Farhad Ahakpaz1 
, Ali Akbar Asadi *2 , Abdolvahab Abdulahi3, Elyas Neyestani4 , Fereshteh Seif5 , Mohamad Sharif Khaledian6 , Seif Amiri Saber7 , Behrooz Mohammadi8 , Teymor Dolatpanah9
, Ali Akbar Asadi *2 , Abdolvahab Abdulahi3, Elyas Neyestani4 , Fereshteh Seif5 , Mohamad Sharif Khaledian6 , Seif Amiri Saber7 , Behrooz Mohammadi8 , Teymor Dolatpanah9
1- Assistant Professor Maragheh Rainfed Agricultural Research Institute, Iran
2- Crop and Horticultural Science Research department,Zanjan Agricultural and Natural Resources Research and Education Center, AREEO, Zanjan, Iran.
3- Assistant Professor of Cereal Research Department, Rainfed Agricultural Research Institute, Sararoud, Kermanshah, Iran
4- Assistant of Professor, Crop and Horticultural Science Research department, North Khorasan Agricultural and Natural Resources Research and Education Center, AREEO, Bojnurd, Iran.
5- Expert of Crop and Horticultural Science Research department, Hamedan Agricultural and Natural Resources Research and Education Center, AREEO, Hamedan, Iran
6- Expert of Crop and Horticultural Science Research department, Kordestan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj, Iran.
7- Instructor of Crop and Horticultural Science Research department, Ardabil Agricultural and Natural Resources Research and Education Center, AREEO, Ardabil, Iran.
8- Expert of Crop and Horticultural Science Research department, Zanjan Agricultural and Natural Resources Research and Education Center, AREEO, Zanjan, Iran
9- - Expert of the Rainfed Agricultural Research Institute
2- Crop and Horticultural Science Research department,Zanjan Agricultural and Natural Resources Research and Education Center, AREEO, Zanjan, Iran.
3- Assistant Professor of Cereal Research Department, Rainfed Agricultural Research Institute, Sararoud, Kermanshah, Iran
4- Assistant of Professor, Crop and Horticultural Science Research department, North Khorasan Agricultural and Natural Resources Research and Education Center, AREEO, Bojnurd, Iran.
5- Expert of Crop and Horticultural Science Research department, Hamedan Agricultural and Natural Resources Research and Education Center, AREEO, Hamedan, Iran
6- Expert of Crop and Horticultural Science Research department, Kordestan Agricultural and Natural Resources Research and Education Center, AREEO, Sanandaj, Iran.
7- Instructor of Crop and Horticultural Science Research department, Ardabil Agricultural and Natural Resources Research and Education Center, AREEO, Ardabil, Iran.
8- Expert of Crop and Horticultural Science Research department, Zanjan Agricultural and Natural Resources Research and Education Center, AREEO, Zanjan, Iran
9- - Expert of the Rainfed Agricultural Research Institute
Abstract: (123 Views)
Introduction and Objective: Considering the diversity in climatic conditions, agricultural management and the extent of barley cultivation areas in the country and observing the different reactions of different cultivars to environmental conditions, it is of particular importance to introduce high-yielding cultivars with wide adaptability to different conditions. Due to genotype × environment interaction effect, it is difficult to identify cultivars that have good stability and acceptable yield in various environmental conditions. Therefore, cultivars should be studied in a wide range of environmental changes in different locations and years so that the information obtained from the estimation of compatibility and yield stability of genotypes is a more reliable criterion for recommending cultivars and their efficiency. The methods for determining the genotype × environment interaction effect are divided into two groups: single variable (parametric and non-parametric) and multivariable. Each of these methods show different aspects of the stability of genotypes, and one method alone cannot investigate the yield of a genotype in different environments from different aspects of stability. The aim of this research was to select promising barley genotypes with high yield and suitable stability in dry conditions in the cold climate of the country using parametric and non-parametric univariate stability analysis methods.
Materials and Methods: 25 advanced and promising lines of barley along with Ansar, Abider and Sararoud1 (check cultivar) in dry conditions in completely randomized block design with four repetitions in research stations of Maragheh, Kurdistan (Qamlo), Zanjan (Qidar), Ardabil, Kermanshah (Sararoud), Shirvan and Hamedan were studied for three crop seasons from 2016 to 2019. To check the stability of genotypes, parametric and non-parametric univariate methods were used. Also, in order to integrate parametric and non-parametric univariate methods, selection ideal index genotype method was used. Finally, the correlation of the parameters with yield and the selection ideal index was also calculated.
Findings: Separate analysis of variance in each of the environments showed that the genotype effect was significant in 12 out of 19 environments, which indicated the fluctuation of the yield of each genotype from one environment to another. Combined variance analysis showed that the interaction effects of year × location and genotype × year × location were significant at the 1%, the year effect at the 5%, and the location and genotype effects were significant at the 10% probability level. The main effect of the environment and the genotype × environment interaction effect had the largest share in the total sum of squares observed in the experiments with 69.98 and 10.83%, respectively. Eberhart and Russel's analysis identified genotypes G1, G4, G5, G8, G9, G10 and G26 as the most stable genotypes due to having the lowest deviation from regression and a regression coefficient close to one; finally, considering the yield, G9 and G10 genotypes were introduced as stable genotypes with high yield. According to Finley and Wilkinson's linear regression coefficient, genotypes G4, G6, G9, G11, G12, G15, G17, G20, G27 and G28 had a regression coefficient close to one, which shows that these genotypes have general adaptability to environments. Based on Wrick's equivalence index and shukla stability variance, genotypes G8, G19, G10, G20, G9, G4, G26 and G1 were identified as stable genotypes. Based on the coefficient of environmental variation, genotypes G10, G1, G8, G23, G13, G2 and G5 had the lowest coefficient of variation. Based on Plasted and Peterson method, genotypes G10, G20, G19 and G9 were selected as stable genotypes with high yield. In the Plaisted method, genotypes G10, G20, G19 and G9 with the least contribution in creating interaction and having the desired yield were introduced as stable and high yielding genotypes. Based on Lin and Bains, genotypes G15, G6, G21, G19, G20, G7 and G9 had the least amount of this statistic and were introduced as the most stable genotypes. Based on Kang's total rank method, G20, G19, G10, G9 and G22 genotypes with the lowest total rank were selected as stable genotypes. Based on parameters of Nassar and Huhn, genotypes G8, G9, G10, G1, G20, G19 and G21 and based on parameters of Thenarasu, genotypes G8, G9, G10, G1, G19 and G22 with the lowest rank were selected as stable genotypes. Finally, based on the selection ideal index genotype, genotypes G10, G9, G19, G22 and G20 had the closest value to one and had a higher yield than the overall average; therefore, they were selected as the most stable genotypes.
Conclusion: Based on the selection ideal index genotype (SIIG index), genotypes G10, G9, G19, G22 and G20 had the closest value to one and also had yield above the average; therefore, they were selected as the most stable genotypes. Also, the use of SIIG index is recommended due to the high correlation with all the indices used to summarize the results of parametric and non-parametric stability indices.
Materials and Methods: 25 advanced and promising lines of barley along with Ansar, Abider and Sararoud1 (check cultivar) in dry conditions in completely randomized block design with four repetitions in research stations of Maragheh, Kurdistan (Qamlo), Zanjan (Qidar), Ardabil, Kermanshah (Sararoud), Shirvan and Hamedan were studied for three crop seasons from 2016 to 2019. To check the stability of genotypes, parametric and non-parametric univariate methods were used. Also, in order to integrate parametric and non-parametric univariate methods, selection ideal index genotype method was used. Finally, the correlation of the parameters with yield and the selection ideal index was also calculated.
Findings: Separate analysis of variance in each of the environments showed that the genotype effect was significant in 12 out of 19 environments, which indicated the fluctuation of the yield of each genotype from one environment to another. Combined variance analysis showed that the interaction effects of year × location and genotype × year × location were significant at the 1%, the year effect at the 5%, and the location and genotype effects were significant at the 10% probability level. The main effect of the environment and the genotype × environment interaction effect had the largest share in the total sum of squares observed in the experiments with 69.98 and 10.83%, respectively. Eberhart and Russel's analysis identified genotypes G1, G4, G5, G8, G9, G10 and G26 as the most stable genotypes due to having the lowest deviation from regression and a regression coefficient close to one; finally, considering the yield, G9 and G10 genotypes were introduced as stable genotypes with high yield. According to Finley and Wilkinson's linear regression coefficient, genotypes G4, G6, G9, G11, G12, G15, G17, G20, G27 and G28 had a regression coefficient close to one, which shows that these genotypes have general adaptability to environments. Based on Wrick's equivalence index and shukla stability variance, genotypes G8, G19, G10, G20, G9, G4, G26 and G1 were identified as stable genotypes. Based on the coefficient of environmental variation, genotypes G10, G1, G8, G23, G13, G2 and G5 had the lowest coefficient of variation. Based on Plasted and Peterson method, genotypes G10, G20, G19 and G9 were selected as stable genotypes with high yield. In the Plaisted method, genotypes G10, G20, G19 and G9 with the least contribution in creating interaction and having the desired yield were introduced as stable and high yielding genotypes. Based on Lin and Bains, genotypes G15, G6, G21, G19, G20, G7 and G9 had the least amount of this statistic and were introduced as the most stable genotypes. Based on Kang's total rank method, G20, G19, G10, G9 and G22 genotypes with the lowest total rank were selected as stable genotypes. Based on parameters of Nassar and Huhn, genotypes G8, G9, G10, G1, G20, G19 and G21 and based on parameters of Thenarasu, genotypes G8, G9, G10, G1, G19 and G22 with the lowest rank were selected as stable genotypes. Finally, based on the selection ideal index genotype, genotypes G10, G9, G19, G22 and G20 had the closest value to one and had a higher yield than the overall average; therefore, they were selected as the most stable genotypes.
Conclusion: Based on the selection ideal index genotype (SIIG index), genotypes G10, G9, G19, G22 and G20 had the closest value to one and also had yield above the average; therefore, they were selected as the most stable genotypes. Also, the use of SIIG index is recommended due to the high correlation with all the indices used to summarize the results of parametric and non-parametric stability indices.
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
