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Multi-variate analysis for yield evaluation in rice (Oryza sativa L.) genotypes

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  • Multi-variate Analysis For Yield Evaluation In Rice (Oryza Sativa L.) Genotypes
  • Multi-variate analysis for yield evaluation in rice (Oryza sativa L.) genotypes

Nwafor Daniel Chijioke * and Oluwatoyin Sunday Osekita

Department of Plant Science and Biotechnology, Adekunle Ajasin University Akungba Akoko, Ondo State, Nigeria.
 
Research Article
GSC Advanced Research and Reviews, 2021, 06(03), 067-075.
Article DOI: 10.30574/gscarr.2021.6.3.0042
DOI url: https://doi.org/10.30574/gscarr.2021.6.3.0042
Received on 01 February 2021; revised on 28 February 2021; accepted on 02 March 2021
 
Field experiment was carried out at the experimental field of the Department of Plant Science and Biotechnology beside the screen house, to study yield evaluation in rice genotypes. The plot was laid out in a randomized complete block design (RCBD) and the treatments replicated three times. Seven rice genotypes sourced from the department crop improvement unit were sowed in a plot size of 5×1m. The study was conducted in 2016/2017 planting seasons. Data were collected on yield component traits i.e. number of tillers, plant height, number of days to panicle initiation, number of days to maturity, panicle length, panicle weight, number of spikelet per panicle, number of grain per panicle, 1000 grain weight, grain yield per hill and flag leaf length. The result of factor analysis indicated that the first factor was positively loaded for yield component trait however; the first six principal components jointly accounted for 98.99% of the total variation among the genotype studied. High levels of variability expressed among the varieties suggested that further improvement in the varieties is possible.
 
Variation; Principal component; Rice, Variety
https://gscarr.gsconlinepress.com/sites/default/files/fulltext_pdf/GSCARR-2021-…

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Nwafor Daniel Chijioke and Oluwatoyin Sunday Osekita. Multi-variate analysis for yield evaluation in rice (Oryza sativa L.) genotypes. GSC Advanced Research and Reviews, 2021, 6(3), 067-075. Article DOI: https://doi.org/10.30574/gscarr.2021.6.3.0042

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