International Journal of Pharmacognosy and Pharmaceutical Sciences

Vol. 4, Issue 2, Part A (2022)

Assessment of genetic diversity for yield and quality traits of rice landraces of Telengana by multivariate analyses

Author(s):

Ponselvan A, Sanghamitra Rout, Pusarla Susmitha, Poulami Sil, SR Harish Chandar and Seri Subba Santosh

Abstract:

The present investigation on ‘Assessment of genetic diversity for yield and quality traits of rice landraces of Telengana by multivariate analyses’, was conducted during the kharif-2021, which characterize 23 rice landraces with 21 yield and quality traits. All the genotypes were significantly different for every trait. The genetic variability studies emulated, high PCV and GCV was absorbed for the traits followed, number of fertile spikelets per panicle, elongation ratio, kernel length breadth ratio, protein content, water uptake ratio, harvest index, number of effective tillers per plant, alkali spread value, biological yield and grain yield per plant. High heritability coupled with high genetic advance was observed on the following characters viz., harvest index, grain breadth, alkali spread value, protein content, number of fertile spikelets per panicle, grain yield per plant, grain length, biological yield, plant height, kernel length breadth ratio, amylose content and thousand grain weight. It explains that there is scope of improvement through selection in these characters. Principal Component Analysis revealed usage of Akshaya ponni, Nagara, Halla batta, Gadakadhiya Mahi, Aashudhee, Ghalima and Kukuda Munde would be rewarding in crop improvement for good yield, likewise, Bhairojlu, Daddigha, Gadakadhiya Mahi, Kaala Jeera, Krishtampeta gold and Kumar Gorla would be rewarding in improvement of quality traits.

Pages: 42-48  |  23 Views  11 Downloads

How to cite this article:
Ponselvan A, Sanghamitra Rout, Pusarla Susmitha, Poulami Sil, SR Harish Chandar and Seri Subba Santosh. Assessment of genetic diversity for yield and quality traits of rice landraces of Telengana by multivariate analyses. Int. J. Pharmacognosy Pharm. Sci. 2022;4(2):42-48.
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