Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments

Food Chemistry

Volumn 168, Issue , 2015, Pages 454-459

  Guiné, Raquel P F ^a   Barroca, Maria João ^b   Gonçalves, Fernando J ^a   Alves, Mariana ^a   Oliveira, Solange ^a   Mendes, Mateus ^b  

^a POLYTECHNIC INSTITUTE OF VISEU   (Portugal)

^b POLYTECHNIC INSTITUTE OF COIMBRA   (Portugal)

Author keywords

Antioxidant activity; Banana; Drying; Neural network; Phenolic compounds

Indexed keywords

DRYING; FRUITS; NEURAL NETWORKS;

ACETONE/WATER SOLUTIONS; ANTI-OXIDANT ACTIVITIES; BANANA; DRYING TREATMENT; INPUT VARIABLES; OUTPUT VARIABLES; PHENOLIC COMPOUNDS; PHENOLIC CONTENT;

PHENOLS; DRYING;

PHENOL DERIVATIVE; ACETONE; FLAVONOID; METHANOL; WATER; ANTIOXIDANT; PLANT EXTRACT;

ANTIOXIDANT ACTIVITY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BANANA; CULTIVAR; FREEZE DRYING; MUSA; MUSA CAVENDISHII; MUSA NANA; NONHUMAN; DRYING; FOOD PROCESSING; NERVE CELL; NERVE CELL NETWORK; TEMPERATURE; CHEMISTRY; DESICCATION; PROCEDURES;

ANTIOXIDANTS; DESICCATION; MUSA; NEURAL NETWORKS (COMPUTER); PHENOLS; PLANT EXTRACTS;

EID: 84907325165     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2014.07.094     Document Type: Article

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