AMMI analysis nested with BLUP for stability analysis of barley genotypes evaluated at Northern Hills Zone of the country
DOI:
https://doi.org/10.5958/2582-2683.2022.00052.1Keywords:
AMMI, MASV, ASTAB, WAASB, SSIAbstract
Highly significant effects of environments (E), GxE interaction and genotypes (G) had expressed by AMMI analysis for problem soils under coordinated barley improvement program of the country. Interaction effects GxE accounted for 52.4% & 30.5% and environment effects explained 19.4% & 50.3% during cropping seasons of 2018-19 and 2019-20 respectively. Stability measure WAASB based on all significant interaction principal components ranked suitability of UPB1077, BHS400, HBL851 genotypes. Superiority index while weighting 0.65 and 0.35 for mean yield & stability ranked VLB162, BHS400, HBL113 as of stable performance with high yield barley genotypes. ASTAB measure achieved the desirable lower values for BHS474, HBL113, VLB 162. Composite measure MASV1 found BHS474, HBL113, VLB162 and as per MASV ranks BHS474, HBL113, HBL863 genotypes would be of choice for these locations of the zone. Biplot graphical analysis as per 66.3% of variation of the stability measures exhibited MASV1 clubbed with ASTAB, EV, SIPC, Za, W3, WAASB and MASV measures. Yield based measures clubbed with corresponding SI measures. For the second-year lower value of WAASB measure had observed for BHS481, BHS400, BHS352 whereas large value by HBL867. Ranking of genotypes as per Superiority index found BHS482, HBL113, VLB168 as of stable performance with high yield. Barley genotypes HBL113, VLB168, VLB166 were selected as per values of ASTAB measure accounted the AMMI analysis with BLUP of genotypes yield values. Composite measure MASV1 selected HBL113, VLB168, HBL867 while HBL113, VLB168, HBL867 identified by MASV as genotypes of choice for these locations of the zone. 73.1% of variation of the stability measures in biplot analysis observed MASV1 clubbed with ASTAB, EV, SIPC, Za, W3, WAASB and MASV measures. Average yield measures clubbed with corresponding SI measures.
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Agahi K, Ahmadi J, Oghan H A, Fotokian M H, Orang S F (2020). Analysis of genotype × environment interaction for seed yield in spring oilseed rape using the AMMI model. Crop Breeding and Applied Biotechnology 20(1): e26502012
Ajay BC, Bera SK, Singh AL, Kumar N, Gangadhar K, Kona P (2020). Evaluation of Genotype × Environment Interaction and Yield Stability Analysis in Peanut Under Phosphorus Stress Condition Using Stability Parameters of AMMI Model. Agric Res 9: 477-486
Bocianowski J, Niemann J, Nowosad K (2019). Genotype-by environment interaction for seed quality traits in interspecific cross-derived Brassica lines using additive main effects and multiplicative interaction model. Euphytica 215(7):1–13
Farshadfar E (2008). Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pak J Biol Sci 11:1791–1796
Farshadfar E, Mahmodi N and Yaghotipoor A (2011). AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum L.). Aust J Crop Sci 5:1837–1844
Gauch HG (2013). A simple protocol for AMMI analysis of yield trials. Crop Sci 53:1860–1869
Kang MS (1993). Simultaneous selection for yield and stability in crop performance trials: Consequences for growers. Agronomy Journal 85:754-757
Karkee A, Ghimire K H and Joshi, B K. 2020. Evaluation on naked barley landraces foragro-morphological traits. Journal of Nepal Agricultural Research Council. 6:34-43.
Kendel M, Dhami N B and Shrestha J. 2019. Performance evaluation of barley (Hordeum vulgare L.) genotypes in Dolakha, Nepal: from yielding perspective. Journal of Agriculture and Natural Resources 2(1):322-337.
Olivoto T, Lucio A Dal’Col, Gonzalez, Silva JA da, Marchioro VS (2019). Mean performance and stability in multi environment trials I: Combining features of AMMI and BLUP techniques. Agron J 111:1–12
Oyekunle M, Menkir A, Mani H, Olaoye G, Usman IS, Ado S (2017). Stability analysis of maize cultivars adapted to tropical environments using AMMI analysis. Cereal Res Commun 45:336–345
Piepho HP, Mo¨hring J, Melchinger AE, Bu¨chse A (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161(1):209–228
Rao AR and Prabhakaran VT (2005). Use of AMMI in simultaneous selection of genotypes for yield and stability. Journal of the Indian Society of Agricultural Statistics 59:76-82
Resende MDV, Duarte JB (2007). Precision and Quality Control in Variety Trials. PesquisaAgropecuaria Tropical 37: 182- 194
Shimizu C, KiharaM, Aoe S, Araki A, Ito K, Hayashi K, Watari J, Sakata Y and Ikegami S. 2008. Effect of high ß-glucan barley on serum cholesterol concentrations and visceral fat area in Japanese men- A randomized, double-blinded, placebo-controlled trial. Plant Food Human Nutrition 63:21-25
Zali H, Farshadfar E, Sabaghpour SH, Karimizadeh R (2012). Evaluation of genotype × environment interaction in chickpea using measures of stability from AMMI model. Ann Biol Res 3:3126–3136
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