GENOTYPIC VARIANCE AND SELECTION CRITERIA IN GROUNDNUT (ARACHISHYPOGAEAL.) BASED ON OIL QUALITY AND AGRONOMIC TRAITS

Authors

  • Nafisa Abdurrasheed
  • A. Usman
  • Y. Oladosu

DOI:

https://doi.org/10.33003/fjs-2021-0503-751

Keywords:

Genetic Advance, Genotype, Heritability, Traits association, Phenotype

Abstract

Variability gives room for recombination which is important for any crop improvement program. Based on this contextual, this work was conducted to evaluate genetic variability among groundnut germplasm and establish relationships between oil quality and agronomic traits using multivariate analysis. To achieve this objective, fifteen groundnut genotypes were evaluated in a randomized complete block design with three replications. Data were collected on oil and yield quality traits. The estimates of genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were high for number of pods and number of seeds per plant, carbohydrate and protein. Broad sense heritability estimates for agronomic and oil content traits ranged from 49.57% - 99.06% while the genetic advance expressed as percentage of mean estimates ranged from 17.73% -114.38%.  The evaluated genotypes were clustered into four main groups based on oil and yield quality traits using UPGMA dendrogram. Hence, hybridization of group II with either group I, III or IV could be used to achieve higher vigor or heterosis among the genotypes. The number of pods per plant showed a significant correlation with pod weight per plant (r =0.79) and the number of seeds (0.99). However, most of the oil content traits recorded a non-significant negative correlation. It was concluded that number of pods, seeds per plant, and fat content might be the major agronomic and oil quality traits as selection criteria for improving groundnut genotypes. Also, this assessment could be used in development of reliable selection criteria for important agronomic traits in groundnut

References

Brugano L. &Trigiante D. (1998); Solving differential problem by multistep initial andBoundary value method: Gordon and Breach Science publication. Amsterdam.

Curtis C.F. and HirschfelderJ.O (1952).; Integration of stiff Equations, National Academy of Sciences. Vol.38: 235-243.

Chu M.T, Hamilton H. (1987); Parallel solution of ODE’s by multi-block methods.SIAM. J Sci. Stat. Comput. Vol.8: 342-353.

DahlquishC.G (1974), Problem related to the numerical treatment of stiff differentialequations. International Computing Symposium: Vol. 307 – 314.

Milner, W.E, (1953); Numerical solution of differential equation. John Wiley, New York

Musa H, MB Sulaiman, F ismail, N Senu, ZA Majid, ZB Ibrahim (2014), A new fifth Order implicit block method for solving first order stiff ordinary differential equation. Malaysian Journal of Mathematical Science. Vol. 5: 45-59.

Musa H, MB Sulaiman, F Ismail, ZB Ibrahim (2013); An accurate block solver for stiff initial value problems. ISRN Applied Mathematics. Hindawi.

Musa H., Suleiman M.B., Ismail F, Senu N, ZB Ibrahim (2012); An improved 2-point block backward differentiation formula for solving initial value problems. AIP Conference proceeding. Vol. 1522: 211-220.

Musa H, M.A.Unwala (2019); Extended 3-point super class of block backward differentiation formula for solving initial value problem. 38th conference of National Mathematical Science university of Nigeria.Nsukka.

Published

2021-11-03

How to Cite

Abdurrasheed, N., Usman, A., & Oladosu, Y. (2021). GENOTYPIC VARIANCE AND SELECTION CRITERIA IN GROUNDNUT (ARACHISHYPOGAEAL.) BASED ON OIL QUALITY AND AGRONOMIC TRAITS. FUDMA JOURNAL OF SCIENCES, 5(3), 247 -258. https://doi.org/10.33003/fjs-2021-0503-751