1- Horticulture Crop Research Department, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, AREEO, Mashhad, Iran
Abstract: (221 Views)
Extended Abstract
Background: After wheat, barley is the main crop in Iran and, according to the latest statistics from the Ministry of Agriculture (2023), the area under cultivation in Iran was reported to be 1.685 million hectares, of which the grain production was 3.177 million tons. Khorasan Razavi Province ranks first in barley production in Iran, with the production of 415,736 tons per hectare. Due to the low expectation of the barley crop in relation to water and soil conditions, this crop can have a better position in most of the poor, low rainfall, salty, and low-water lands of the country. An increase in yield is one of the primary aims pursued in plant breeding programs. Similar to other crops, insufficient yield stability in barley is recognized as one of the factors responsible for the gap between actual yield and potential yield. In breeding programs, the identification of superior genotypes is difficult due to the environmental variability of target locations and the interaction of these variabilities with the investigated genotypes. Therefore, it is important to evaluate the advanced agronomic lines across various environments and over multiple years to ensure their yield stability and production. Many statistical models have been suggested to analyze the G × E interaction. The GGE (genotype plus genotype-by-environment) biplot method is a multivariate model based on principal component analysis, which simultaneously represents the G, E, and G × E interaction on a graph known as the biplot. The GGE biplot is widely used in agricultural research as it provides a simple graphical interpretation of the G × E interaction. The main objective of this study was to select the superior barley genotypes based on grain yield and their stability in the temperate regions of Khorasan Razavi Province.
Methods: Nineteen promising barley lines, along with a check cultivar Behrokh, were studied during 2018-2020 in Neishabour and Mashhad regions located in Khorasan Razavi Province. The experimental design was a randomized complete block with three replications. Univariate (the environmental coefficient of variation and Eberhart and Russell parameters) and multivariate (GGE biplot) methods were used to yield the stability assessment of genotypes. Combined analysis of variance for grain yield was analyzed using ADEL-R software. The methodologies for the GGE biplot and univariate stability indices biplots were employed to analyze the G × E interaction and characterize barley genotypes using GEA-R software.
Results: The combined analysis of variance showed that the main effect of the environment and the G × E interaction were significant at the 1% probability level, while the main effect of the genotype was significant at the 5% probability level. Moreover, about 51%, 5.24%, and 19.41% of the total variation were related to the environment effect, the genotype effect, and the G × E interaction, respectively. Overall, the average grain yield of the evaluated lines ranged from 5.838 to 6.651 ton /ha, and the G15, G16, and G12 lines produced the lowest, and G8, G9, G11, G19, and G20 presented the highest grain yields, respectively. Based on the environmental coefficient of variation, G3 and G2 were the most stable genotypes, respectively, but their grain yield was lower than the overall average. Based on this method, G11, G9, and G19 were selected as stable genotypes with higher-than-average yields. The regression coefficient graph and the deviation coefficient from regression introduced the G2 genotype, which produced a below-average yield, as a stable genotype and G8, which was one of the most yielding lines, as the genotype with high compatibility. The simultaneous evaluation of grain yield and stability through the average environment coordinate (AEC) biplot showed that genotype G8 with a high grain yield was the most stable genotype. There were many similarities between 2 years of Mashhad (the first environmental group) and 2 years of Neishbour (the second environmental group). The angles between these two environmental groups were about 90 degrees, indicating that they were independent in ranking genotypes. Among the investigated environments, the environment of Mashhad in 2017 was close to the ideal environment. An ideal environment should clearly discriminate among genotypes and simultaneously be a good representative of the target environment. According to the resulting biplot of barley promising lines in comparison with the ideal genotype, G8 was identified as the ideal genotype. Moreover, the closest genotypes to it were G20 and G19. Overall, the mentioned promising lines presented high grain yield, stability, and good general compatibility in the investigated environments compared to the other genotypes. The GGE biplot method is based on agronomic compatibility and stability, and therefore, the genotypes that are selected in this way have high performance, in addition to stability and compatibility.
Conclusion: Based on the results of this study, lines G8, G20, and G19 showed high grain yield, good stability, and general adaptability in temperate and cold temperate regions of Khorasan Razavi Province. Therefore, the promising line/lines that retain their high yield and favorable characteristics compared to check cultivars after being examined in extension research experiments at farmers’ conditions of temperate regions, can be selected as candidates for naming and introduction.
Background: After wheat, barley is the main crop in Iran and, according to the latest statistics from the Ministry of Agriculture (2023), the area under cultivation in Iran was reported to be 1.685 million hectares, of which the grain production was 3.177 million tons. Khorasan Razavi Province ranks first in barley production in Iran, with the production of 415,736 tons per hectare. Due to the low expectation of the barley crop in relation to water and soil conditions, this crop can have a better position in most of the poor, low rainfall, salty, and low-water lands of the country. An increase in yield is one of the primary aims pursued in plant breeding programs. Similar to other crops, insufficient yield stability in barley is recognized as one of the factors responsible for the gap between actual yield and potential yield. In breeding programs, the identification of superior genotypes is difficult due to the environmental variability of target locations and the interaction of these variabilities with the investigated genotypes. Therefore, it is important to evaluate the advanced agronomic lines across various environments and over multiple years to ensure their yield stability and production. Many statistical models have been suggested to analyze the G × E interaction. The GGE (genotype plus genotype-by-environment) biplot method is a multivariate model based on principal component analysis, which simultaneously represents the G, E, and G × E interaction on a graph known as the biplot. The GGE biplot is widely used in agricultural research as it provides a simple graphical interpretation of the G × E interaction. The main objective of this study was to select the superior barley genotypes based on grain yield and their stability in the temperate regions of Khorasan Razavi Province.
Methods: Nineteen promising barley lines, along with a check cultivar Behrokh, were studied during 2018-2020 in Neishabour and Mashhad regions located in Khorasan Razavi Province. The experimental design was a randomized complete block with three replications. Univariate (the environmental coefficient of variation and Eberhart and Russell parameters) and multivariate (GGE biplot) methods were used to yield the stability assessment of genotypes. Combined analysis of variance for grain yield was analyzed using ADEL-R software. The methodologies for the GGE biplot and univariate stability indices biplots were employed to analyze the G × E interaction and characterize barley genotypes using GEA-R software.
Results: The combined analysis of variance showed that the main effect of the environment and the G × E interaction were significant at the 1% probability level, while the main effect of the genotype was significant at the 5% probability level. Moreover, about 51%, 5.24%, and 19.41% of the total variation were related to the environment effect, the genotype effect, and the G × E interaction, respectively. Overall, the average grain yield of the evaluated lines ranged from 5.838 to 6.651 ton /ha, and the G15, G16, and G12 lines produced the lowest, and G8, G9, G11, G19, and G20 presented the highest grain yields, respectively. Based on the environmental coefficient of variation, G3 and G2 were the most stable genotypes, respectively, but their grain yield was lower than the overall average. Based on this method, G11, G9, and G19 were selected as stable genotypes with higher-than-average yields. The regression coefficient graph and the deviation coefficient from regression introduced the G2 genotype, which produced a below-average yield, as a stable genotype and G8, which was one of the most yielding lines, as the genotype with high compatibility. The simultaneous evaluation of grain yield and stability through the average environment coordinate (AEC) biplot showed that genotype G8 with a high grain yield was the most stable genotype. There were many similarities between 2 years of Mashhad (the first environmental group) and 2 years of Neishbour (the second environmental group). The angles between these two environmental groups were about 90 degrees, indicating that they were independent in ranking genotypes. Among the investigated environments, the environment of Mashhad in 2017 was close to the ideal environment. An ideal environment should clearly discriminate among genotypes and simultaneously be a good representative of the target environment. According to the resulting biplot of barley promising lines in comparison with the ideal genotype, G8 was identified as the ideal genotype. Moreover, the closest genotypes to it were G20 and G19. Overall, the mentioned promising lines presented high grain yield, stability, and good general compatibility in the investigated environments compared to the other genotypes. The GGE biplot method is based on agronomic compatibility and stability, and therefore, the genotypes that are selected in this way have high performance, in addition to stability and compatibility.
Conclusion: Based on the results of this study, lines G8, G20, and G19 showed high grain yield, good stability, and general adaptability in temperate and cold temperate regions of Khorasan Razavi Province. Therefore, the promising line/lines that retain their high yield and favorable characteristics compared to check cultivars after being examined in extension research experiments at farmers’ conditions of temperate regions, can be selected as candidates for naming and introduction.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
