1- Agricultural Research, Education and Extension Organization (AREEO),
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Extended Abstract
Background: Barley (Hordeum vulgare L.) is an ancient and significant cereal crop, ranking fourth in production after wheat, rice, and maize, globally. Barley is recognized from other crops due to characteristic such as resistance to various biotic stresses, broad adaptability, and short growth duration. Genetic improvement is accelerated through the investigation of the genetic diversity in genetic materials across various environments. Since, the grain yield is a quantitative and inherited trait, it largely influenced by genotypic and environmental factors. Hence, indirect selection using other agronomic traits may be useful in identifying superior genotypes. The selection index of ideal genotype (SIIG) can be used to better rank and compare different genotypes and select the best genotypes, as well as determine the distances between genotypes and their clustering. with increasing number of traits or indices, it becomes difficult to select the appropriate genotype. In the SIIG index, all indexes or traits become one index and it becomes easier to rank and identify superior genotypes
Methods: To evaluate the genetic diversity and early screening of superior barley genotypes, an experiment was performed with 108 pure genotypes along with four check genotypes (Armaghan, Rehan 03, Furat 03 and V Morales) in an augmented design with in at Darab Agricultural and Natural Resources Research Station in the 2022-2023 cropping year. To select the superior genotypes in terms of grain yield and other measured traits, the SIIG index and principal components analysis (PCA) were used. The genotypes tested were planted in three genotypes in 2.5 m in long and 15 cm space between them. Seed density was determined as 300 seeds per square. The measured traits included of grain yield (GY), thousand grain weight (TGW), grain filling rate (GFR), plant height (PLH), number of days to heading (DHE), and number of days to physiological maturity (DMA). ACBD software was used to estimate the variance components and means comparison test. The SIIG index and principal component analysis (PCA) were computed R software.
Results: The results of restricted maximum likelihood (REML) analysis showed the lowest heritability values were related to the TGW (60%) and DMA (66%), while the highest values were found for PLH (96%) and GFR (91%). The grain yield varied between 1600 and 7833 kg ha-1 across investigated genotypes, indicating the significant difference and other words a high level of genetic diversity among them. The highest grain yield was recorded for genotype numbers No. 83, 57 and 27 with a value of 7833, 7300 and 7100 kg ha-1, respectively. The highest and lowest TGW were related to genotype numbers No. 17 (67.1 gr) and 56 (36.2 gr), respectively. As a result, two-row genotypes showed the highest TGW, so the average TGW varied between 52.6 grin two-row genotypes and 45.8 gr in six-row genotypes. Our results showed that the average GFR in two-row genotypes (120.7 kg ha-1) was higher than the average GFR in six-row barley (110.3 kg ha-1). Moreover, DHE ranged from 131 to 144 days. On the other hand, the average of DMA was 139 days in two-row barley and 141 in six-row barley. Principal component analysis was used to group genotypes and investigate the relationship among the measured traits. The first and second components justified 0.43 % and 29.7 % of the total phenotypic variation, respectively. In the first PC, SIIG index and GY and GFP traits had the largest contribution, respectively. In the second PC, DMA, DHE, TGW, and PLH showed the largest contribution. As a result, GY and GFR showed the strong correlation with SIIG index. Based on the PCA-based biplot, all investigated genotypes were divided into four groups. The first group consisted of the superior genotypes (No. 57, 83, 63, 66, 25, 68, 60, 61, 48, 27, 23, 1, 3, 34, 25, 12, and 20) with SIIG index greater than 0.6. The fourth group consisted of genotypes with SIIG index less than 0.4.
Conclusion: The results of this study revealed a high level of genetic diversity among the evaluated barley genotypes. The results showed that the SIIG index is a suitable tool for the initial screening of genotypes in the preliminary tests of performance comparison using different traits. Based on the PCA results, the genotypes categorized in the first group (with SIIG values above 0.6) were identified as superior genotypes and can be used for additional tests. Moreover, a high association was found between the results of the SIIG index and PCA in grouping the genetic materials.
Background: Barley (Hordeum vulgare L.) is an ancient and significant cereal crop, ranking fourth in production after wheat, rice, and maize, globally. Barley is recognized from other crops due to characteristic such as resistance to various biotic stresses, broad adaptability, and short growth duration. Genetic improvement is accelerated through the investigation of the genetic diversity in genetic materials across various environments. Since, the grain yield is a quantitative and inherited trait, it largely influenced by genotypic and environmental factors. Hence, indirect selection using other agronomic traits may be useful in identifying superior genotypes. The selection index of ideal genotype (SIIG) can be used to better rank and compare different genotypes and select the best genotypes, as well as determine the distances between genotypes and their clustering. with increasing number of traits or indices, it becomes difficult to select the appropriate genotype. In the SIIG index, all indexes or traits become one index and it becomes easier to rank and identify superior genotypes
Methods: To evaluate the genetic diversity and early screening of superior barley genotypes, an experiment was performed with 108 pure genotypes along with four check genotypes (Armaghan, Rehan 03, Furat 03 and V Morales) in an augmented design with in at Darab Agricultural and Natural Resources Research Station in the 2022-2023 cropping year. To select the superior genotypes in terms of grain yield and other measured traits, the SIIG index and principal components analysis (PCA) were used. The genotypes tested were planted in three genotypes in 2.5 m in long and 15 cm space between them. Seed density was determined as 300 seeds per square. The measured traits included of grain yield (GY), thousand grain weight (TGW), grain filling rate (GFR), plant height (PLH), number of days to heading (DHE), and number of days to physiological maturity (DMA). ACBD software was used to estimate the variance components and means comparison test. The SIIG index and principal component analysis (PCA) were computed R software.
Results: The results of restricted maximum likelihood (REML) analysis showed the lowest heritability values were related to the TGW (60%) and DMA (66%), while the highest values were found for PLH (96%) and GFR (91%). The grain yield varied between 1600 and 7833 kg ha-1 across investigated genotypes, indicating the significant difference and other words a high level of genetic diversity among them. The highest grain yield was recorded for genotype numbers No. 83, 57 and 27 with a value of 7833, 7300 and 7100 kg ha-1, respectively. The highest and lowest TGW were related to genotype numbers No. 17 (67.1 gr) and 56 (36.2 gr), respectively. As a result, two-row genotypes showed the highest TGW, so the average TGW varied between 52.6 grin two-row genotypes and 45.8 gr in six-row genotypes. Our results showed that the average GFR in two-row genotypes (120.7 kg ha-1) was higher than the average GFR in six-row barley (110.3 kg ha-1). Moreover, DHE ranged from 131 to 144 days. On the other hand, the average of DMA was 139 days in two-row barley and 141 in six-row barley. Principal component analysis was used to group genotypes and investigate the relationship among the measured traits. The first and second components justified 0.43 % and 29.7 % of the total phenotypic variation, respectively. In the first PC, SIIG index and GY and GFP traits had the largest contribution, respectively. In the second PC, DMA, DHE, TGW, and PLH showed the largest contribution. As a result, GY and GFR showed the strong correlation with SIIG index. Based on the PCA-based biplot, all investigated genotypes were divided into four groups. The first group consisted of the superior genotypes (No. 57, 83, 63, 66, 25, 68, 60, 61, 48, 27, 23, 1, 3, 34, 25, 12, and 20) with SIIG index greater than 0.6. The fourth group consisted of genotypes with SIIG index less than 0.4.
Conclusion: The results of this study revealed a high level of genetic diversity among the evaluated barley genotypes. The results showed that the SIIG index is a suitable tool for the initial screening of genotypes in the preliminary tests of performance comparison using different traits. Based on the PCA results, the genotypes categorized in the first group (with SIIG values above 0.6) were identified as superior genotypes and can be used for additional tests. Moreover, a high association was found between the results of the SIIG index and PCA in grouping the genetic materials.
Type of Study: Applicable |
Subject:
اصلاح نباتات، بیومتری
Received: 2024/10/5 | Accepted: 2024/11/12
Received: 2024/10/5 | Accepted: 2024/11/12
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