Analysis of Genotype × Environment Interaction for Seed Yield in Winter Rapeseed Cultivars and Lines Using Multivariate Method of Additive Main Effects and Multiplicative Interaction

2021 ◽  
Vol 11 (1) ◽  
Keyword(s):  
Seed Yield ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Multivariate Method ◽  
Genotype Environment Interaction ◽  
Winter Rapeseed ◽  
Main Effects

An analysis of variability and genotype × environment interaction in mung bean (Vigna radiata) in south-eastern Queensland

1982 ◽  
Vol 33 (3) ◽  
pp. 523 ◽  
Author(s):  
BC Imrie ◽  
KL Butler
Keyword(s):  
Plant Height ◽  
Seed Yield ◽  
Vigna Radiata ◽  
Mung Bean ◽  
Rainfall Variability ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Sowing Dates ◽  
Photoperiod Sensitive ◽  
Main Effects

Thirty mung bean (Vigna radiata) accessions were grown in replicated hill plots at two sites in each of 2 years. Plant height, days to flower and to harvest, and seed yield were recorded for each plot. In an analysis of variance most main effects and interactions were statistically significant. Estimated variance due to environment exceeded that due to genotypes for all characters. Broad sense heritability of seed yield was 0.07. The linear regression of seed yield on plant height was statistically significant, and there was a significant quadratic effect of yield on days to flower. It was concluded that environmental effects on the duration of growth phases were likely to be mainly due to the effect of different sowing dates on photoperiod-sensitive accessions, while rainfall variability most likely contributed to yield variance. Emphasis in an evaluation program should be on sampling years rather than locations.

scholarly journals Stability Analysis for Seed Yield over Environments in Coriander

2016 ◽  
Vol 4 (11) ◽  
pp. 1014
Author(s):  
Sangeeta Yadav ◽  
Arun Kumar Barholia
Keyword(s):  
Stability Analysis ◽  
Seed Yield ◽  
High Fertility ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Back Ground ◽  
Ammi Model ◽  
Main Effects

Thirty five genotypes of coriander (Coriandrum sativum L.) were tested in four artificially created environments to judge their stability in performance of seed yield. The differences among genotypes and environments were significant for seed yield. Stability parameters varied considerably among the tested genotypes in all the methods used. The variation in result in different methods was due to non-fulfillment of assumption of different models. However, AMMI analysis provides the information on main effects as well as interaction effects and depiction of PCA score gives better understanding of the pattern of genotype – environment interaction. The sum of squares due to PCAs was also used for the computation of AMMI stability values for better understanding of the adaptability behavior of genotypes hence, additive main effects and multiplicative interaction (AMMI) model was most appropriate for the analysis of G x E interactions for seed yield in coriander. Genotypes RVC 15, RVC 19, RVC 22, RVC 25 and Panipat local showed wider adaptability while, Simpo S 33 exhibited specific adaptability to favourable conditions of high fertility. These genotypes could be utilized in breeding programmers to transfer the adaptability genes into high yielding genetic back ground of coriander.

scholarly journals Genotype-by-environment interaction for seed glucosinolate content in winter oilseed rape (Brassica napus L.) using an additive main effects and multiplicative interaction model

2018 ◽  
Vol 55 (1) ◽  
pp. 85-96 ◽  
Author(s):  
Jan Bocianowski ◽  
Kamila Nowosad ◽  
Alina Liersch ◽  
Wiesława Popławska ◽  
Agnieszka Łącka
Keyword(s):  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Glucosinolate Content ◽  
Environment Interaction ◽  
Brassica Napus L ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Winter Rapeseed ◽  
Main Effects

Summary The objective of this study was to assess genotype-by-environment interaction for seed glucosinolate content in winter rapeseed cultivars grown in western Poland using the additive main effects and multiplicative interaction model. The study concerned 25 winter rapeseed genotypes (15 F1 CMS ogura hybrids, parental lines and two European cultivars: open pollinated Californium and F1 hybrid Hercules), evaluated at five locations in a randomized complete block design with four replicates. The seed glucosinolate content of the tested genotypes ranged from 5.53 to 16.80 μmol∙g-1 of seeds, with an average of 10.26 μmol∙g-1. In the AMMI analyses, 48.67% of the seed glucosinolate content variation was explained by environment, 13.07% by differences between genotypes, and 17.56% by genotype-by-environment interaction. The hybrid PN66×PN07 is recommended for further inclusion in the breeding program due to its low average seed glucosinolate content; the restorer line PN18, CMS ogura line PN66 and hybrids PN66×PN18 and PN66×PN21 are recommended because of their stability and low seed glucosinolate content.

scholarly journals Seed vigor level in association to fertilizer distribution

2020 ◽  
Vol 9 (10) ◽  
pp. e5999108658
Author(s):  
Simone Morgan Dellagostin ◽  
Vinícius Jardel Szareski ◽  
Gustavo Henrique Demari ◽  
Ivan Ricardo Carvalho ◽  
Michele Renata Revers Meneguzzo ◽  
...  
Keyword(s):  
Grain Yield ◽  
Seed Yield ◽  
Distribution System ◽  
Distribution Systems ◽  
Seed Vigor ◽  
Soybean Seeds ◽  
Environment Interaction ◽  
Absolute Increase ◽  
Genotype Environment Interaction ◽  
Main Effects

This work aimed at evaluating yielding responses of soybean seeds production fields in response to the association between seed vigor level and fertilizer distribution systems at the sowing line.Experimental design was randomized blocks design, with two growing environments (Passo Fundo - RS and Ernestina - RS) x three vigor levels (high = 90%, medium = 70% and low = 60%) x three fertilizer distribution systems (absence, conventional and by transhipment), arranged in four replicates, grain yield (GY). For grain yield (GY), it was applied the method genotype main effects and genotype environment interaction (GGE). Seed vigor levels and fertilizer distribution systems influence on seed yield, first pod insertion height, plant height, number of pods in the main stem and ramifications, magnitude and length of ramifications in soybean.The high vigor level in the conventional and by transshipment fertilization systems provided an absolute increase of 10.9 and 5.6% in seed yield, respectively, in Ernestina-RS. The conventional fertilizer distribution system, in Passo Fundo-RS, increased seed yield in 12.5% in plants originated from low vigor seeds.

scholarly journals Análises Biplot: conceitos, interpretações e aplicações

2012 ◽  
Vol 42 (8) ◽  
pp. 1404-1412 ◽  
Author(s):  
Raphael Rossi Silva ◽  
Giovani Benin
Keyword(s):  
Environment Interaction ◽  
Gge Biplot ◽  
Multiplicative Interaction ◽  
Genotype Environment Interaction ◽  
Main Effects

A seleção e recomendação de genótipos superiores são dificultadas devido à ocorrência da interação genótipo e ambiente. Nesse contexto, as análises biplot têm sido cada vez mais utilizadas na análise de dados agronômicos, com interações de natureza complexa. Entretanto, as particularidades existentes no gráfico biplot dificultam sua interpretação, podendo induzir o pesquisador a erros. Assim, este artigo de revisão discute a aplicabilidade e a interpretação gráfica dos modelos AMMI (Additive Main effects and Multiplicative Interaction) e GGE biplot (genotype main effects + genotype environment interaction) destas análises no gráfico biplot. Também, visa a desmistificar a necessidade de comparação entre ambas as metodologias. Discute-se quanto à escolha da metodologia mais adequada, levando em consideração a informação requerida e os objetivos do pesquisador.

Genotype-environment interaction and stability analysis in hybrid rice: an application of additive main effects and multiplicative interaction

2013 ◽  
Vol 42 (1) ◽  
pp. 73-82 ◽  
Author(s):  
M Umma Kulsum ◽  
M Jamil Hasan ◽  
Anowara Akter ◽  
Hafizar Rahman ◽  
Priyalal Biswas
Keyword(s):  
Grain Yield ◽  
Hybrid Rice ◽  
Amylose Content ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Hybrid Combination ◽  
Stability Performance ◽  
Genotype Environment Interaction ◽  
Wide Range ◽  
Main Effects

Genotype-environment interaction and stability performance were investigated on amylase, protein and grain yield with 13 hybrid rice promising combinations in five environments. The combined ANOVA showed that the mean sum of square due to genotype (G), environment (E) and G × E interaction were significant for amylose content, protein content and grain yield. This suggests a number of variabilities among the genotypes and environments as and the indicated genotypes interacted significantly with environments. The Additive Main Effects and Multiplicative Interaction (AMMI) biplot for yield clearly indicated that the hybrids BR10A/BR12R, II32A/BR15R, II32A/BR16R, II32A/BR10R, BR9A/BR15R, BRRI hybrid dhan2 and BRRI hybrid dhan3 were high yielding, stable and had general adaptability at all locations. The AMMI estimation had a profound effect in producing sharp and stratified ranking patterns and on this basis BRRI hybrid dhan2 would be considered more adapted to a wide range of environments than the rest of the genotypes. The biplot technique was used to identify appropriate genotype to special locations. This consideration on the basis of average yield for specific genotype to the specific location. The hybrid combination II32A/BR12R was more suitable for Gazipur location and the hybrid combination BR10A/BR13R was considered for Comilla region. Barisal was more stable site than other location for grain yield due to IPCA score near zero which had no interaction effect. DOI: http://dx.doi.org/10.3329/bjb.v42i1.15867 Bangladesh J. Bot. 42(1): 73-81, 2013 (June)

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