Unraveling the stable green super rice lines across the multi-environment yield trials | [Pakistan Journal of Agricultural Sciences • 2022]

Author(s):

1. Muhammad Kashif Naeem: National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre,Park Road, Islamabad 45500,Pakistan

2. Madiha Habib: National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre,Park Road, Islamabad 45500,Pakistan

3. Syed Adeel Zafar: National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre,Park Road, Islamabad 45500,Pakistan

4. Muhammad Uzair: National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre,Park Road, Islamabad 45500,Pakistan

5. Shehzad Amir Naveed: Institute of Crop Science, Chinese Academy of Agricultural Sciences,Beijing,China

6. Jianlong Xu: Institute of Crop Science, Chinese Academy of Agricultural Sciences,Beijing,China

7. Jauhar Ali: International Rice Research Institute,Los Baños,Philippines

8. Zhikang Li: Institute of Crop Science, Chinese Academy of Agricultural Sciences,Beijing,China

9. M. Ramzan Khan: National Institute for Genomics and Advanced Biotechnology, National Agriculture Research Centre,Park Road, Islamabad 45500,Pakistan

Abstract:

The stable performance of cultivars is a prerequisite for enhanced yield production to ensure food security. Identification o f the stable yield performing genotype is the necessity of any breeding program to improve the livelihood of farmers. The present study was performed to evaluate the genotype and environment interaction of 22 green super rice (GSR) genotypes at eight different locations in Pakistan. The genotype ´ environment interaction was assessed by univariate and multivariate analysis for yield and yield-related traits. The harvest index, grain yield, total biomass, and straw yield showed higher variation among the genotypes, evaluated by PCA biplot analysis. The multiplicative interactions (AMMI) analysis of variance was found significant among genotypes, environments (locations), and genotype ´ environment interaction (G ´ E). The AMMI model demonstrated that genotypes S8 and S16 performed best across the environments, whereas, genotypes S18, S17, S15, and S5 revealed stable performance across the environments. The two-dimensional GGE biplot explained 56.74% variation for all studied traits across the environments. The GGE biplot results indicated that genotypes S13, S15, S18, S1, and S5 showed stable yield performance across the environments, whereas genotypes S16 and S8 demonstrated the high yield genotypes with low stability. Based on these multivariate analyses, genotype S5 depicted stable performance across the environments, while genotypes S8 and S16 were high yielding with low stability across the environments. Among the environments, Islamabad, Muzaffargarh, and Sahiwal are the most suitable environments for GSR genotypes cultivation. These results could be helpful in the selection of genotypes and will be recommended for commercial cultivation in the future.

Page(s): 953-963

DOI: 10.21162/PAKJAS/22.96

Published: Journal: Pakistan Journal of Agricultural Sciences, Volume: 59, Issue: 6, Year: 2022

Keywords:

PCA , grain yield , GGE biplot , multienvironment , AMMI analysis , Multivariate analysis , Green Super Rice

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