Estimation of sweet cherry antioxidant activity and anthocyanin content during ripening by artificial neural network-assisted image processing technique

International Journal of Food Science and Technology

Volumn 48, Issue 4, 2013, Pages 735-741

  Taghadomi Saberi, Saeedeh ^a   Omid, Mahmoud ^a   Emam Djomeh, Zahra ^a   Ahmadi, Hojjat ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Anthocyanin content; Antioxidant activity; Artificial neural network; Cherry fruit; Image processing; Ripening

Indexed keywords

IMAGE PROCESSING; MATLAB; MEAN SQUARE ERROR; NETWORK ARCHITECTURE; NETWORK LAYERS; NEURAL NETWORKS;

2 ,2-DIPHENYL-1-PICRYLHYDRAZYL; ANTHOCYANIN CONTENT; ANTI-OXIDANT ACTIVITIES; CORRELATION COEFFICIENT; FLUORESCENT LIGHT; HIDDEN LAYER NETWORKS; IMAGE PROCESSING TECHNIQUE; RIPENING;

ANTHOCYANINS;

PRUNUS AVIUM;

EID: 84975879158     PISSN: 09505423     EISSN: 13652621     Source Type: Journal    
DOI: 10.1111/ijfs.12021     Document Type: Article

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