Please use this identifier to cite or link to this item: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31609
Title: Essential Mineral Elements Profile of Selected Foods commonly consumed in Nigeria necessary for Machine Learning operation.
Authors: Durojaiye, Abdulwahab Ismail
Olorunsogo, Samuel Tunde
Adejumo, Bolanle Adenike
Babawuya, Alkali
Muhamad, Ida Idayu
Keywords: mineral elements
micronutrients
machine learning
food products
non-destructive equipment
Issue Date: Oct-2024
Publisher: Nigerian Institution of Agricultural Engineers (NIAE) Conference Proceedings
Citation: Durojaiye, A.I., Olorunsogo, S.T., Adejumo, B.A., Babawuya, A., Muhamad, I.I. (2024/2025). Essential Mineral Elements Profile of Selected Foods commonly consumed in Nigeria necessary for Machine Learning operation. Proceedings of the 24th International Conference and 44th Annual General Meetings of the NIAE, pp. 522-535.
Series/Report no.: Conference Paper;
Abstract: Dietary mineral contents are essential nutritional elements with utmost importance which greatly contributes to both human and animal wellbeing to maintain sound health. It also assists plants to flourish adequately especially during growth. Deficiency in any of the essential micronutrients can result to life-threatening circumstances. In this study, essential elements (Ca, Fe, K, Na and Se) of two varieties of rice (NERICA 1 and FARO 59), two varieties of beans (pod borer resistant (PBR) and IT07K-318-33), plantain (Musa paradisiaca spp), Marabel irish potatoes (Solanum tuberosum L.), beef (Bos taurus) and chicken (Gallus gallus domesticus) commonly consumed in various forms were evaluatedto ensure seamless supervise machine learning operation for the calibration of a non-destructive equipment. Association of official analytical chemist (AOAC) standard experimental procedure was adopted and atomic absorption spectrophotometer (AAS) was used to obtain reference data of mineral contents for both raw and cooked samples of the selected food products. The experimental results revealed high values of 18.72mg/kg, 2.56mg/kg, 30.92mg/kg, 19.94mg/kg and 1.64mg/kg in Ca, Fe, K, Na and Se respectively across the food combinations. The result trend was observed with lowest spread of mineral values of 1.57mg/kg, 0.02mg/kg, 2.54mg/kg, 0.88mg/kg and 0.04mg/kg in the above trace elements sequence respectively. Generally, the results cascade within the daily acceptable limit for consumption as prescribed by food regulatory agencies and hence, fit and reliable for use as reference data for machine learning training for a non-destructive tool.
URI: http://irepo.futminna.edu.ng:8080/jspui/handle/123456789/31609
Appears in Collections:Agric. and Bioresources Engineering



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