Assessing the relationship between yield component in pea (Pisum sativum L.) varieties using correlation and path analysis under Sulaimani condition

Authors

  • Bestoon Ali Abdolla Assistant Lecturer

DOI:

https://doi.org/10.59658/jkas.v6i3.719

Abstract

Correlation and path analysis studies were conducted during the winter season of 2017-2018 and spring season of 2018. The present experiment was conducted to study the availability and determines the relative importance of primary and secondary traits in field pea, through the association among the characters viz. ( No. of pods plant-1 - Weight of pods plant-1(g) – Pod length plant-1 (cm) - No. of seeds pod-1 - Weight of seeds pod-1 (g) - Weight of seeds plant-1 (g) - 100 seed Weight (g) - Biological weight plant-1 (g) - Harvest Index - Seed yield (Kg ha-1) ) . The experimental material comprised of 4 field pea varieties viz. (Americana, Jeza, Pakland , Avola). From each plot, five competitive plants were selected randomly for recording observation for all quantitative characters. The results were summarized as follow, highly significant and positive association were recorded between seed yield with other characters except for the character 100 seed weight which was not significant at winter season and significant at spring season, but not significant with harvest index at both seasons. The highest positive direct effect in seed yield produced by the weight of seeds per plant at both seasons, while the highest positive indirect effect in seed yield recorded by weight of seeds per plant via weight of pods per plant at both seasons.

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Published

09/30/2019

How to Cite

Abdolla, B. A. (2019). Assessing the relationship between yield component in pea (Pisum sativum L.) varieties using correlation and path analysis under Sulaimani condition. Journal of Kerbala for Agricultural Sciences, 6(3), 1–15. https://doi.org/10.59658/jkas.v6i3.719

Issue

Vol. 6 No. 3 (2019): Volume 6, Issue 3 Year 2019

Section

Articles

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Copyright (c) 2019 Journal of Kerbala for Agricultural Sciences

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