Prediction of the Physicochemical Properties of Spray-Dried Black Mulberry (Morus nigra) Juice using Artificial Neural Networks

Food and Bioprocess Technology

Volumn 6, Issue 2, 2013, Pages 585-590

  Fazaeli, Mahboubeh ^a   Emam Djomeh, Zahra ^a   Omid, Mahmoud ^a   Kalbasi Ashtari, Ahmad ^a  

^a UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Artificial neural networks; Black mulberry; Color change; Spray drying; Total anthocyanin content; Yield

Indexed keywords

ANTHOCYANINS; BACKPROPAGATION; COLORIMETRY; COMPRESSED AIR; FORECASTING; MEAN SQUARE ERROR; MULTILAYER NEURAL NETWORKS; NEURAL NETWORKS; PHYSICOCHEMICAL PROPERTIES; PLANTS (BOTANY); SPRAY DRYING;

ANTI-OXIDANT ACTIVITIES; BLACK MULBERRIES; COEFFICIENT OF DETERMINATION; COLOR CHANGES; MULTI-LAYERED PERCEPTRON; ROOT MEAN SQUARE ERRORS; TOTAL ANTHOCYANIN CONTENTS; YIELD;

NETWORK LAYERS;

ACACIA SENEGAL; MORUS NIGRA;

EID: 84975861192     PISSN: 19355130     EISSN: 19355149     Source Type: Journal    
DOI: 10.1007/s11947-011-0648-x     Document Type: Article

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