Modeling of the lycopene extraction from tomato pulps

Food Chemistry

Volumn 190, Issue , 2016, Pages 968-973

  Dolatabadi, Zahra ^a   Elhami Rad, Amir Hossien ^a   Farzaneh, Vahid ^b   Akhlaghi Feizabad, Seyed Hashem ^a   Estiri, Seyed Hossein ^a   Bakhshabadi, Hamid ^c  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b UNIVERSITY OF ALGARVE   (Portugal)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

ANN; Enzyme treatment; Lycopene; Modeling

Indexed keywords

LEARNING ALGORITHMS; MEAN SQUARE ERROR; MODELS; SONICATION;

ANN; CORRELATION COEFFICIENT; ENZYME TREATMENT; LEVENBERG-MARQUARDT ALGORITHM; LYCOPENES; OPTIMAL NETWORKS; RADICAL SCAVENGING ACTIVITY; ROOT MEAN SQUARED ERRORS;

FEEDFORWARD NEURAL NETWORKS;

LYCOPENE; POLYGALACTURONASE; CAROTENOID;

ARTICLE; CORRELATION COEFFICIENT; EXTRACTION; LEARNING ALGORITHM; MEASUREMENT ERROR; MODEL; NONHUMAN; TOMATO; VALIDITY; ALGORITHM; ARTIFICIAL NEURAL NETWORK; CHEMISTRY; ISOLATION AND PURIFICATION;

LYCOPERSICON ESCULENTUM;

ALGORITHMS; CAROTENOIDS; LYCOPERSICON ESCULENTUM; NEURAL NETWORKS (COMPUTER);

EID: 84933073596     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2015.06.069     Document Type: Article

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