Identification of adaptable rice genotypes under diverse production environments using a multivariate statistical model

  • Hari Kesh Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, Haryana, India
  • Akshay Kumar Vats Department of Agriculture, Maharishi Markandeshwar University, Ambala, Haryana, India
  • Mujahid Khan Agricultural Research Station, SKNAU, Jobner, Rajasthan, India
  • Satender Yadav Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar, Haryana, India


Basmati rice is sold at a higher price in both local and international markets due to its superior grain qualities. Identification of high performing
and adaptable genotypes under multi-environmental conditions is very crucial to sustain rice production. In the present research, sixteen
Basmati rice genotypes were evaluated under three diverse production environments i.e. transplanted (TPR), direct seeded (DSR), and
system of rice intensification (SRI) during two consecutive kharif seasons. The experiment was laid down in randomized block design with
three replications. The primary objective of this research was to identify stable genotypes adaptable to different production environments
with a high mean using the GGE biplot model. Genotypes explained a higher proportion (44.25 to 60.71 %) of the total sum of squares
while environment attributed only (7.71 to 23.26%). Genotype by environment interaction contributed 31.58% to 36.77% of the total
variation for studied traits. Under DSR, Haryana Basmati-1 for hulling%, milling%, and head rice recovery% while Improved Pusa Basmati
1 for amylose content were identified as specifically adapted genotypes. Likewise, under SRI, HKR 98-476 for hulling% and milling%, Pusa
Basmati-1 for head rice recovery%, and Improved Pusa Basmati -1 for amylose content were found suitable genotypes. These genotypes
can be recommended for commercial cultivation for specific production environments.

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How to Cite
Kesh, H., A. Kumar Vats, M. Khan, and S. Yadav. “Identification of Adaptable Rice Genotypes under Diverse Production Environments Using a Multivariate Statistical Model”. Emirates Journal of Food and Agriculture, Vol. 34, no. 3, Apr. 2022, doi: Accessed 25 May 2022.
Research Article