Country-wide, multi-location trials of Green Super Rice lines for yield performance and stability analysis using genetic and stability parameters

Abstract

Rice (Oryza sativa L.) is an important member of the family Poaceae and more than half of world population depend for their dietary nutrition on rice. Rice cultivars with higher yield, resilience to stress and wider adaptability are essential to ensure production stability and food security. The fundamental objective of this study was to identify higher-yielding rice genotypes with stable performance and wider adaptability in a rice growing areas of Pakistan. A triplicate RCBD design experiment with 20 Green Super Rice (GSR) advanced lines was conducted at 12 rice growing ecologies in four Provinces of Pakistan. Grain yield stability performance was assessed by using different univariate and multivariate statistics. Analysis of variance revealed significant differences among genotypes, locations, and G x E interaction for mean squares (p < 0.05) of major yield contributing traits. All the studied traits except for number of tillers per plant revealed higher genotypic variance than environmental variance. Broad sense heritability was estimated in the range of 44.36% to 98.60%. Based on ASV, ASI, bi, Wi², σ²_i and WAAS statistics, the genotypes G1, G4, G5, G8, G11 and G12 revealed lowest values for parametric statistics and considered more stable genotypes based on paddy yield. The additive main effects and multiplicative interaction (AMMI) model revealed significant variation (p < 0.05) for genotypes, non-signification for environment and highly significant for G × E interaction. The variation proportion of PC1 and PC2 from interaction revealed 67.2% variability for paddy yield. Based on 'mean verses stability analysis of GGE biplot', 'Which-won-where' GGE Biplot, 'discriminativeness vs. representativeness' pattern of stability, 'IPCA and WAASB/GY' ratio-based stability Heat-map, and ranking of genotypes, the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 were observed ideal genotypes with yield potential more than 8 tons ha^-1. Discriminativeness vs. representativeness' pattern of stability identifies two environments, E5 (D.I Khan, KPK) and E6 (Usta Muhammad, Baluchistan) were best suited for evaluating genotypic yield performance. Based on these findings we have concluded that the genotypes G1, G2, G3, G5, G8, G10, G11 and G13 could be included in the commercial varietal development process and future breeding program.

Keywords: GGE biplot; G × E interaction; Paddy yield; Rice; Stability.

Figure 1

Map of experimental sites across Pakistan with legends indicating the locations of the Institutes where experiment was conducted. (ArcGIS-10.8 Software was used to generate the map).

Figure 2

The GGE biplot design of genotype × environment interaction of 20 GSR lines and 2 check cultivars planted at 12 environments during the year 2021 for paddy yield. Note: METAN R package was used to generate figures.

Figure 3

‘Mean versus stability’ GGE biplot of 20 GSR lines including checks planted at 12 environments during the year 2021 for paddy yield.

Figure 4

‘Which − won − where’ view of GGE biplot 20 GSR lines including checks under 12 environments during the year 2021 for paddy yield.

Figure 5

‘Discriminativeness vs. representativeness’ view of GGE biplot of 18 GSR lines and 2 check cultivars grown under 12 environments during the year 2021 for paddy yield.

Figure 6

a Shows the genotype ranking depending on the number of principal component axis used for estimating the WAASB index. Four clusters of genotypes are shown by label colors (red) unproductive and unstable genotypes; (blue) productive, but unstable genotypes; (black) stable, but unproductive genotypes; and (green), productive and stable genotypes. b Shows the genotype ranking depending on the WAASB/GY ratio. The ranks obtained with a ratio of 100/0 consider exclusively the stability for the genotype ranking. On the other hand, a ratio of 0/100 considers exclusively the productivity for the genotype ranking.

Figure 7

The GGE biplot ‘Ranking Environments’ profile to rank environments for the ideal location of 20 GSR lines including checks grown under 12 environments during the year 2021 for paddy yield.

Figure 8

The GGE biplot ‘Ranking genotypes’ pattern to rank genotypes to find out the ideal genotype of 20 GSR lines including checks evaluated under 12 environments during the year 2021for grain yield.