discrimination ability. The genotypes 2 and 4 with higher seed yield than the total mean were the most stable genotypes, while the genotypes 20 and 21 with the highest contribution to GE interaction were the most unstable genotypes. Wricke’s ecovalence stability parameter (W2 i) showed that the genotypes G9, G2, G11 and G4 were the most stable genotypes. Conclusion: In this study, according to the AMMI model, the G2 and G4 were the genotypes that exhibited the best adaptation and superiority in the all environments. These two genotypes with no thorns and red flowers were also determined as the most stable among the tested genotypes based on Wricke’s ecovalence analysis. Moreover, AMMI biplot demonstrated that G2 (genotype 411), which produced yields greater than the grand mean, can be considered stable with the ability to produce sufficient yields. Acknowledgements: I would like to thank E. Neyestani and other members of the Agricultural and Natural Resources Research and Education Center of Khorasan Shomali for their kind advice. The collaborations of A. Hakimi, M. Hakimi and A. Saburi at Shirvan Agricultural Research Station are greatly acknowledged.