Paper
21 May 2015 Pesticide residue quantification analysis by hyperspectral imaging sensors
Yuan-Hsun Liao, Wei-Sheng Lo, Horng-Yuh Guo, Ching-Hua Kao, Tau-Meu Chou, Junne-Jih Chen, Chia-Hsien Wen, Chinsu Lin, Hsian-Min Chen, Yen-Chieh Ouyang, Chao-Cheng Wu, Shih-Yu Chen, Chein-I Chang
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Abstract
Pesticide residue detection in agriculture crops is a challenging issue and is even more difficult to quantify pesticide residue resident in agriculture produces and fruits. This paper conducts a series of base-line experiments which are particularly designed for three specific pesticides commonly used in Taiwan. The materials used for experiments are single leaves of vegetable produces which are being contaminated by various amount of concentration of pesticides. Two sensors are used to collected data. One is Fourier Transform Infrared (FTIR) spectroscopy. The other is a hyperspectral sensor, called Geophysical and Environmental Research (GER) 2600 spectroradiometer which is a batteryoperated field portable spectroradiometer with full real-time data acquisition from 350 nm to 2500 nm. In order to quantify data with different levels of pesticide residue concentration, several measures for spectral discrimination are developed. Mores specifically, new measures for calculating relative power between two sensors are particularly designed to be able to evaluate effectiveness of each of sensors in quantifying the used pesticide residues. The experimental results show that the GER is a better sensor than FTIR in the sense of pesticide residue quantification.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuan-Hsun Liao, Wei-Sheng Lo, Horng-Yuh Guo, Ching-Hua Kao, Tau-Meu Chou, Junne-Jih Chen, Chia-Hsien Wen, Chinsu Lin, Hsian-Min Chen, Yen-Chieh Ouyang, Chao-Cheng Wu, Shih-Yu Chen, and Chein-I Chang "Pesticide residue quantification analysis by hyperspectral imaging sensors", Proc. SPIE 9501, Satellite Data Compression, Communications, and Processing XI, 95010B (21 May 2015); https://doi.org/10.1117/12.2176800
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KEYWORDS
FT-IR spectroscopy

Sensors

Hyperspectral imaging

Agriculture

Image sensors

Lithium

Spectroscopy

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