Title: Nutritional cluster analysis of leguminous food sources across West Africa

Authors: Donald Douglas Atsa'am; Gabriel Shimasaan Iorundu; Moses Terkula Ukeyima

Addresses: Department of Computer Science, College of Physical Sciences, Joseph Sarwuan Tarka University, Makurdi, 970212, Nigeria ' Department of Computer Science, College of Physical Sciences, Joseph Sarwuan Tarka University, Makurdi, 970212, Nigeria ' Department of Nutrition and Dietetics, College of Food Technology and Human Ecology, Joseph Sarwuan Tarka University, Makurdi, 970212, Nigeria

Abstract: The present form of the data on West African legumes reported in the West Africa Food Composition Table (WAFCT) do not reflect sub-groupings based on (dis)similarity in nutritive value. A possible consequence is that an uninformed user interested in leguminous food could randomly pick any from the data since all are summarily classified as one family in the WAFCT. To resolve this, the objective of this study was to apply the clustering technique to form sub-groups based on similarity in nutritional content. Three clusters were extracted, and unique properties have been established for food sources in each cluster at the granular level of nutrients. Going by the clustering, users who are interested/not interested in a particular content could look up the cluster with a lower, moderate, or higher content of the desired/non-desired element. The results are useful in the selection of raw materials, formulation of nutritional guidelines, and food labelling.

Keywords: legumes; nutritional analysis; legumes food sources; WAFCT; West Africa Food Composition Table; k-means clustering.

DOI: 10.1504/IJDATS.2025.144966

International Journal of Data Analysis Techniques and Strategies, 2025 Vol.17 No.1, pp.65 - 75

Received: 16 Feb 2024
Accepted: 24 May 2024
Published online: 14 Mar 2025 *

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