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

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.

1. Application of electronic nose systems for assessing quality of medicinal and aromatic plant products: a review;Kiani;J. Appl. Res. Med. Aromat. Plants,2016

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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