Utilizing Genetic Traits Distributions to Enhance Rice Breeding Programs: A Study of Skewness and Kurtosis in Segregating Generations
G. S. Shai Prasanna, J. L. Joshi, Ajish Muraleedharan
Journal of Experimental Agriculture International · pp. 741–760 · Published 9 Sep 2024
10.9734/jeai/2024/v46i92871Abstract
This study analyzed the genetic basis of skewness and kurtosis in segregating generations of six rice crosses. Skewness and kurtosis values were calculated for ten biometrical traits across the populations. The traits examined included plant height, number of productive tillers, panicle length, grain yield, and grain dimensions. Results showed diverse patterns of skewness and kurtosis across traits, crosses and generations. Platykurtic distributions were predominant for most traits, suggesting flatter distributions with lighter tails compared to normal. Skewness varied between positive and negative across traits and crosses. Some traits like grain L/B ratio tended to show positive skewness more frequently. Plant height often exhibited negative skewness. The diversity in distribution characteristics indicates significant genetic variability in the populations. Traits showing platykurtic distributions with negative skewness, such as plant height in several crosses, suggest duplicate epistasis and polygenic control. Positively skewed platykurtic distributions for traits like grain dimensions in some crosses indicate complementary epistasis requiring intense selection. Hence, skewness denotes the horizontal pull and kurtosis deals with vertical peaks of the segregating population. The findings provide insights into the genetic control of key rice traits and have implications for breeding strategies. The complex distribution patterns revealed offer a rich basis for selective breeding, depending on specific trait objectives.
Cited by 4
Edwin Afriyie Owusu, Zhanglun Sun, Shengqin Liu · Agronomy · 2025
Masud Perves, Abu Sayeed Md Hasibuzzaman, Rashadul Hasan · Reproduction and Breeding · 2025
João Everthon da Silva Ribeiro, Antonio Gideilson Correia da Silva, Pablo Henrique de Almeida Oliveira · IEEE Access · 2025
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