Analysis of morphological characteristics of six varieties of cassava using discriminant analytical approach
DOI:
https://doi.org/10.64497/jssci.122Keywords:
CassavaMorphological traits; Multiple Discriminant Analysis; Varietal classification; NigeriaAbstract
Abstract
Cassava (Manihot esculenta Crantz) is a vital staple crop in sub-Saharan Africa, yet accurate varietal identification is often hindered by overlapping morphological traits influenced by environmental variability. This study applied Multiple Discriminant Analysis (MDA) to evaluate the discriminatory capacity of six morphological traits—leaf width, leaf length, leaf area, leaf index, plant height, and mean angle—across six cassava varieties cultivated in Nigeria. Data from 96 plants were analyzed using descriptive statistics, MANOVA, Mahalanobis distances, and canonical discriminant functions. Results showed that leaf area, leaf index, and mean angle were the most influential traits for separation. However, classification accuracy was modest, with an overall accuracy of 45.8% (APER = 54.2%). TMS98212 (75%) and NR100235 (56.7%) achieved the highest correct classification, while B515, COB61, IITA-IBA980581, and NWAGERI were completely misclassified. Canonical discriminant plots confirmed that TMS98212 and NR100235 clustered apart, whereas the other varieties overlapped extensively. These findings highlight the limitations of morphological traits as standalone classifiers and underscore the need to integrate molecular markers and advanced computational approaches for robust varietal identification.
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[1] Asare, P. A., Galyuon, I. K. A., Sarfo, J. K., & Tetteh, J. P. (2011). Morphological and molecular diversity studies of cassava germplasm in Ghana. African Journal of Biotechnology, 10(63), 13900–13908. DOI: https://doi.org/10.5897/AJB11.929
[2] Derso, E., & Mohamud, S. (2018). Morphological characterization of cassava varieties in Ethiopia. International Journal of Plant Research, 8(2), 45–53.
[3] Ezekwe, A. G. (2017). Application of discriminant analysis in the morphometric Githiri, S. M., et al. (2006). Morphological variation of cassava clones in the coastal region of Kenya. Journal of Plant Breeding and Crop Science, 1(2), 21-27.
[4] FAO. (2013). Cassava: A vital food security crop in Africa. Food and Agriculture Organization of the United Nations, Rome.
[5] Johnson, R. A., & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson Prentice Hall.
[6] Kouakou, D. A., Kouadio, Y. J., Kouassi, K. E., Koffi, K. F., & Akaffou, D. S. (2023). Agro-morphological variability of cassava in Côte d’Ivoire. Journal of Applied Biosciences, 181, 18962–18973. DOI: https://doi.org/10.35759/JABs.181.7
[7] Montalvo, C., et al. (2014). Multivariate analysis of morphological characteristics of Peruvian cocoa beans (Theobroma cacao L.). Scientia Agropecuaria, 5(3), 123-135.
[8] Nwakuya, M. T., Biu, E. O., & Merua, G. O. (2022). Multiple Discriminant Analysis of five cassava varieties. International Journal of Innovative Mathematics, Statistics & Energy Policies, 10(4), 71–83.
[9] Olayiwola, M. O., et al. (2022). Morphological characterization and discriminant analysis of sesame (Sesamum indicum L.) accessions. Journal of Agricultural Science and Practice, 7(2), 45-53.
[10] Zhang, D., Liu, X., & Yang, C. (2019). Genetic diversity of cassava germplasm revealed by morphological traits and SSR markers. PLOS ONE, 14(3), e0212875.
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Copyright (c) 2026 Samuel U. Enogwe, Chinelo U. Chikwelu, Goodluck O. Merua, Ihuoma L. Onyeugo
This work is licensed under a Creative Commons Attribution 4.0 International License.
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