A Neural Based Modeling Approach for Drying Kinetics Analysis of Mint Branches and Their Fractions (Leaves and Stems)

ISSN Print: 2160-0392
ISSN Online: 2160-0406
www.scirp.org/journal/aces
E-mail: aces@scirp.org

"A Neural Based Modeling Approach for Drying Kinetics Analysis of Mint Branches and Their Fractions (Leaves and Stems)"
written by Aline de Holanda Rosanova, Gustavo Dias Maia, Fábio Bentes Freire, Maria do Carmo Ferreira,
published by Advances in Chemical Engineering and Science, Vol.7 No.2, 2017

has been cited by the following article(s):

[1]	The Use of Digital Color Imaging and Machine Learning for the Evaluation of the Effects of Shade Drying and Open-Air Sun Drying on Mint Leaf Quality
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[1]	The Use of Digital Color Imaging and Machine Learning for the Evaluation of the Effects of Shade Drying and Open-Air Sun Drying on Mint Leaf Quality Applied Sciences, 2022 DOI:10.3390/app13010206

[2]	Drying of olive (Olea europaea L.) leaves on a conveyor belt for supercritical extraction of bioactive compounds: Mathematical modeling of drying/extraction operations and analysis of extracts Industrial Crops and Products, 2019 DOI:10.1016/j.indcrop.2019.05.004

[3]	Conveyor-belt drying of Eugenia uniflora L. leaves: Influence of drying conditions on the yield, composition, antioxidant activity and total phenolic content of supercritical CO2 extracts Food and Bioproducts Processing, 2019 DOI:10.1016/j.fbp.2019.05.005

[4]	Intensification of the convective drying process of Salvia officinalis: Modeling and optimization Food Science and Technology International, 2018 DOI:10.1177/1082013218759363

[5]	Análise da Secagem de Folhas e Hastes de Hortelã em Camada Fina Blucher Chemical Engineering Proceedings, 2017 DOI:10.5151/chemeng-cobeqic2017-257