Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractNanomaterial Gas Sensors for Online Monitoring System of Fruit Jams    Next AbstractBreba Fruits Characterization from Four Varieties (Ficus carica L.) with Important Commercial Interest in Spain »

Sensors (Basel)


Title:"Internet of Food (IoF), Tailor-Made Metal Oxide Gas Sensors to Support Tea Supply Chain"
Author(s):Nunez-Carmona E; Abbatangelo M; Sberveglieri V;
Address:"CNR-IBBR, Institute of Bioscience and Bioresources, Via Madonna del Piano, 10, 50019 Sesto Fiorentino, FI, Italy. Nano Sensor Systems, NASYS Spin-Off University of Brescia, Brescia, Via Camillo Brozzoni, 9, 25125 Brescia, BS, Italy"
Journal Title:Sensors (Basel)
Year:2021
Volume:20210622
Issue:13
Page Number: -
DOI: 10.3390/s21134266
ISSN/ISBN:1424-8220 (Electronic) 1424-8220 (Linking)
Abstract:"Tea is the second most consumed beverage, and its aroma, determined by volatile compounds (VOCs) present in leaves or developed during the processing stages, has a great influence on the final quality. The goal of this study is to determine the volatilome of different types of tea to provide a competitive tool in terms of time and costs to recognize and enhance the quality of the product in the food chain. Analyzed samples are representative of the three major types of tea: black, green, and white. VOCs were studied in parallel with different technologies and methods: gas chromatography coupled with mass spectrometer and solid phase microextraction (SPME-GC-MS) and a device called small sensor system, (S3). S3 is made up of tailor-made metal oxide gas sensors, whose operating principle is based on the variation of sensor resistance based on volatiloma exposure. The data obtained were processed through multivariate statistics, showing the full file of the pre-established aim. From the results obtained, it is understood how supportive an innovative technology can be, remotely controllable supported by machine learning (IoF), aimed in the future at increasing food safety along the entire production chain, as an early warning system for possible microbiological or chemical contamination"
Keywords:Internet Odorants/analysis Oxides Solid Phase Microextraction Tea *Volatile Organic Compounds/analysis Gc-ms MOX sensors S3 volatiloma;
Notes:"MedlineNunez-Carmona, Estefania Abbatangelo, Marco Sberveglieri, Veronica eng Switzerland 2021/07/03 Sensors (Basel). 2021 Jun 22; 21(13):4266. doi: 10.3390/s21134266"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 04-12-2024