Neuro-fuzzy modeling of pulp temperature in rapid cooling chamber

被引：0
|
作者：
Santos, italo Emannuel dos Anjos [1 ]
Okita, Willian Minoru [1 ]
Lourenconi, Dian [1 ]
Amorim, Magno do Nascimento [2 ]
de Sa Silva Lins, Ana Carolina [3 ]
Miranda, Isadora Benevides [4 ]
Turco, Silvia Helena Nogueira [1 ]
机构：
[1] Fed Univ Sao Francisco Valley UNIVASF, Collegiate Agr & Environm, Ave Antonio C Magalhaes,510 St Antonio, Juazeiro, BA, Brazil
[2] Univ Sao Paulo, Luiz De Queiroz Coll Agr, Ave Padua Dias, 11-Agron, Piracicaba, SP, Brazil
[3] Univ Fed Lavras, Agr Engn Dept, Lavras, MG, Brazil
[4] Univ Fed Campina Grande, Agr Engn Dept, R Aprigio Veloso,882 Univ, Campina Grande, PB, Brazil
来源：
JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE | 2024年
关键词：
Post-harvest losses; Cold chain; Neuro-fuzzy model; Mango; Rapid cooling chambers; INFERENCE SYSTEM; PERFORMANCE;
D O I：
10.1007/s13197-024-06109-7
中图分类号：
TS2 [食品工业];
学科分类号：
0832 ;
摘要：
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 (R-2 = 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.
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页数：6
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