Nutritional cluster analysis of leguminous food sources across West Africa

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.

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Publication Details

Journal
International Journal of Data Analysis Techniques and Strategies
Published
2025-01-01
DOI
https://doi.org/10.1504/ijdats.2025.144966
Primary Topic
Agriculture and Rural Development Research
Type
article
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article

Nutritional cluster analysis of leguminous food sources across West Africa

Donald Douglas Atsa', N.A. am, Moses Terkula Ukeyima, Gabriel Shimasaan Iorundu
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International Journal of Data Analysis Techniques and Strategies
Agriculture and Rural Development Research
article

Nutritional cluster analysis of leguminous food sources across West Africa

Donald Douglas Atsa', N.A. am, Moses Terkula Ukeyima, Gabriel Shimasaan Iorundu
article en

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.

International Journal of Data Analysis Techniques and StrategiesVol. 17(1)
Joseph Sarwuan Tarka University Makurdi (NG)
Zero hunger
Openalex Percentile: Top 96%
Agriculture and Rural Development Research
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Nutritional cluster analysis of leguminous food sources across West Africa — Donald Douglas Atsa', N.A. am, et al. · International Journal of Data Analysis Techniques and Strategies (2025) | TGRS Research Map | TGRS