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 AbstractBiogenic VOCs Emission Profiles Associated with Plant-Pest Interaction for Phenotyping Applications    Next Abstract"Courtship and mating by the sandfly Phlebotomus duboscqi, a vector of zoonotic cutaneous leishmaniasis in the Afrotropical region" »

HardwareX


Title:Development of a semi-automated volatile organic compounds (VOCs) sampling system for field asymmetric ion mobility spectrometry (FAIMS) analysis
Author(s):Valencia-Ortiz M; Sankaran S;
Address:"Department of Biological System Engineering, Washington State University, Pullman, WA 99164, USA"
Journal Title:HardwareX
Year:2022
Volume:20220810
Issue:
Page Number:e00344 -
DOI: 10.1016/j.ohx.2022.e00344
ISSN/ISBN:2468-0672 (Electronic) 2468-0672 (Linking)
Abstract:"In recent years, applications of volatile organic compounds (VOCs) sensing technologies such as field asymmetric-waveform ion-mobility spectrometry (FAIMS) system in agriculture have accelerated. FAIMS system for VOCs sensing is attractive as it offers high sensitivity, selectivity, real-time monitoring, and portability. However, the development of a robust instrumentation system is needed for precise sampling, high accumulation of VOCs, and careful handling of samples. In this study, we developed a simple semi-automated VOC sampling (SAVS) system using a Raspberry Pi microcontroller, flowmeters, electromechanical solenoid, and cellphone-based app to control cleaning and sampling loops. The system was compared with customized headspace sampling apparatus (CHSA) and validated with a biomarker (acetone) identified to be associated with potato rot development during postharvest storage. The standard error within ion current data across different compensation voltage was lower using the SAVS system than the CHSA. In addition, the maximum peak values across scans displayed a high coefficient of variation using the CHSA (16.23%) than the SAVS system (4.51%). Future work will involve improving system efficiency by adapting multiple sample units, system miniaturization, and automating the flowmeter operation. Such automation is critical to characterize VOCs precisely and automatically across several samples for multiple applications such as pathogen detection, evaluation of crop responses, etc"
Keywords:Automated control Biological samples Flow meter Raspberry Pi;
Notes:"PubMed-not-MEDLINEValencia-Ortiz, Milton Sankaran, Sindhuja eng England 2022/08/30 HardwareX. 2022 Aug 10; 12:e00344. doi: 10.1016/j.ohx.2022.e00344. eCollection 2022 Oct"

 
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 21-11-2024