scholarly journals Genetic Variability and G×E Interactions in a Diverse Set of Groundnut Accessions

2022 ◽  
Author(s):  
K. Gangadhara ◽  
H.K. Gor
Keyword(s):  
Cluster Analysis ◽  
Euclidean Distance ◽  
Agronomic Traits ◽  
Environment Interaction ◽  
Pod Yield ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Days To Maturity ◽  
Component Traits

Background: Knowledge of the genetic diversity for various agronomic traits and their interaction with the environment and subsequent classification of genotypes will be beneficial for identification of divergent and stable sources of agronomic traits. Methods: A set of 96 groundnut germplasm accessions belonging to four botanical groups were evaluated for three years (2017 to 2019) for pod yield and component traits using AMMI analysis and subsequently accessions were classified based Euclidean cluster analysis. Result: Among different botanical groups, Virginia genotypes matured late and possessed high SPAD chlorophyll meter readings (SCMR) and pod yield compared to Spanish types. The component traits of pod maturity like days to flowering (first and 50%) showed low heritability and high genotype × environment interaction (GEI) and significant negatively affected sound mature kernel (SMK) and shelling per centage (SP). The cumulative contribution of environment and GEI component to the total variance was the highest in the expression of SP (67%) followed by days to maturity (54%) and days to 50% flowering (52%). Euclidean distance-based cluster analysis grouped the 96 accessions into five major clusters. Cluster I had accessions with higher pod yield, whereas cluster V contained accessions with low SLA, high SCMR and moderate pod yield. High yielding as well as stable accessions identified based on AMMI stability value (ASV) are NRCG 17332, 10076, 17268, 17197, 17108, 10106, 10089 and 17165. Trait specific as well as stable accessions identified in the present study can be useful donors for groundnut breeding programme.

scholarly journals Influence of genotype-environment interaction on the classification of Nellore bulls in Southern Brazil

2015 ◽  
Vol 37 (2) ◽  
pp. 195 ◽  
Author(s):  
Tiago Bresolin ◽  
Dionéia Magda Everling ◽  
Paulo Roberto Nogara Rorato ◽  
Camila Urbano Braz ◽  
Fernanda Cristina Breda
Keyword(s):  
Environment Interaction ◽  
Southern Brazil ◽  
Genotype Environment Interaction

scholarly journals Properties of spontaneous mutations affecting quantitative traits

1999 ◽  
Vol 74 (3) ◽  
pp. 341-350 ◽  
Author(s):  
A. GARCÍA-DORADO ◽  
C. LÓPEZ-FANJUL ◽  
A. CABALLERO
Keyword(s):  
Deleterious Mutation ◽  
Natural Populations ◽  
Detectable Effect ◽  
Environment Interaction ◽  
Fitness Component ◽  
Standing Variation ◽  
Genotype Environment Interaction ◽  
Component Traits ◽  
Mutational Variance ◽  
New Mutations

Recent mutation accumulation results from invertebrate species suggest that mild deleterious mutation is far less frequent than previously thought, implying smaller expressed mutational loads. Although the rate (λ) and effect (s) of very slight deleterious mutation remain unknown, most mutational fitness decline would come from moderately deleterious mutation (s ≈ 0·2, λ ≈ 0·03), and this situation would not qualitatively change in harsh environments. Estimates of the average coefficient of dominance (h¯) of non-severe deleterious mutations are controversial. The typical value of h¯ = 0·4 can be questioned, and a lower estimate (about 0·1) is suggested. Estimated mutational parameters are remarkably alike for morphological and fitness component traits (excluding lethals), indicating low mutation rates and moderate mutational effects, with a distribution generally showing strong negative asymmetry and little leptokurtosis. New mutations showed considerable genotype–environment interaction. However, the mutational variance of fitness-component traits due to non-severe detrimental mutations did not increase with environmental harshness. For morphological traits, a class of predominantly additive mutations with no detectable effect on fitness and relatively small effect on the trait was identified. This should be close to that responsible for standing variation in natural populations.

Genotype × environment interaction and AMMI analysis for heat tolerance in wheat

2012 ◽  
Vol 40 (2) ◽  
pp. 267-276 ◽  
Author(s):  
S. Sareen ◽  
R. Munjal ◽  
N. Singh ◽  
B. Singh ◽  
R. Verma ◽  
...  
Keyword(s):  
Heat Tolerance ◽  
Environment Interaction ◽  
Genotype Environment Interaction ◽  
Ammi Analysis

scholarly journals Investigation of genotype-environment interaction by cluster analysis in animal experiments

1994 ◽  
Vol 74 (4) ◽  
pp. 607-612 ◽  
Author(s):  
C. Y. Lin ◽  
C. S. Lin
Keyword(s):  
Cluster Analysis ◽  
Key Words ◽  
Animal Experiment ◽  
Animal Experiments ◽  
Environment Interaction ◽  
Mean Square ◽  
Ge Interaction ◽  
Interaction Structure ◽  
Genotype Environment Interaction ◽  
Animal Data

The conventional ANOVA (F ratio of GE interaction mean squares to error mean square) provides a means to test if GE interaction is significant, but it does not tell us which factor levels are significantly different or how they are interacting. To answer the latter question, plant researchers developed a technique to group genotypes for similarity of GE interactions and through the resulting groups to explore the GE interaction structure. The basic idea of the technique is to stratify genotypes (or environments) into subgroups such that GE interactions among genotypes (or environments) are homogeneous within groups but heterogeneous among groups. This technique is introduced in this paper using an animal experiment as an example for illustration. The possibilities and limitations of applying this technique to animal data are also discussed. Key words: Genotype-environment interaction, cluster analysis

Inheritance of resistance to Mal de Río Cuarto (MRC) disease in Zea mays (L.)

2002 ◽  
Vol 139 (1) ◽  
pp. 47-53 ◽  
Author(s):  
M. A. DI RENZO ◽  
N. C. BONAMICO ◽  
D. D. DÍAZ ◽  
J. C. SALERNO ◽  
M. M. IBAÑEZ ◽  
...  
Keyword(s):  
Zea Mays ◽  
Plant Height ◽  
Disease Severity ◽  
Agronomic Traits ◽  
Severity Index ◽  
Point Estimate ◽  
Environment Interaction ◽  
Disease Severity Index ◽  
Evaluation Activity ◽  
Genotype Environment Interaction

No genetic estimates for resistance to Mal de Río Cuarto (MRC) disease in Zea mays (L.) are currently available in the literature. Therefore, the objectives of this investigation were (i) to estimate the variance and heritability of partial resistance to MRC disease and of other agronomic traits from maize families and (ii) to examine associations among MRC disease severity values across different environments and between MRC and other agronomic traits. These estimations, obtained in an endemic area, could contribute to the design of efficient enhancement programmes and evaluation activity for the improvement of MRC resistance. The research was conducted by testing 227 F3 derived-lines from a cross between a susceptible dent line, Mo17, and a partially resistant flint line, BLS14, for MRC disease at two Río Cuarto locations in each of 2 years. The resistance of the lines, measured with a disease severity index (DSI), was normally distributed across environments. Genotypic variances were highly significant on all scoring environments. Estimates of genotype–environment interaction were also significant, suggesting that certain genotypes have little stability over different environments. For disease severity index all estimates demonstrated moderate heritabilities ranging from 0.44 to 0.56 and were similar when based on individual environments or across environment. Confidence interval widths ranged from 34.88 to 50.30% as large as the heritability point estimate. The correlations between environments were small enough to indicate that families did not rank similarly in individual environments for MRC resistance. Disease severity index correlated significantly (P<0.01) with plant height, leaf surface, leaf border, leaf length and tassel type. Heritability estimates for plant height and tassel type were 0.48 and 0.38 respectively and for the various leaf traits heritability values were very low. On the basis of the substantial genotype–environment interaction and the little association between DSI values in the different environments, selection for an increased resistance to MRC disease would require evaluation of germplasm across multiple years and locations. Tassel type would be a useful predictor of DSI and can be used effectively to improve screening procedures.

scholarly journals Genotype environment interaction and stability for yield and its components in advanced breeding lines of red rice (Oryza sativa L.)

2020 ◽  
Vol 49 (3) ◽  
pp. 425-435
Author(s):  
BM Dushyantha Kumar ◽  
AP Purushottam ◽  
P Raghavendra ◽  
T Vittal ◽  
KN Shubha ◽  
...  
Keyword(s):  
Grain Yield ◽  
Oryza Sativa L ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Red Rice ◽  
Yield Performance ◽  
Breeding Lines ◽  
Genotype Environment Interaction ◽  
Ammi Analysis ◽  
Total Variability

Effects of genotype, environment and their interaction for grain yield and yield attributing characters in 20 advanced breeding lines of rice across six environments was investigated. Yield stability and adaptability of yield performance were analyzed by Eberhart and Russel model and (GGE) bi-plot. The AMMI analysis of variance indicated that mean squares due to genotypes, location and genotype location contributed per cent 59.08, 5.79 and 21.63, respectively for total variability in grain yield per hectare. Estimates of GGE bi-plot revealed that the lines G1, G3, G11, G13, G15, G12, G16, G7 and G10 were positioned near GGL bi-plot origin indicating wider adaptation for the trait grain yield per hectare. Eberhart and Russel Model and GGE biplot model showed the advanced breeding lines viz., JB 1-11-7 (G1) and JA 6-2 (G15) exhibited wider adaptability across the tested environments for number of productive tillers per plant and yield per hectare.

scholarly journals Analysis of yield stability of strawberry varieties and hybrids

2020 ◽  
Vol 25 ◽  
pp. 02014
Author(s):  
Vadim Lapshin ◽  
Valentina Yakovenko ◽  
Sergey Shcheglov
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster ◽  
Yield Stability ◽  
Environment Interaction ◽  
Multivariate Statistical ◽  
Genotype Environment Interaction ◽  
Yield Structure ◽  
Biological Yield ◽  
Factor Of Influence

The profitability of strawberry cultivation is largely determined by the capacity and quality of the yield, depended on the features of the variety genotype. The aim of this work was to estimate the yield stability of varieties and hybrids by the methods of multivariate statistical analysis and identify the best genotypes. To solve this problem, we have used the two-factor analysis of variance and hierarchical cluster analysis according to the Ward’s method as well as the integral estimate of the differences between the values of yield. The results of the studies have shown that the genotype of the variety (hybrid) are makes a decisive factor of influence for variability of the yield structure signs from 17,1% (number of inflorescences) to 32,2% (number of berries). The «genotype × environment» interaction is comparable with the genotype influence, the share of influence of the year conditions of the year is insignificant. Cluster analysis according to complex of economic valuable signs allows us to identify the eight forms that the most adapted to the conditions of the Krasnodar Territory as 13-1-15, Florence, Roxana, 18-1-15, Asia, Onda, Kemia, Nelli from which the Roxana, Florence, 18-1-15, 13-1-15 have a high and steadily rising biological yield.

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