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dc.contributor.authorThomas, B-
dc.contributor.authorPulissery, S K-
dc.contributor.authorSankalpa, K B-
dc.contributor.authorNandhu Lal, A M-
dc.contributor.authorWarrier, A S-
dc.contributor.authorMahanti, N K-
dc.contributor.authorKothakota, A-
dc.date.accessioned2024-04-04T12:28:33Z-
dc.date.available2024-04-04T12:28:33Z-
dc.date.issued2024-01-
dc.identifier.citationJournal of Food Science; 89(1):494-512en_US
dc.identifier.urihttps://ift.onlinelibrary.wiley.com/doi/10.1111/1750-3841.16875-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4813-
dc.description.abstractThe vacuum impregnation (VI) process parameters (vacuum pressure = 20–60 kPa; VI temperature = 35–55°C; concentration of the sucrose solution = 40–60 °Brix; and vacuum process time = 8–24 min) for pineapple rings were optimized based on the moisture content (MC), water loss (WL), solids gain (SG), yellowness index (YI), and total soluble solids (TSS) content of pineapple rings using response surface methodology (RSM). A relationship was developed between the process and response variables using RSM and artificial neural network (ANN) techniques. The effectiveness of VI was evaluated by comparing it with the osmotic dehydration (OD) technique. The optimum condition was found to be 31.782 kPa vacuum pressure, 50.441°C solution temperature, and 60 °Brix sucrose concentration for 20.068 min to attain maximum TSS, YI, SG, and WL, and minimum MC of pineapple rings. The R2 values of RSM models for all variables varied between 0.70 and 0.91, whereas mean square error values varied between 0.76 and 71.58 and for ANN models varied between 0.87–0.93 and 0.53–193.78, respectively.en_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.titleOptimization and modeling of vacuum impregnation of pineapple rings and comparison with osmotic dehydrationen_US
dc.typeArticleen_US
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