Ultrasound assisted extraction of phenolic compounds from P. lentiscus L. leaves: Comparative study of artificial neural network (ANN) versus degree of experiment for prediction ability of phenolic compounds recovery-Reference-Cited by-同舟云学术

Ultrasound assisted extraction of phenolic compounds from P. lentiscus L. leaves: Comparative study of artificial neural network (ANN) versus degree of experiment for prediction ability of phenolic compounds recovery

Published:2015-12 Issue: Volume:77 Page:251-261
ISSN:0926-6690
Container-title:Industrial Crops and Products
language:en
Short-container-title:Industrial Crops and Products

Author:

Dahmoune Farid,Remini Hocine,Dairi Sofiane,Aoun Omar,Moussi Kamal,Bouaoudia-Madi Nadia,Adjeroud Nawel,Kadri Nabil,Lefsih Khalef,Boughani Lhadi,Mouni Lotfi,Nayak Balunkeswar,Madani Khodir

Publisher

Elsevier BV

Subject

Agronomy and Crop Science

Reference32 articles.

1. Evaluation of total antioxidant potential of Pistacia lentiscus var. chia leaves extracts using UHPLC–HRMS;Bampouli;J. Food Eng.,2014

2. Green extraction of natural products: concept and principles;Chemat;Int. J. Mol. Sci.,2012

3. Optimization of total phenolic content extracted from Garcinia mangostana Linn hull using response surface methodology versus artificial neural network;Cheok;Ind. Crops Prod.,2012

4. Valorization of Citrus limon residues for the recovery of antioxidants: evaluation and optimization of microwave and ultrasound application to solvent extraction;Dahmoune;Ind. Crops Prod.,2013

5. Optimization of ultrasound-assisted extraction of phenolic compounds from Citrus sinensis L peels using response surface methodology;Dahmoune;Chem. Eng.,2014

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