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Showing 3 results for Shobeiri
Seyedeh Soudabeh Shobeiri, Davood Sadeghzadeh Ahari, Payam Pezeshkpour, Mahmoud Azimi,
Volume 13, Issue 40 (12-2021)
Volume 13, Issue 40 (12-2021)
Abstract
Extended Abstract
Introduction and Objective: Improper distribution of rainfall and reduced rainfall are major factors in reducing lentil yield per unit area . Therefore, the use of genotypes adapted to adverse environmental conditions can play an important role in increasing yield in such conditions. Awareness of genotype × environment interactions helps breeds to be more accurate in evaluating genotypes and choosing the best genotypes.
Materials and Methods: This study was conducted during two years (2019-2020 and 2020-2021) in two stations in the cold dry areas of the country (Qeydar Zanjan, Maragheh). The experiment consisted of 17 advanced lentil genotypes along with three control cultivars Kimia, Bilesvar and Senna (20 genotypes in total) which was performed in a randomized complete block design with 3 replications.
Results: The results of combined analysis showed a significant difference in the level of one percent probability for environment, genotype and genotype × environment interaction. The results of combined analysis of variance showed that the environment, genotype and genotype by environment interaction effects were 79.5%, 2.25% and 18.23% of total variance, respectively The results of GGE biplot indicate the existence of 42.1% of the total changes related to the first component and 26% of the total changes related to the second component, which together explain 68.1% of the total changes. According to the obtained results, there is a high correlation between E1 and E3 environments and between E2 and E4 environments and they can be introduced as similar environments. In biplot study, genotypes 7 (FLIP2013-29L), 13 (FLIP 2012-262 L) and 11 (FLIP 2012-207L) had higher performance and stability at the same time.
Conclusion: Genotypes 13, 7 and 11 were introduced as high yielding and stable genotypes and can be used to select or recommend a variety.
Introduction and Objective: Improper distribution of rainfall and reduced rainfall are major factors in reducing lentil yield per unit area . Therefore, the use of genotypes adapted to adverse environmental conditions can play an important role in increasing yield in such conditions. Awareness of genotype × environment interactions helps breeds to be more accurate in evaluating genotypes and choosing the best genotypes.
Materials and Methods: This study was conducted during two years (2019-2020 and 2020-2021) in two stations in the cold dry areas of the country (Qeydar Zanjan, Maragheh). The experiment consisted of 17 advanced lentil genotypes along with three control cultivars Kimia, Bilesvar and Senna (20 genotypes in total) which was performed in a randomized complete block design with 3 replications.
Results: The results of combined analysis showed a significant difference in the level of one percent probability for environment, genotype and genotype × environment interaction. The results of combined analysis of variance showed that the environment, genotype and genotype by environment interaction effects were 79.5%, 2.25% and 18.23% of total variance, respectively The results of GGE biplot indicate the existence of 42.1% of the total changes related to the first component and 26% of the total changes related to the second component, which together explain 68.1% of the total changes. According to the obtained results, there is a high correlation between E1 and E3 environments and between E2 and E4 environments and they can be introduced as similar environments. In biplot study, genotypes 7 (FLIP2013-29L), 13 (FLIP 2012-262 L) and 11 (FLIP 2012-207L) had higher performance and stability at the same time.
Conclusion: Genotypes 13, 7 and 11 were introduced as high yielding and stable genotypes and can be used to select or recommend a variety.
Adel Ghadiri, Seiedeh Soodabeh Shobeiri, Ali Akbar Asadi1,
Volume 15, Issue 45 (5-2023)
Volume 15, Issue 45 (5-2023)
Abstract
Extended Abstract
Introduction and Objective: Existence of genotype × environment interaction for quantitative traits such as grain yield can limit the selection of superior genotypes for the development of improved cultivars. In order to calculate the interaction of genotype × environment, breeders evaluate genotypes in several environments to identify genotypes with high yield and stability. This experiment was performed to investigate the interaction of genotype in the environment on 11 bean genotypes using parametric and nonparametric methods and GGE bioplot model to evaluate genotypes and environments, determine the relationship between genotypes and environments and identify the ideal genotype.
Material and Methods: In this experiment, 9 lines of pinto beans along with Ghaffar cultivars and Cos16 lines (11 lines in total) were performed in a randomized complete block design with three replications in order to achieve high yield and marketable bean cultivars. Parametric and non-parametric methods were used to select stable genotypes with high yield and GGE bioplot analysis was used to select superior genotypes that are compatible with regional environments.
Results: There was a significant interaction between genotype and environment, indicating significant differences in the response of genotypes to different environments of the experiment. In parametric methods G4, G8, G9 and to some extent G2 genotypes and in nonparametric methods G2, G8, G3, G4 and to some extent G9 genotypes were introduced as stable cultivars. Biplot analysis showed that G1 genotype in Zanjan in first and Second years and G2 genotype in Khomein n first and second environments showed the highest yield. G11 and G7 genotypes with the longest distance to the ATC line had low yield and low yield stability. None of the genotypes were found to be desirable genotypes with average yield and high yield stability, but G2 genotype and later, G4 genotype was a short distance from the ideal genotype. None of the studied environments is close to the ideal environment and therefore none of them can be considered as representative of environments for genotype segregation.
Results: Zanjan in first and Second years and G2 genotype in Khomein n first and second environments have the highest yield. No ideal genotypes were observed, but two genotypes, G1 and G4, can be introduced as superior genotypes.
Introduction and Objective: Existence of genotype × environment interaction for quantitative traits such as grain yield can limit the selection of superior genotypes for the development of improved cultivars. In order to calculate the interaction of genotype × environment, breeders evaluate genotypes in several environments to identify genotypes with high yield and stability. This experiment was performed to investigate the interaction of genotype in the environment on 11 bean genotypes using parametric and nonparametric methods and GGE bioplot model to evaluate genotypes and environments, determine the relationship between genotypes and environments and identify the ideal genotype.
Material and Methods: In this experiment, 9 lines of pinto beans along with Ghaffar cultivars and Cos16 lines (11 lines in total) were performed in a randomized complete block design with three replications in order to achieve high yield and marketable bean cultivars. Parametric and non-parametric methods were used to select stable genotypes with high yield and GGE bioplot analysis was used to select superior genotypes that are compatible with regional environments.
Results: There was a significant interaction between genotype and environment, indicating significant differences in the response of genotypes to different environments of the experiment. In parametric methods G4, G8, G9 and to some extent G2 genotypes and in nonparametric methods G2, G8, G3, G4 and to some extent G9 genotypes were introduced as stable cultivars. Biplot analysis showed that G1 genotype in Zanjan in first and Second years and G2 genotype in Khomein n first and second environments showed the highest yield. G11 and G7 genotypes with the longest distance to the ATC line had low yield and low yield stability. None of the genotypes were found to be desirable genotypes with average yield and high yield stability, but G2 genotype and later, G4 genotype was a short distance from the ideal genotype. None of the studied environments is close to the ideal environment and therefore none of them can be considered as representative of environments for genotype segregation.
Results: Zanjan in first and Second years and G2 genotype in Khomein n first and second environments have the highest yield. No ideal genotypes were observed, but two genotypes, G1 and G4, can be introduced as superior genotypes.
Behrouz Asadi, Seyedeh Soudabeh Shobeiri, Ali Akbar Asadi, , ,
Volume 16, Issue 1 (4-2024)
Volume 16, Issue 1 (4-2024)
Abstract
Extended Abstract
Introduction and Objectives: The evaluation of the genotype × environment interaction effect provides valuable information regarding the yield of plant cultivars in different environments and plays an important role in evaluating the stability of the yield of breeding cultivars. Genotype × environment interaction effect, especially in stressful environments, are important limiting factors in the introduction of new cultivars; therefore, it is very important to know the type and nature of the interaction effect and reach the verities that have the least role in creating interaction effects. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The results of different methods may not be the same, but the best result is obtained when a genotype with different evaluation methods shows similar results in terms of stability. The purpose of this research was to evaluate the genotype × environment interaction effect in experiments conducted in different environments, to determine the relationships between genotypes and environments and to introduce the most stable red bean genotypes.
Material and Methods: In this research, 14 red bean lines along with Yakut, Ofog and Dadfar control cultivars were cultivated in the form of a randomized complete block design with three replications in Khomein, Borujerd, Shahrekord and Zanjan research stations for 2 crop years under the same conditions. After combined variance analysis, according to the significance of genotype × environment interaction, AMMI and GGE-Biplot analysis methods were used to determine the compatibility and stability of genotypes. After AMMI Analysis, the stability parameters of AMMI were calculated. In addition to the AMMI stability parameters, the simultaneous selection index was also calculated for each of the indices, which was the sum of the rank of the genotypes based on each of the AMMI stability indices and the average seed yield rank of the genotypes in all environments.
Results: The significance of the double and triple interaction effects of genotype with year and place (environment) in this study showed that genotypes showed different responses in different environments, and in other words, the difference between genotypes is not the same from one environment to another, and in these conditions, the stability of grain yield can be evaluated. The contribution of about 2.5 times the interaction effect of genotype × environment from the total sum of squares, compared to the effect of genotype, indicated the possibility of the existence of mega-environmental groups in which some genotypes show their maximum performance potential in those environmental groups. Genotypes G12, G5 and G17 had the highest seed yield among the genotypes with yields of 3288, 3136 and 3111 kg per hectare, respectively. AMMI analysis showed that the first to seventh main components were significant at the 1% probability level, and despite the significance of all model components, the first and second main components had the largest contribution to the expression of genotype × environment interaction (66.5%). Based on AMMI1 biplot Genotypes G4, G5, G16, G17 and G12 had the highest values (positive and negative) of IPCA1. In contrast, genotypes G8, G3, G2, G7 and G11 had IPCA1 values close to zero. However, only the genotype G11 showed a performance higher than the average total yield and therefore it can be introduced as a stable genotype with high general compatibility. Based on AMMI2 biplot, genotypes G2, G7, G3 and to some extent G8 and G13 were introduced as stable genotypes, but only G13 genotype had a higher yield in all environments, so this genotype can be introduced as a stable genotype with good yield.; also, every two years, the same place under investigation had a high correlation with each other, so that Bro1 and Bro2 environments on the one hand and Kho1 and Kho2 environments and finally Zan1 and Zan2 showed a high positive correlation (the same effect) to create a mutual effect. In total of the simultaneous selection indices calculated based on AMMI analysis, genotypes G11, G17, G7, G13 and G12 were introduced as stable genotypes with high yield. GGE-Biplot analysis based on average yield and stability showed that genotypes G1, G2, G3, G8 and G7 had the highest general stability compared to other genotypes despite having the lowest yield. On the other hand, G12, G5 and G17 genotypes had the highest yield with less stability. No ideal environment was observed. But Kho1, Kho2 and Sha1 environments are closer to the ideal environment than other environments and they can be used to distinguish the studied genotypes to some extent. On the other hand, G12 genotype can be considered as a desirable genotype that has high average yield and high yield stability. In the same way, G17, G5 and G11 genotypes were in the next stage compared to the ideal genotype and to some extent they can also be considered as desirable genotypes.
Conclusion: According to all the results, G12 genotype can be considered as a desirable genotype that has a high average yield and also has yield stability, and G17, G5 and G11 genotypes were in the next stage.
Introduction and Objectives: The evaluation of the genotype × environment interaction effect provides valuable information regarding the yield of plant cultivars in different environments and plays an important role in evaluating the stability of the yield of breeding cultivars. Genotype × environment interaction effect, especially in stressful environments, are important limiting factors in the introduction of new cultivars; therefore, it is very important to know the type and nature of the interaction effect and reach the verities that have the least role in creating interaction effects. Various methods have been introduced to evaluate the interaction effect, each of which examines the nature of the interaction effect from a specific point of view. The results of different methods may not be the same, but the best result is obtained when a genotype with different evaluation methods shows similar results in terms of stability. The purpose of this research was to evaluate the genotype × environment interaction effect in experiments conducted in different environments, to determine the relationships between genotypes and environments and to introduce the most stable red bean genotypes.
Material and Methods: In this research, 14 red bean lines along with Yakut, Ofog and Dadfar control cultivars were cultivated in the form of a randomized complete block design with three replications in Khomein, Borujerd, Shahrekord and Zanjan research stations for 2 crop years under the same conditions. After combined variance analysis, according to the significance of genotype × environment interaction, AMMI and GGE-Biplot analysis methods were used to determine the compatibility and stability of genotypes. After AMMI Analysis, the stability parameters of AMMI were calculated. In addition to the AMMI stability parameters, the simultaneous selection index was also calculated for each of the indices, which was the sum of the rank of the genotypes based on each of the AMMI stability indices and the average seed yield rank of the genotypes in all environments.
Results: The significance of the double and triple interaction effects of genotype with year and place (environment) in this study showed that genotypes showed different responses in different environments, and in other words, the difference between genotypes is not the same from one environment to another, and in these conditions, the stability of grain yield can be evaluated. The contribution of about 2.5 times the interaction effect of genotype × environment from the total sum of squares, compared to the effect of genotype, indicated the possibility of the existence of mega-environmental groups in which some genotypes show their maximum performance potential in those environmental groups. Genotypes G12, G5 and G17 had the highest seed yield among the genotypes with yields of 3288, 3136 and 3111 kg per hectare, respectively. AMMI analysis showed that the first to seventh main components were significant at the 1% probability level, and despite the significance of all model components, the first and second main components had the largest contribution to the expression of genotype × environment interaction (66.5%). Based on AMMI1 biplot Genotypes G4, G5, G16, G17 and G12 had the highest values (positive and negative) of IPCA1. In contrast, genotypes G8, G3, G2, G7 and G11 had IPCA1 values close to zero. However, only the genotype G11 showed a performance higher than the average total yield and therefore it can be introduced as a stable genotype with high general compatibility. Based on AMMI2 biplot, genotypes G2, G7, G3 and to some extent G8 and G13 were introduced as stable genotypes, but only G13 genotype had a higher yield in all environments, so this genotype can be introduced as a stable genotype with good yield.; also, every two years, the same place under investigation had a high correlation with each other, so that Bro1 and Bro2 environments on the one hand and Kho1 and Kho2 environments and finally Zan1 and Zan2 showed a high positive correlation (the same effect) to create a mutual effect. In total of the simultaneous selection indices calculated based on AMMI analysis, genotypes G11, G17, G7, G13 and G12 were introduced as stable genotypes with high yield. GGE-Biplot analysis based on average yield and stability showed that genotypes G1, G2, G3, G8 and G7 had the highest general stability compared to other genotypes despite having the lowest yield. On the other hand, G12, G5 and G17 genotypes had the highest yield with less stability. No ideal environment was observed. But Kho1, Kho2 and Sha1 environments are closer to the ideal environment than other environments and they can be used to distinguish the studied genotypes to some extent. On the other hand, G12 genotype can be considered as a desirable genotype that has high average yield and high yield stability. In the same way, G17, G5 and G11 genotypes were in the next stage compared to the ideal genotype and to some extent they can also be considered as desirable genotypes.
Conclusion: According to all the results, G12 genotype can be considered as a desirable genotype that has a high average yield and also has yield stability, and G17, G5 and G11 genotypes were in the next stage.
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