Preprint Communication Version 1 Preserved in Portico This version is not peer-reviewed

Developing a Multi-Spectral Nir Led-Based Instrument for the Detection of Pesticide Residues Containing Chlorpyrifos-Methyl in Rough, Brown, And Milled Rice

Fatima R. Macadaeg
* ,
Paul R. Armstrong
* ORCID logo ,
Elizabeth B. Maghirang
* ,
Erin D. Scully
* ORCID logo ,
Daniel L. Brabec
,
Frank H. Arthur
,
Arlene D. Adviento-Borbe
,
Kevin F. Yaptenco
,
Delfin C. Suministrado
Version 1 : Received: 3 May 2024 / Approved: 3 May 2024 / Online: 3 May 2024 (10:30:24 CEST)

How to cite: Macadaeg, F. R.; Armstrong, P. R.; Maghirang, E. B.; Scully, E. D.; Brabec, D. L.; Arthur, F. H.; Adviento-Borbe, A. D.; Yaptenco, K. F.; Suministrado, D. C. Developing a Multi-Spectral Nir Led-Based Instrument for the Detection of Pesticide Residues Containing Chlorpyrifos-Methyl in Rough, Brown, And Milled Rice. Preprints 2024, 2024050188. https://doi.org/10.20944/preprints202405.0188.v1 Macadaeg, F. R.; Armstrong, P. R.; Maghirang, E. B.; Scully, E. D.; Brabec, D. L.; Arthur, F. H.; Adviento-Borbe, A. D.; Yaptenco, K. F.; Suministrado, D. C. Developing a Multi-Spectral Nir Led-Based Instrument for the Detection of Pesticide Residues Containing Chlorpyrifos-Methyl in Rough, Brown, And Milled Rice. Preprints 2024, 2024050188. https://doi.org/10.20944/preprints202405.0188.v1

Abstract

A recent study showed the potential of DA Perten 7200 NIR Spectrometer in detecting chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice. However, this instrument is still lab-based and generally suited for point-of-sale testing in many countries. To provide a field deployable version of this technique, an existing light emitting diode (LED)-based instrument which provide discrete NIR wavelength illumination and reflectance spectra over the range of 850-1550 nm was tested. Spectra were collected from rough, brown, and milled rice at different pesticide concentrations and analysed for quantitative and qualitative measurement using partial least squares regression (PLS) and discriminant analysis (DA). Simulations for LED-based instruments were also evaluated using segments of spectra from the DA7200 to represent LED illumination. For the simulation of the existing LED-based instrument (LEDPrototype1) using their wavelengths range yielded 70.4% to 100% correct classification. Simulation of a second LED instrument, LEDPrototype2, with spectral segments selected based on significant wavelength regions from PLS regressions coefficients obtained from the DA7200 showed improved performance with R2 of 0.59 to 0.82 and correct classifications of 71.3 to 100%. An actual LED based instrument with this capability could provide a quick screening tool to determine if MRLs are exceeded.

Keywords

chlorpyrifos-methyl pesticide residue (CMPR); detection; LED; NIR; organophosphates; pesticide residue; rice

Subject

Engineering, Other

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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