1- Agricultural Research, Education and Extension Organization (AREEO)
Abstract: (10 Views)
Background: In wheat breeding programs, breeders are required to increase productivity and increase wheat tolerance to multiple stresses by developing new genotypes with improved traits including high yield and tolerance to multiple stresses. Genotype selection is an important step in breeding programs with the aim of identifying superior genotypes with high yield and desirable agronomic traits. Therefore, it is essential to use effective and efficient selection techniques that can classify genotypes based on multiple traits. The SIIG index is one of the indicators for selecting superior genotypes in terms of performance and various traits simultaneously. GT biplot analysis also examines the relationship between genotype and trait and evaluates genotypes based on multiple traits. In this study, 21 durum wheat genotypes along with four control cultivars were evaluated based on the SIIG index and the GT method. The aim of this study was to rank genotypes and select superior genotypes based on the SIIG index and identify relationships between traits. The results of this study will help us identify suitable durum wheat genotypes for rainfed conditions and use them for future breeding programs or as candidate lines for cultivar introduction.
Methods: In this study, 21 selected lines from the wheat breeding programs of the Rainfed Agricultural Research Institute and submitted from the ICARDA International Research Center, along with four control cultivars (Saji, Zahab, Dehdasht, and Saverz), were evaluated at the Sarab Changaei Research Station in Khorramabad County for two cropping years 2020-2022. The genotypes were evaluated in a randomized complete block design with three replications under dryland conditions.During the growing season and after harvest, data related to phonological and morphological traits were recorded and measured. In this study, all evaluated traits were analyzed by variance analysis and the mean of genotypes was compared using the LSD method. Correlation analysis was performed using the Pearson method. In order to select the best genotypes in terms of yield and other agronomic traits, the SIIG index and genotype × trait biplot (GT) were used, and cluster analysis method was used to group the studied genotypes. GGEBiplot were used for the biplot analysis of the genotype × trait. Data were grouped using cluster analysis with SPSS software. The correlation between traits was calculated by pearson’s method using R software (GGALLY package). The Selection Index of Ideal Genotype (SIIG) was calculated in Excel.
Results: The results of variance analysis showed that there were significant differences between the genotypes for days to heading and days to maturity, plant height, spike length, peduncle length, number of spikelet per spike, number of grain per spike, grain weight per spike, and thousand kernel weight. This indicates genetic diversity among genotypes for evaluated traits. The highest grain yield was obtained for genotypes G8, G10 and G22 with average grain yield of 3522, 3362 and 3258 kg/ha, respectively. The results of trait correlation showed that there was a positive and highly significant correlation between grain yield and grain filling rate (r=0.90**). The SIIG index was positively and significantly correlated with peduncle length (r=0.63**), grain weight per spike (r=0.54**), grain yield (r=0.48*), and thousand-grain weight (r=0.41*). The results of the SIIG index showed that genotypes G8 and G16 were the best genotypes with the highest SIIG index values of 0.62 and 0.61, respectively. Genotype G14 with the lowest index value (0.32) was the weakest genotype for evaluated traits. In cluster analysis, the genotypes were divided into three groups, and the high-yielding genotypes G8, G10, G16, and G22 were placed in group 1. The genotypes of the third group had the lowest grain yield and other agronomic traits. Based on the GT biplot results, genotypes G4, G8, G10, G11 and G22 were the best for grain yield. Also, the mentioned genotypes had high 1000-grain weight, panicle length, peduncle length, plant height and grain filling period.
Conclusion: Based on the results obtained from the mean comparison, SIIG index, and GT biplot, the G8 genotype is recommended for use in breeding programs or as a promising line for the cultivar introduction program. According to the positive and highly significant correlation between grain yield and grain filling rate, the grain filling rate trait suggested as a valuable marker for identifying high-yielding durum wheat genotypes.
Methods: In this study, 21 selected lines from the wheat breeding programs of the Rainfed Agricultural Research Institute and submitted from the ICARDA International Research Center, along with four control cultivars (Saji, Zahab, Dehdasht, and Saverz), were evaluated at the Sarab Changaei Research Station in Khorramabad County for two cropping years 2020-2022. The genotypes were evaluated in a randomized complete block design with three replications under dryland conditions.During the growing season and after harvest, data related to phonological and morphological traits were recorded and measured. In this study, all evaluated traits were analyzed by variance analysis and the mean of genotypes was compared using the LSD method. Correlation analysis was performed using the Pearson method. In order to select the best genotypes in terms of yield and other agronomic traits, the SIIG index and genotype × trait biplot (GT) were used, and cluster analysis method was used to group the studied genotypes. GGEBiplot were used for the biplot analysis of the genotype × trait. Data were grouped using cluster analysis with SPSS software. The correlation between traits was calculated by pearson’s method using R software (GGALLY package). The Selection Index of Ideal Genotype (SIIG) was calculated in Excel.
Results: The results of variance analysis showed that there were significant differences between the genotypes for days to heading and days to maturity, plant height, spike length, peduncle length, number of spikelet per spike, number of grain per spike, grain weight per spike, and thousand kernel weight. This indicates genetic diversity among genotypes for evaluated traits. The highest grain yield was obtained for genotypes G8, G10 and G22 with average grain yield of 3522, 3362 and 3258 kg/ha, respectively. The results of trait correlation showed that there was a positive and highly significant correlation between grain yield and grain filling rate (r=0.90**). The SIIG index was positively and significantly correlated with peduncle length (r=0.63**), grain weight per spike (r=0.54**), grain yield (r=0.48*), and thousand-grain weight (r=0.41*). The results of the SIIG index showed that genotypes G8 and G16 were the best genotypes with the highest SIIG index values of 0.62 and 0.61, respectively. Genotype G14 with the lowest index value (0.32) was the weakest genotype for evaluated traits. In cluster analysis, the genotypes were divided into three groups, and the high-yielding genotypes G8, G10, G16, and G22 were placed in group 1. The genotypes of the third group had the lowest grain yield and other agronomic traits. Based on the GT biplot results, genotypes G4, G8, G10, G11 and G22 were the best for grain yield. Also, the mentioned genotypes had high 1000-grain weight, panicle length, peduncle length, plant height and grain filling period.
Conclusion: Based on the results obtained from the mean comparison, SIIG index, and GT biplot, the G8 genotype is recommended for use in breeding programs or as a promising line for the cultivar introduction program. According to the positive and highly significant correlation between grain yield and grain filling rate, the grain filling rate trait suggested as a valuable marker for identifying high-yielding durum wheat genotypes.
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