Volume 17, Issue 2 (5-2025)
J Crop Breed 2025, 17(2): 43-55 |
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Zali H, Pour-Aboughadareh A, Vanda M. (2025). Evaluation of Genetic Diversity in Two- and Six-Row Barley Genotypes with an Emphasis on the Selection of Superior Genotypes Using Multivariate Methods. J Crop Breed. 17(2), 43-55. doi:10.61882/jcb.2024.1577
URL: http://jcb.sanru.ac.ir/article-1-1577-en.html
URL: http://jcb.sanru.ac.ir/article-1-1577-en.html
1- Department of Crop and Horticultural Science Research, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Darab, Iran
2- Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3- Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Darab, Iran
2- Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3- Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Darab, Iran
Abstract: (841 Views)
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 characteristics such as resistance to various biotic stresses, broad adaptability, and short growth duration. Genetic improvement is accelerated through the investigation of genetic diversity in genetic materials across various environments. Since grain yield is a quantitative and inherited trait, it is 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 genotypes (SIIG) can be used to better rank and compare different genotypes, select the best genotypes, and determine distances between genotypes and their clustering. With the increase in the number of traits or indices, it becomes difficult to select the appropriate genotype. In the SIIG index, all indices 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 in the Darab Agricultural and Natural Resources Research Station in the 2022-2023 cropping year. The SIIG index and principal component analysis (PCA) were used to select the superior genotypes in terms of grain yield and other measured traits. The genotypes tested were planted in three genotypes of 2.5 m long and 15 cm apart. Seed density was determined as 300 seeds per square. The measured traits included 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 the mean comparison test. The SIIG index and PCA were computed with R software.
Results: The results of restricted maximum likelihood (REML) analysis showed that the lowest heritability values belonged to 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 a significant difference and a high level of genetic diversity among them. The highest grain yield was recorded for genotypes 83, 57, and 27 with values of 7833, 7300, and 7100 kg ha-1, respectively. The highest and lowest TGW values were measured for genotypes 17 (67.1 g) and 56 (36.2 g), respectively. As a result, two-row genotypes showed the highest TGW; thus, the average TGW varied between 52.6 g in two-row genotypes and 45.8 g in six-row genotypes. The average GFR in two-row genotypes (120.7 kg ha-1) was higher than that 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 days in six-row barley. PCA 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, the 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 a strong correlation with the SIIG index. Based on the PCA-based biplot, all investigated genotypes were divided into four groups. The first group consisted of the superior genotypes (57, 83, 63, 66, 25, 68, 60, 61, 48, 27, 23, 1, 3, 34, 25, 12, and 20) with an SIIG index greater than 0.6. The fourth group consisted of genotypes with an 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 show 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 characteristics such as resistance to various biotic stresses, broad adaptability, and short growth duration. Genetic improvement is accelerated through the investigation of genetic diversity in genetic materials across various environments. Since grain yield is a quantitative and inherited trait, it is 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 genotypes (SIIG) can be used to better rank and compare different genotypes, select the best genotypes, and determine distances between genotypes and their clustering. With the increase in the number of traits or indices, it becomes difficult to select the appropriate genotype. In the SIIG index, all indices 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 in the Darab Agricultural and Natural Resources Research Station in the 2022-2023 cropping year. The SIIG index and principal component analysis (PCA) were used to select the superior genotypes in terms of grain yield and other measured traits. The genotypes tested were planted in three genotypes of 2.5 m long and 15 cm apart. Seed density was determined as 300 seeds per square. The measured traits included 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 the mean comparison test. The SIIG index and PCA were computed with R software.
Results: The results of restricted maximum likelihood (REML) analysis showed that the lowest heritability values belonged to 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 a significant difference and a high level of genetic diversity among them. The highest grain yield was recorded for genotypes 83, 57, and 27 with values of 7833, 7300, and 7100 kg ha-1, respectively. The highest and lowest TGW values were measured for genotypes 17 (67.1 g) and 56 (36.2 g), respectively. As a result, two-row genotypes showed the highest TGW; thus, the average TGW varied between 52.6 g in two-row genotypes and 45.8 g in six-row genotypes. The average GFR in two-row genotypes (120.7 kg ha-1) was higher than that 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 days in six-row barley. PCA 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, the 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 a strong correlation with the SIIG index. Based on the PCA-based biplot, all investigated genotypes were divided into four groups. The first group consisted of the superior genotypes (57, 83, 63, 66, 25, 68, 60, 61, 48, 27, 23, 1, 3, 34, 25, 12, and 20) with an SIIG index greater than 0.6. The fourth group consisted of genotypes with an 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 show 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: 2025/02/2
Received: 2024/10/5 | Accepted: 2025/02/2
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