Artificial neural network modeling for temperature and moisture content prediction in tomato slices undergoing microwave-vacuum drying

Journal of Food Science

Volumn 72, Issue 1, 2007, Pages E042-E047

  Poonnoy, Poonpat ^a   Tansakul, Ampawan ^a   Chinnan, Manjeet ^b  

^a KING MONGKUT'S UNIVERSITY OF TECHNOLOGY THONBURI   (Thailand)

^b UNIVERSITY OF GEORGIA   (United States)

Author keywords

Drying; Microwave vacuum; Modeling; Neural network; Tomato

Indexed keywords

LYCOPERSICON ESCULENTUM;

WATER;

ARTICLE; ARTIFICIAL NEURAL NETWORK; FOOD HANDLING; FOOD PRESERVATION; KINETICS; METABOLISM; METHODOLOGY; MICROWAVE RADIATION; PHYSIOLOGY; PRESSURE; RADIATION EXPOSURE; RADIATION RESPONSE; TEMPERATURE; TIME; TOMATO; VACUUM;

DOSE-RESPONSE RELATIONSHIP, RADIATION; FOOD PRESERVATION; FOOD TECHNOLOGY; KINETICS; LYCOPERSICON ESCULENTUM; MICROWAVES; NEURAL NETWORKS (COMPUTER); PRESSURE; TEMPERATURE; TIME FACTORS; VACUUM; WATER;

EID: 33846967062     PISSN: 00221147     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1750-3841.2006.00220.x     Document Type: Article

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