Ítalo Emannuel dos Anjos Santos, Willian Minoru Okita, Dian Lourençoni, Magno do Nascimento Amorim, Ana Carolina de Sá Silva Lins, Isadora Benevides Miranda, Sílvia Helena Nogueira Turco
{"title":"Neuro-fuzzy modeling of pulp temperature in rapid cooling chamber","authors":"Ítalo Emannuel dos Anjos Santos, Willian Minoru Okita, Dian Lourençoni, Magno do Nascimento Amorim, Ana Carolina de Sá Silva Lins, Isadora Benevides Miranda, Sílvia Helena Nogueira Turco","doi":"10.1007/s13197-024-06109-7","DOIUrl":null,"url":null,"abstract":"<div><p>Post-harvest fruit losses in Brazil can reach up to 40%, with inadequacies in the cold chain being one of the primary causes. This study proposes the development of a neuro-fuzzy model to predict the pulp temperature of mangoes in rapid cooling chambers, aiming to enhance the efficiency of the cooling process. The experiment was conducted on a commercial mango farm in Petrolina, Pernambuco. The results demonstrated that the neuro-fuzzy model can accurately estimate the pulp temperature of mangoes (R² = 0.98), thereby aiding decision-making related to optimal rapid cooling times. Implementing this model could significantly reduce post-harvest losses and help ensure the quality of the final product.</p></div>","PeriodicalId":632,"journal":{"name":"Journal of Food Science and Technology","volume":"62 6","pages":"1110 - 1115"},"PeriodicalIF":2.7010,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Science and Technology","FirstCategoryId":"1","ListUrlMain":"https://link.springer.com/article/10.1007/s13197-024-06109-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Post-harvest fruit losses in Brazil can reach up to 40%, with inadequacies in the cold chain being one of the primary causes. This study proposes the development of a neuro-fuzzy model to predict the pulp temperature of mangoes in rapid cooling chambers, aiming to enhance the efficiency of the cooling process. The experiment was conducted on a commercial mango farm in Petrolina, Pernambuco. The results demonstrated that the neuro-fuzzy model can accurately estimate the pulp temperature of mangoes (R² = 0.98), thereby aiding decision-making related to optimal rapid cooling times. Implementing this model could significantly reduce post-harvest losses and help ensure the quality of the final product.
期刊介绍:
The Journal of Food Science and Technology (JFST) is the official publication of the Association of Food Scientists and Technologists of India (AFSTI). This monthly publishes peer-reviewed research papers and reviews in all branches of science, technology, packaging and engineering of foods and food products. Special emphasis is given to fundamental and applied research findings that have potential for enhancing product quality, extend shelf life of fresh and processed food products and improve process efficiency. Critical reviews on new perspectives in food handling and processing, innovative and emerging technologies and trends and future research in food products and food industry byproducts are also welcome. The journal also publishes book reviews relevant to all aspects of food science, technology and engineering.