Additive Main Effect and Multiplicative Interaction Analysis of National Turfgrass Performance Trials: I. Interpretation of Genotype × Environment Interaction

Ebdon, J. S.; Gauch, Hugh G.

doi:10.2135/cropsci2002.4890

Cited by 117 publications

(95 citation statements)

References 19 publications

(37 reference statements)

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“…The definition of the environmental factor contributing to the observed G 9 E interactions empowers the breeder to focus the search for relevant genetic variation for resistance/ tolerance to the defined production constraint, rather than dealing with the amorphous search for specific or broad adaptation. In National Turfgrass trials in the USA, Ebdon and Gauch (2002) observed that leaf spot disease incidence explained a large proportion of observed G x E interactions for quality performance and resulted in narrow adaptation of tested genotypes. Byth et al (1976) attributed a number of strong G 9 E interactions for yield in wheat to the incidence of foliar diseases and the presence of genetic variation for resistance to the disease.…”

Section: Discussionmentioning

confidence: 99%

Genotype × environment interaction for yield and reaction to leaf spot infections in groundnut in semiarid West Africa

Padi¹

2008

Euphytica

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Capitalizing on the yield potential in available groundnut germplasm, and high stability of kernel yield are important requirements for groundnut producers in semiarid environments. Forty-seven groundnut genotypes were evaluated from 2003 to 2005 at 4 locations representative of the Guinea and Sudan savanna ecologies in Ghana. The objectives were to assess genotypic differences in reaction to early and late leaf spot infections under natural field conditions, assess the extent of genotype 9 environment (G 9 E) interaction for kernel yield, and determine the relationship between yield potential and yield stability. Genotypes differed significantly in their reaction to leaf spot infections indicated by the area under disease progress curve (AUDPC). Genotypic AUDPC was negatively correlated with maturity period (P \ 0.01), with kernel yield (P \ 0.05) at each of the 3 locations in the Guinea savanna ecology but not in the Sudan savanna ecology and with each of four stability parameters (P \ 0.05). High or low yielding genotypes were grouped based on Dunnett's test at P \ 0.10. High yielding groups had significantly low AUDPC, high biomass, high partitioning of dry matter for kernel growth, and were later in maturity compared to low yielding genotypes. Significant G 9 E interaction effect for kernel yield was dominated mainly by the lack of correlation among environments variance (76-78%) relative to the heterogeneity of genotypic variance component (22-24%). Stability of yield assessed through the among-environment variance, Wricke's ecovalence, and Finlay-Wilkinson regression coefficient revealed that genotypes in the higher yielding group were relatively unstable compared to the low yielding group. Indicated by the Kataoka's index of yield reliability, however, relatively unstable genotypes in the high yielding group are expected to be more productive even under assumptions of high risk aversion (P = 0.75-0.95) compared to the more stable, low yielding genotypes. The findings indicate that deploying these recently developed germplasm in semiarid regions in West Africa provides a better match to farmers' risk-averse strategies compared with the use of existing earlier maturing cultivars.

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Section: Discussionmentioning

confidence: 99%

Genotype × environment interaction for yield and reaction to leaf spot infections in groundnut in semiarid West Africa

Padi¹

2008

Euphytica

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“…The biplot graph, which clearly displays complex yield patterns (Gauch 1992;Krualee et al 2012), can capture 90% of treatment variation (Krualee et al 2012). Although AMMI model analysis results are based simply on yield statistics (not environmental data), Ebdon and Gauch (2002) have reported that AMMI environmental statistics correlate with environmental factors. An ideal plant variety exhibits both high yields and stability of performance (Eberhart & Russell 1966) over a wide range of environments (Allard & Bradshaw 1964).…”

Section: Ammi Analysismentioning

confidence: 99%

Genetic stability analysis of introducedBetula pendula, Betula kirghisorum, andBetula pubescensfamilies in saline-alkali soil of northeastern China

Zhao

Bian

et al. 2014

Scandinavian Journal of Forest Research

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Approximately, 20% of arable land worldwide, as well as nearly half of irrigated land, is subjected to salt stress. Osmotic stress and ion toxicity due to saline soils cause low crop yields. In this study, we introduced 18 families of salt-tolerant birch (Betula pendula Roth., Betula kirghisorum Sav.-Ryczg., and Betula pubescens Ehrh) into five high-salinity locations in northeastern China and evaluated their survival abilities. We also analyzed variation and stability of genotypeenvironment interactions of the different families under an additive main effect and multiplicative interaction model. Survival rate analysis indicated that the introduced families were well adapted to the high-salinity environments, whereas native families died. Variation analysis revealed significant differences between location × family interaction mean values for height and basic stem diameter (BSD), suggesting that most genotypes responded differently to different sites. The heritability of tree height and BSD at different sites varied from 0.416 to 0.940, with the coefficient of phenotypic variation ranging from 9.88% to 35.53%. Stability analysis indicated that some families had high tree heights but were sensitive to environmental conditions, whereas others were resistant but had average tree heights. These results suggest that families should be bred in various habitats to assess growth under favorable and unfavorable environments.

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“…In particular, great differences in nodule dry matter among genotypes were associated with differences in seed nitrogen concentration. Furthermore, the targeting of genotypes to specific environments is difficult when GE (genotype × environment) interaction is present since their expression is less predictable and cannot be interpreted based only on G and E means (Ebdon and Gauch 2002;González et al 2006). Crop-breeding programs should also take GE interaction into consideration and estimate its magnitude relative to the magnitude of G and E effects, which affect specific traits.…”

Section: Introductionmentioning

confidence: 99%

Variation for nodulation and plant yield of common bean genotypes and environmental effects on the genotype expression

Rodiño¹,

Fuente²,

Ron³

et al. 2011

Plant Soil

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Common bean symbiotic nitrogen fixation provides an ecological and economical alternative to increase bean production but it depends on soil fertility and climate conditions. The objectives of this work were to characterize common bean genotypes for their ability to establish symbiosis under controlled conditions and to study the effect of the environment on the expression of those genotypes. The experiment under controlled conditions was conducted in a greenhouse with 158 genotypes that represented the major dry bean market classes. The field experiment was carried out in six environments with 64 genotypes that were previously selected for their contrasting nodulation ability and/or root development under the controlled conditions experiment. Nodulation, plant, and grain yield data of the bean genotypes were measured in both experiments. There was a significant high variability in plant development responses among the studied genotypes associated with the rhizobial strain inoculated under controlled conditions. Two nodulation phenotypes were observed among the genotypes tested: the big-nodules phenotype (BNO) associated with almost 63% fewer nodules and 58% higher proportion of nodule biomass in the below-ground compartment than the smallnodules phenotype (SNO) with less developed aerial parts. Genotype plus genotype × environment (GGE) biplot model analysis enabled identification of the highest-yielding genotypes for the different environments. The soil chemical factors of these environments were associated with the nodule number or the biomass of the common bean genotypes. Genotypes with a BNO phenotype showed a good plant response, indicating that this phenotype may be more beneficial for plant growth and seed yield in environmental conditions that may limit nodule development. The amplitude of the genotypic variability found in this work confirms the potential for rhizobial symbiosis of adapted bean genotypes, which could constitute a preferential material for initial breeding of symbiotically active lines. The data also indicate the potential of bean breeding to identify environments containing effective strains of rhizobia essential for sustainable agriculture, improving productivity, and maintaining environmental quality.

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Additive Main Effect and Multiplicative Interaction Analysis of National Turfgrass Performance Trials: I. Interpretation of Genotype × Environment Interaction

Cited by 117 publications

References 19 publications

Genotype × environment interaction for yield and reaction to leaf spot infections in groundnut in semiarid West Africa

Genotype × environment interaction for yield and reaction to leaf spot infections in groundnut in semiarid West Africa

Genetic stability analysis of introducedBetula pendula, Betula kirghisorum, andBetula pubescensfamilies in saline-alkali soil of northeastern China

Variation for nodulation and plant yield of common bean genotypes and environmental effects on the genotype expression

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