| چکیده انگلیسی مقاله |
Extended Abstract
Introduction: Barley (Hordeum vulgare L.) is one of the important cereal crops, so after wheat, rice, and maize it ranked fourth, globally. In any breeding program, superior genotypes must be accurately identified. Improvement of some traits such as grain yield may be efficient through indirect selection pathway due to other traits that have a high correlation with it. Therefore, this study aimed to select the best barley genotypes with desirable agronomic traits by using a combination of different selection indices and finally comparing those.
Materials and methods: To evaluate some of superior barley genotypes using multi-trait selection indices, the experiment was conducted at Darab Agricultural and Natural Resources Research Station, Darab, Iran, in the 2020-2021 cropping year. The plant genetic materials consisted of 51 barley genotypes along with nine check genotypes. The experiment was carried out based on randomized complete block design with three replications. The studied genotypes were planted in six lines 5 m in along and 15 cm space between them. Seed density was determined as 300 seeds per square meter, and sowing done using an experimental plot planter (Wintersteiger, Austria). Before seed sowing, the fertilizer composition was 150 kg ha-1 nitrogen (twice), and di-ammonium phosphate and potassium sulfate were 100 and 50 kg ha-1, respectively. After remove the border effect, all experimental plots were harvested using an experimental combine (Wintersteiger, Austria). Three selection indices including selection of ideal genotype (SIIG), multi-trait genotype-ideotype distance index (MGIDI), ideotype design via best linear unbiased prediction (FAI-BLUP) and Smith-Hazel (SH) were estimated based on 12 morpho-phenological traits to select superior genotypes. The measured traits included of grain yield, number of spikes per square meter, number of grains per spike, weight of spike, thousand grains weight, grain filling period, spike length, plant height, number of days to heading, number of days to maturity, grain filling rate, and type spike.
Results: The results of the likelihood ratio test (LRT) showed that the genotype effect was significant at the 1% probability level for all measured traits. The results of restricted maximum likelihood (REML) showed the lowest heritability was recorded for grain filling period (0.505), grain yield (0.611) and grain filling rate (0.649); while the highest values were observed for thousand grain weight (0.884) and number of days to heading (0.877). The results of comparing the adjusted mean using the REML-BLUP model revealed that the highest grain yield was found by genotypes number 3, 1, 50 and 30, respectively. The grain yield of these genotypes was higher than all check genotypes. Based on the MGIDI index, genotypes number 39, 14, 43, 49, 6, 35, 19, 32, 41, 50, 55 (Auxin), 38, 44, 60 (Nimrooz), 28, 42, 40, and 34 with the lowest values were identified as superior genotypes. Genotypes number 39, 35, 43, 14, 32, 6, 41, 44, 50, and 42 with the highest FAI-BLUP values were selected as the best genotypes. The results of the Smith-Hazel index showed that the genotypes number 30, 55, 1, 2, 3, 40, 38, 12, 10 and 13 with the highest values were identified as superior genotypes. Also, genotypes number 3, 50, 30, 1, 55, 10, 13, 2, 11, 39, 12, 38, 31, 35, 36, and 44 with the highest SIIG index were superior genotypes in terms of most measured traits. The results of correlation analysis showed that grain yield positively and significantly correlated with number of days to maturity (0.35*), plant height (0.37*), grain filling period (0.26*), number of spikes per square meter (0.61**), and grain filling rate (0.96**). The correlation of all selection indices with grain yield was significant, and the highest correlation value with grain yield was found between it and the SIIG (0.92**) and Smith-Hazel (0.78**) indices. FAI-BLUP and MGIDI indices significantly associated with all traits except of thousand grain weight, length of ripening period, length of spike and number of spikes per square meter traits. Only the thousand grain weight and spike length traits did not show significant correlation with any of the selection indices.
Conclusion: In conclusion, genotype numbers 3, 50, 30, 1, 55, 10, 13, 2, 11, 12, and 38 were identified as superior genotypes using both SIIG and Smith-Hazel indices and genotypes number 39, 35, 50, 38 and 44 were identified as superior genotypes by FAI-BLUP and MGIDI indices. Finally, in our results revealed that SIIG and Smith-Hazel indices were better than FAI-BLUP and MGIDI indices to identify superior genotypes.
|