scholarly journals Genotype x environment interaction analysis in Wheat (Triticum aestivum L.)

2020 ◽  
Vol 5 (01) ◽  
pp. 128-132
Author(s):  
Dipendra Rawal ◽  
Amit Tomar ◽  
Mahak Singh

The results of genotype x environment interaction analysis revealed highly significant mean squares due to genotypes as well as environments for all the characters which indicated presence of substantial differences among the genotypes as well as environments for all the eleven characters. The environment linear (E-L) component was also significant for all the characters indicating that the six environments can be graded linearly for their differences in influencing the expression of characters of wheat genotypes. The mean squares due to genotype x environment interaction were also highly significant for all the characters except days to heading, plant height, effective tillers per plant and total number of tillers per plant to suggest important role of g x e interaction in expression of most of the characters in wheat. The linear component of g x e interaction was significant for all the characters which indicated good possibility of predicting linear responses of genotypes for all the characters under study. Thus, there would be ample possibility of discriminating the genotypes for above average, below average and average linear responses to predict their performances in changing environments under study. The significance of non-linear component (pooled deviation) of g x e interactions for all characters except ear length suggested that considerable number of genotypes may exhibit unpredictable and unstable mean performance for different characters across environments even defying their prediction on the basis of linear sensitivity coefficient.

Author(s):  
S L Sawargaonkar ◽  
A K Singh ◽  
J Tiwari ◽  
K P Singh ◽  
A Sao ◽  
...  

The present study was conducted to find out the stability and yield performances of 13 genotypes of indigenous coriander (Coriandrum sativum L.) evaluated in different agro climatic zones of Chhattisgarh. The trials were laid out in a Randomized Block Design (RBD) with three replications at three locations for three years resulting in nine environments (Genotype × year interactions). The genotypes and G × E interactions revealed significant differences at p <0.01 for seed yield indicating varieties and testing environments were distinct from each other. Additive main effects and multiplicative interaction analysis (AMMI-biplot) indicated that the yield performances of indigenous coriander genotypes were highly affected by the environments. The first two principal component axes (PCA 1 and PCA 2) were significant and they explained 67% of the total genotype x environment interaction of which 42.4% and 24.6% were represented by PCA 1 and PCA 2, respectively. A biplot generated using genotypic and environmental scores of the first two AMMI components demonstrated that genotype with larger PCA 1 and lower PCA 2 scores were high yielding and stable genotypes and genotypes with lower PCA 1 and larger PCA 2 scores were low yielding and unstable cultivars in tested locations. The genotype GC 5 C-101 (ICS 4) showed higher grain yields (16.35 q ha-1) over grand mean (13.03 q ha-1) and also had the minimum PCA 1 score, minimum AMMI stability value (ASV) and yield stability index (YSI). Therefore genotype ICS 4 (Chhattisgarh Shri Chandrahasini Dhaniya -2) showed wider stability across different agro climatic environments of Chhattisgarh.


2015 ◽  
Vol 21 ◽  
pp. 41-48
Author(s):  
Gebremedhin Welu

The objective of this experiment was to estimate the magnitude of genotype X environment interaction on grain yield and yield related traits. Twelve varieties of food barley were included in the study planted in randomized complete block design with three replications. The ANOVA of combined and individual location revealed significant differences among the food barley genotypes for grain yield and other traits. The results of ANOVA for grain yield showed highly significant (p≤0.01) differences among genotypes evaluated for grain yield at Maychew and significant (p≤0.05) differences in Korem, Alage and Mugulat. The ANOVA over locations showed a highly significant (p≤0.01) variation for the genotype effect, environment effects, genotype X environment interaction (GEI) effect and significant (p≤0.05) variation for GEI effect of yield and for most of the yield related traits of food barley genotypes. Haftysene, Yidogit, Estayish and Basso were the genotypes with relatively high mean grain yield across all locations and they are highly performing genotypes to the area. Among locations, the highest mean grain yield was recorded at Korem and it was a suited environment to all the genotypes whereas Mugulat is unfavoured one. ECOPRINT 21: 41-48, 2014DOI: http://dx.doi.org/10.3126/eco.v21i0.11903


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