Volume 15, Issue 46 (7-2023)
J Crop Breed 2023, 15(46): 73-83 |
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pezeshkpour P, Karimizadeh R. (2023). Evaluation of the Mean Performance and Stability of Chickpea Genotypes by Integration AMMI and BLUP Models and Selection Based on Multi-Trait Stability Index (MTSI). J Crop Breed. 15(46), 73-83. doi:10.61186/jcb.15.46.73
URL: http://jcb.sanru.ac.ir/article-1-1423-en.html
URL: http://jcb.sanru.ac.ir/article-1-1423-en.html
1- Education and Extension Organization (AREEO), Dryland Agricultural Research Institute, lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khoramabad, Iran
2- Agricultural Research, Education and Extension Organization (AREEO), Dryland Agricultural Research Institute, Kohgiloyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gachsaran, Iran
2- Agricultural Research, Education and Extension Organization (AREEO), Dryland Agricultural Research Institute, Kohgiloyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gachsaran, Iran
Abstract: (1850 Views)
Extended Abstract
Introduction and objective: Chickpea is one of the legumes due to its protein percentage and high nutritional value, and it can be cultivated in the fall in rainy conditions. Identification of high-yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. Combining features of the best linear unbiased predictions (BLUP) and additive main effects and multiplicative interaction (AMMI) in multi- environment experiments and multi-trait stability selection (MTSI) to better evaluate plant genotypes and achieve more accurate results It helps to be more precise. Additive main effect and multiplicative interaction (AMMI) and best linear unbiased prediction (BLUP) are two methods for analyzing multi-environment trials (MET). This research was done to identify stable and high-yielding chickpea genotypes in autumn planting.
Material and Methods: In this study, seventeen advanced chickpea Genotypes were evaluated along with two check varieties (Adel and Azad) based on randomized complete block design with three replications at Sarab Changai agricultural and natural resources research station khoramabad lorestan for four crop years (2013-2017) were evaluated. To quantify the genotypic stability, the best linear unbiased predictions of the genotype by environment interactions (GEI) were estimated, and singular value decomposition (SVD), which is the basis of AMMI analysis, was performed on the resulting matrix.
Results: The heat map plot indicated the variation of seed yield of genotype and sum squares of genotype by environment interaction in total sum of squares were 15.45 % and 31.26 % respectively. The likelihood ratio test (LRT) showed that the effect of GEI was significant on grain yield, 100 grain weight, plant height, grain – filling rate and grain– filling period. Therefore, due to the significant interaction of genotype by environment, BLUP analysis can be performed on this data. The screet test showed that the first four principal components had a significant Contribution in the GEI matrix derived from BLUP, as the first and second principal components explained only 34.31% and 31.38% of the GEI variation respectively. Based on the multi- trait stability index (MTSI), G7 was also selected as the best genotype in terms of grain yield, evaluated traits and stability of each trait.
Conclusion: In general, based on the results of all methods and simultaneous selection based on seed yield stability and all measured traits (MTSI), genotypes No. 7 (FLIP07-201C), and 4 (FLIP06-43C) were stable and superior genotypes, They were compared to the average of the total traits of the genotypes. Genotype No. 4 in terms of seed filling period (32 days), seed yield (2536.9 kg/ha), hundred seed weight (34.3 gr.), plant height (65.3 cm) and Genotype No. 7, with The average seed filling ratio (10.63 mg per seed per day) and seed yield (2250 kg/ha) were more than the average of the total traits of genotypes and controls (Azad and Adel) in this research
Introduction and objective: Chickpea is one of the legumes due to its protein percentage and high nutritional value, and it can be cultivated in the fall in rainy conditions. Identification of high-yield genotypes with adaptation to a wide range of environments is one of the major goals in crop breeding programs. Combining features of the best linear unbiased predictions (BLUP) and additive main effects and multiplicative interaction (AMMI) in multi- environment experiments and multi-trait stability selection (MTSI) to better evaluate plant genotypes and achieve more accurate results It helps to be more precise. Additive main effect and multiplicative interaction (AMMI) and best linear unbiased prediction (BLUP) are two methods for analyzing multi-environment trials (MET). This research was done to identify stable and high-yielding chickpea genotypes in autumn planting.
Material and Methods: In this study, seventeen advanced chickpea Genotypes were evaluated along with two check varieties (Adel and Azad) based on randomized complete block design with three replications at Sarab Changai agricultural and natural resources research station khoramabad lorestan for four crop years (2013-2017) were evaluated. To quantify the genotypic stability, the best linear unbiased predictions of the genotype by environment interactions (GEI) were estimated, and singular value decomposition (SVD), which is the basis of AMMI analysis, was performed on the resulting matrix.
Results: The heat map plot indicated the variation of seed yield of genotype and sum squares of genotype by environment interaction in total sum of squares were 15.45 % and 31.26 % respectively. The likelihood ratio test (LRT) showed that the effect of GEI was significant on grain yield, 100 grain weight, plant height, grain – filling rate and grain– filling period. Therefore, due to the significant interaction of genotype by environment, BLUP analysis can be performed on this data. The screet test showed that the first four principal components had a significant Contribution in the GEI matrix derived from BLUP, as the first and second principal components explained only 34.31% and 31.38% of the GEI variation respectively. Based on the multi- trait stability index (MTSI), G7 was also selected as the best genotype in terms of grain yield, evaluated traits and stability of each trait.
Conclusion: In general, based on the results of all methods and simultaneous selection based on seed yield stability and all measured traits (MTSI), genotypes No. 7 (FLIP07-201C), and 4 (FLIP06-43C) were stable and superior genotypes, They were compared to the average of the total traits of the genotypes. Genotype No. 4 in terms of seed filling period (32 days), seed yield (2536.9 kg/ha), hundred seed weight (34.3 gr.), plant height (65.3 cm) and Genotype No. 7, with The average seed filling ratio (10.63 mg per seed per day) and seed yield (2250 kg/ha) were more than the average of the total traits of genotypes and controls (Azad and Adel) in this research
Keywords: Mosaic plot, Multi- trait stability index(MTSI), Simultaneous selection, Single Value Decomposition (SVD).
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