Canonical Correlation Analysis Between Plant Characteristics and Yields Component in Oil Palm (Elaeis Guineensis Jacq.)

E. Iguodala; J. Osemwenkhae; F. Oyegue; A. Iduseri; N. Ikoba

PDF

Published: 2025-11-24

Keywords:

Oil Palm, Optim, Least Absolute Shrinkage and Selection Operator, Canonical Correlation Analysis

E. A. Iguodala

Statistics Division, Nigerian Institute for Oil Palm Research (NIFOR), P.M.B 1030, Benin City, Edo State, Nigeria

J. E. Osemwenkhae

Statistics Division, Nigerian Institute for Oil Palm Research (NIFOR), P.M.B 1030, Benin City, Edo State, Nigeria

F. O. Oyegue

Department of Statistics, Faculty of Physical Sciences, University of Benin, Benin City, Nigeria

A. Iduseri

Department of Statistics, Faculty of Physical Sciences, University of Benin, Benin City, Nigeria

N. Ikoba

Department of Statistics, Faculty of Physical Sciences, University of Ilorin, Kwara State, Nigeria

Abstract

Canonical correlation analysis (CCA) is a multivariate statistical technique that describes the associations between two sets of variables. In this paper a formulation of Canonical correlation analysis based on the Least Absolute Shrinkage and Selection Operator (LASSO) is utilized to examine the relationship between plant characteristics and oil palm yield. The modified CCA based on LASSO was applied to oil palm data from Nigerian Institute for Oil Palm Research (NIFOR), Nigeria. The analysis was based on an approximation using a modified optim algorithm in R statistical package. The results showed that the modified CCA approach based on LASSO distinctively selected the pairwise variables that mutually maximized the canonical correlation. The method identified optimal combinations of the key variables on oil palm characteristics for accurate prediction plant vegetative growth and development. The newly developed approach is suggested as a better alternative to the classical CCA in assessing plant development and yield.

Downloads

Download data is not yet available.

Issue

Vol. 8 No. 1 (2025)

Section

Articles

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

Iguodala, E., Osemwenkhae, J., Oyegue, F., Iduseri, A., & Ikoba, N. (2025). Canonical Correlation Analysis Between Plant Characteristics and Yields Component in Oil Palm (Elaeis Guineensis Jacq.). Benin Journal of Statistics, 8(1), 50– 59. https://bjs-uniben.org/index.php/home/article/view/42

References

Ayodeji, I. O. and Obilade, T.O. (2016). A Predictive Model for Canonical Correlation Analysis with Implications for the Simple and Multiple Correlations.

Bach, F.R., and Jordan, M.I. (2005). A probabilistic interpretation of canonical correlation analysis, Tech. Rep. 688.

Balkaya, A., Cankaya, S., and Ozbakir, M. (2011). Use of canonical correlation analysis for determination of relationships between plant characters and yield components in winter squash (cucurbita maxima duch.) populations. Bulgarian journal of agricultural science, 17(5), 606-614.

Cankaya, S. and Kayaalp, G.T. (2010). Estimation of relationship between live weights and some body measurements in German farm × hair crossbred by canonical correlation analysis. J Anim Prod, 48(2), 27-32.

Daher, R. F., Pereira, A.V., Menezes, B.R., Cassaro, S., Cecon, A.A., Furlani, E. P., Junior, A.T., Pereira, M.G., Stida, W.F., and Vidal, A.F. (2018). Canonical correlations among morpho-agronomic and chemical traits in hybrids between elephant grass and millet. Australian Journal of Crop Science, 12(02), 210-216.

Hardle, W. and Simar, L. (2007). Canonical Correlation Analysis. Applied Multivariate Statistical Analysis, 321–330.

Hoerl, A.E. and Kennard, R.W. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1), 55–67.

Hotelling, H. (1935). The most predictable criterion. Journal of educational Psychology, 26(2), 139.

Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28(3/4), 321-377.

Knapp, T. R. (1978). Canonical correlation analysis: A general parametric significancetesting system. Psychological Bulletin. 85(2), 410–416.

Muller, K. (1982). Understanding Canonical Correlation Analysis through the GeneralLinear Model and Principal Components, The American Statistician, 36(4), 342-346.

Thompson, B. (1984). Canonical Correlation Analysis: Uses and Interpretation, Sage, Newbury Park. DOI: https://doi.org/10.4135/9781412983570.

Vieira, C. R., Oscarlina, L. W., Kuang, H., and Fernando, S. (2019). Canonical Correlation Analysis Between Growth and Nutrition in Teak Seedlings. Floresta e Ambiente, 26(2), 2179-8087.

Vinod, H. D. (1976). Canonical ridge and econometrics of joint production. Journal of Econometrics, 4(2), 147–166.

Waugh, F.V. (1942). Regressions between sets of variables. Econometrica, Journal of the Econometric Society, 290–310.

Article Sidebar

Main Article Content