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Proceedings Paper

Optical instrument development for detection of pesticide residue in apple surface
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Paper Abstract

Apple is the world largest produced and consumed fruit item. At the same time, apple ranks number one among the fruit item contaminated with pesticide. This research focuses on development of laboratory based self-developed software and hardware for detection of commercially available organophosphorous pesticide (chlorpyrifos) in apple surface. A laser light source of 785nm was used to excite the sample, and Raman spectroscopy assembled with CCD camera was used for optical data acquisition. A hardware system was designed and fabricated to clamp and rotate apple sample of varying size maintaining constant working distance between optical probe and sample surface. Graphical Users Interface (GUI) based on LabView platform was developed to control the hardware system. The GUI was used to control the Raman system including CCD temperature, exposure time, track height and track centre, data acquisition, data processing and result prediction. Different concentrations of commercially available 48% chlorpyrifos pesticide solutions were prepared and gently placed in apple surface and dried. Raman spectral data at different points from same apple along the equatorial region were then acquired. The results show that prominent peaks at 341cm-1, 632cm-1 and 680 cm-1 represent the pesticide residue. The laboratory based experiment was able to detect pesticide solution of 20ppm within 3 seconds. A linear relation between Raman intensity and pesticide residue was developed with accuracy of 97.8%. The result of the research is promising and thus is a milestone for developing industrially desired real time, non-invasive pesticide residue detection technology in future.

Paper Details

Date Published: 29 May 2013
PDF: 8 pages
Proc. SPIE 8721, Sensing for Agriculture and Food Quality and Safety V, 87210M (29 May 2013); doi: 10.1117/12.2015862
Show Author Affiliations
Sagar Dhakal, China Agricultural Univ. (China)
Yongyu Li, China Agricultural Univ. (China)
Yankun Peng, China Agricultural Univ. (China)
Kuanglin Chao, Agricultural Research Service (United States)
Jianwei Qin, Agricultural Research Service (United States)

Published in SPIE Proceedings Vol. 8721:
Sensing for Agriculture and Food Quality and Safety V
Moon S. Kim; Shu-I Tu; Kuanglin Chao, Editor(s)

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