Ahmed Muhammad Shahzad, Majeed Abid, Attia Kotb A, Javaid Rana Arsalan, Siddique Faiza, Farooq Muhammad Shahbaz, Uzair Muhammad, Yang Seung Hwan, Abushady Asmaa M
Rice Research Program, Crop Sciences Institute, National Agricultural Research Center, Islamabad, Pakistan.
Department of Biochemistry, College of Science King Saud University, P.O. Box 11451, Riyadh, Saudi Arabia.
Sci Rep. 2024 Apr 24;14(1):9416. doi: 10.1038/s41598-024-55510-x.
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, Wi, σ 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. 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.
水稻(Oryza sativa L.)是禾本科的重要成员,世界上一半以上的人口依靠水稻获取膳食营养。具有更高产量、抗逆性和更广泛适应性的水稻品种对于确保生产稳定性和粮食安全至关重要。本研究的基本目标是在巴基斯坦的水稻种植区鉴定出具有稳定性能和更广泛适应性的高产水稻基因型。在巴基斯坦四个省份的12个水稻种植生态区进行了一项重复三次的随机区组设计试验,涉及20个绿色超级稻(GSR)新品系。通过使用不同的单变量和多变量统计方法评估了籽粒产量稳定性表现。方差分析显示,主要产量构成性状的均方在基因型、地点和基因型与环境互作之间存在显著差异(p < 0.05)。除单株分蘖数外,所有研究性状的基因型方差均高于环境方差。广义遗传力估计范围为44.36%至98.60%。基于ASV、ASI、bi、Wi、σ和WAAS统计,基因型G1、G4、G5、G8、G11和G12的参数统计值最低,基于稻谷产量被认为是更稳定的基因型。加性主效应和乘积互作(AMMI)模型显示基因型存在显著变异(p < 0.05),环境无显著变异,基因型与环境互作高度显著。互作中PC1和PC2的变异比例显示稻谷产量变异为67.2%。基于“GGE双标图的均值与稳定性分析”、“哪一个在哪赢”GGE双标图、“判别力与代表性”稳定性模式、“IPCA和WAASB/GY”比值稳定性热图以及基因型排名,观察到基因型G1、G2、G3、G5、G8、G10、G11和G13是产量潜力超过8吨/公顷的理想基因型。“判别力与代表性”稳定性模式确定了两个环境,E5(开伯尔-普赫图赫瓦省迪尔汗)和E6(俾路支省乌斯塔穆罕默德)最适合评估基因型产量表现。基于这些发现,我们得出结论,基因型G1、G2、G3、G5、G8、G10、G11和G13可纳入商业品种开发过程和未来育种计划。