Vol. 12, Issue 10 (2023)

Author(s):
Shivam D Joshi, Dinesh J Parmar, Kalpesh V Patel and Mahesh B Parmar

Abstract:
The twenty two midlate rice genotypes having fine type were evaluated at four different locations of Gujrat in the years of 2021-22 in RCBD with three replications. The data on grain yield were subjected to statistical analysis with a view to fulfill the objective: (1) To study the G×E interaction using the multivariate technique (AMMI model) (2) To find the stable genotypes using AMMI model and AMMI based stability measures. The grain yield data were subjected to analysis of variance and pooled over locations. GxE interaction was found significant indicating genotypes performed differently in different locations. The results of the AMMI model indicated that GEI was further divided into two PCA axes IPCAI (65.22%) and IPCAII (22.49%) which together contributed 87.71 percent of the GEI. E1 (Nawagam) and E3 (Navsari) were found high yielding environments whereas E2 (Dabhoi) and E4 (Vyara) were found low yielding environments. Mean vs. IPCAI biplot found that genotypes G7, G19, G14 and G11 had general adaptability to the environments. Genotypes G3, G8, G17 and G18 were higher yielder and adapted to favorable environments. Where, genotypes G10, G12, G16 and G22 were lower yielders and adapted to poor environments. According to IPCA scores genotypes G3, G5, G7, G8, G11, G13, G17, G18 and G19 had positive GEI with environments E1 and E3. Which-won-where biplot indicated that genotypes G3 and G8 were vertex genotypes and they gave higher grain yield in environments E1 and E3. Genotypes G2 and G4 were vertex genotypes and high yielding in the E4 and E2 respectively. Genotypes G11, G7, G14 and G19 were the most stable genotypes as had low values of W_{i (AMMI)}, ASV, ASTAB_i and simultaneous selection indices. Genotypes G15, G4, G21 and G18 were found unstable across the environments.