Gas sensor-based machine learning approaches for characterizing tarragon aroma and essential oil under various drying conditions-Reference-Cited by-同舟云学术

Gas sensor-based machine learning approaches for characterizing tarragon aroma and essential oil under various drying conditions

Published:2024-01 Issue: Volume:365 Page:114827
ISSN:0924-4247
Container-title:Sensors and Actuators A: Physical
language:en
Short-container-title:Sensors and Actuators A: Physical

Author:

Karami Hamed,Karami Chemeh Saeed,Azizi Vahid,Sharifnasab Hooman,Ramos Jose,Kamruzzaman Mohammed

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Metals and Alloys,Surfaces, Coatings and Films,Condensed Matter Physics,Instrumentation,Electronic, Optical and Magnetic Materials

Reference46 articles.

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2. Thin layer drying models and characteristics of scent leaves (Ocimum gratissimum) and lemon basil leaves (Ocimum africanum);Mbegbu;Heliyon,2021

3. Using PSO and GWO techniques for prediction some drying properties of tarragon (Artemisia dracunculus L;Karami;J. Food Process Eng.,2018

4. Kinetics mass transfer and modeling of tarragon drying (Artemisia dracunculus L.);Karami;Iran. J. Med. Aromat. Plants Res.,2018

5. Effect of drying temperature and air velocity on the essential oil content of Mentha aquatica L;Karami;J. Essent. Oil Bear. Plants,2017

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