|Title:||Detection of deltamethrin in cabbages using visible shortwave near-infrared spectroscopy||Authors:||Ishkandar C.D.M
|Keywords:||Cabbages;GC-ECD;MRL;Pesticide Residues;Spectroscopy;deltamethrin;dichlorvos;glyphosate;methanol;mycotoxin;pesticide residue;pyrethroid;sodium;agronomy;Article;cabbage;chlorophyll content;climate change;environmental factor;exploratory factor analysis;Fusarium;gas chromatography;infrared spectroscopy;kiwifruit;least square analysis;limit of detection;limit of quantitation;maize;mass spectrometry;measurement accuracy;near infrared spectroscopy;principal component analysis;signal noise ratio;support vector machine;validation process;water pollution||Issue Date:||2021||Journal Volume:||5||Journal Issue:||3||Start page/Pages:||273-280||Source:||Food Research||Abstract:||
Pesticides have long been used in the cabbage industry to control pest infestation. This study investigated the potential application of low-cost and portable visible shortwave near-infrared spectroscopy for the detection of deltamethrin residue in cabbages. A total of sixty organic cabbage samples were used. The sample was divided into four batches, three batches were sprayed with deltamethrin pesticide whereas the remaining batch was not sprayed (control sample). The first three batches of the cabbages were sprayed with the pesticide at three different concentrations, namely low, medium and high with the values of 0.08, 0.11 and 0.14% volume/volume (v/v), respectively. Spectral data of the cabbage samples were collected using visible shortwave near-infrared (VSNIR) spectrometer with wavelengths range between 200 and 1100 nm. Gas chromatography-electron capture detector (GC-ECD) was used to determine the concentration of deltamethrin residues in the cabbages. Partial least square (PLS) regression method was adopted to investigate the relationship between the spectral data and deltamethrin concentration values. The calibration model produced the values of coefficient of determination (R2) and the root mean square error of calibration (RMSEC) of 0.98 and 0.02, respectively. For the prediction model, the values of R2 and the root mean square error of prediction (RMSEP) were 0.94 and 0.04, respectively. These results demonstrated that the proposed spectroscopic measurement is a promising technique for the detection of pesticide at different concentrations in cabbage samples. ? 2021 The Authors. Published by Rynnye Lyan Resources.
|Appears in Collections:||生物機電工程學系|
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