source: Research in Agricultural Engineering
Abstract
The aim of the present study is the development of an electronic nose system prototype for the classification of Gyrinops versteegii agarwood. The prototype consists of three gas sensors, i.e., TGS822, TGS2620, and TGS2610. The data acquisition and quality classification of the nose system are controlled by the Artificial Neural Network backpropagation algorithm in the Arduino Mega2650 microcontroller module. The testing result shows that an electronic nose can distinguish the quality of Gyrinops versteegii agarwood. The good-quality agarwood has an output of [1 -1], while the poor-quality agarwood has an output of [-1 1].
Concepts :
Cultural Heritage Materials Analysis
Identification and Quantification in Food
Wood and Agarwood Research
article
cite 7
Year 2020
source Research in Agricultural Engineering