International Journal of Statistics and Applied Mathematics
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2023, Vol. 8, Special Issue 6

Correlation and path coefficient analysis of quantitative traits in maize (Zea mays L.)


Author(s): Praful M Sondarava, Manish B Patel, Tejaskumar H Borkhatariya, Kuldeep M Akbari and Pinakin K Parmar

Abstract: The present investigation was carried out with 238 genotypes that were grown in Randomized Complete Block Design (RCBD) with three replications to assess correlation and path coefficients during Rabi 2020. Correlation analysis revealed that kernel yield per plant found a significant positive association with cob weight, cob length, cobs per plant, cob girth and kernel per row. Path analysis showed that days to 50% tasseling, cobs per plant, cob weight, cob length, kernel row per cob and cob girth were the major characters having positive direct effects and significant association with kernel yield per plant. Further, the characters viz., cobs per plant and cob weight had a true relationship with kernel yield per plant. Path coefficient analysis can be an effective technique to identify the yield attributes in maize.

DOI: 10.22271/maths.2023.v8.i6So.1516

Pages: 1140-1144 | Views: 258 | Downloads: 6

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How to cite this article:
Praful M Sondarava, Manish B Patel, Tejaskumar H Borkhatariya, Kuldeep M Akbari, Pinakin K Parmar. Correlation and path coefficient analysis of quantitative traits in maize (Zea mays L.). Int J Stat Appl Math 2023;8(6S):1140-1144. DOI: 10.22271/maths.2023.v8.i6So.1516

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