A Framework of Nutrient Analyser Model for Comparing Food Nutrients

• Published in: Current Nutrition and Food Science
• Main Author: Ng S.F.; Tukiman N.; Ismail A.; Khalid A.K.; Yunos N.M.; Norizan N.A.
• Format: Article
• Language: English
• Published: Bentham Science Publishers 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168586412&doi=10.2174%2f1573401319666230223162244&partnerID=40&md5=b5daaa18da9d9c7b3a4b4a8d7e7a0f69
• ISSN: 15734013
• DOI: 10.2174/1573401319666230223162244

Background: Consumers’ lack of nutritional awareness causes them to have little interest in reading and analysing nutritional information on food labels. Rigorous and scientific comparisons of the nutrient contents of commercial buns are rarely conducted in Malaysia. Objective: The first objective of this study is to classify nutrient contents in commercial buns into beneficial and non-beneficial nutrients. The second objective is to develop a nutrient analyser model framework to compare the nutrient contents for different types of commercial buns. Methods: The nutrient analyser model was developed based on the mathematical theory Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) and Shannon’s Entropy Model. The framework of the nutrient analyser model using the two theories was developed. Nutritional data taken from several commercial buns in Malaysia was applied to the model. Results: The results show that the model was able to identify the type of bun having the most beneficial nutrient contents and the least non-beneficial nutrient contents. Conclusion: The framework of the nutrient analyser model could serve as a reference for other researchers. The findings benefit the community and researchers as the results indirectly improve consumer awareness of food nutrients prioritizing good health. © 2023 Bentham Science Publishers.