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Development of a Hyperspectral Imaging System for Online Quality Inspection of Pickling Cucumbers

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Food Processing Automation Conference Proceedings, 28-29 June 2008, Providence, Rhode Island  701P0508cd.(doi:10.13031/2013.24556)
Authors:   Renfu Lu, Diwan P Ariana
Keywords:   Postharvest, Grading, Hyperspectral Imaging, Sensing, Vegetable, Cucumbers, Quality, Defect

This paper reports on the development of a hyperspectral imaging prototype for evaluation of external and internal quality of pickling cucumbers. The prototype consisted of a two-lane round belt conveyor, two illumination sources (one for reflectance and one for transmittance), and a hyperspectral imaging unit. It had a novel feature of simultaneous imaging under reflectance mode covering the visible region of 400-675 nm and transmittance mode for 675-1000 nm, coupled with real-time, continuous calibration of reflectance and transmittance images for each cucumber using reference standards installed on the conveyor. Reflectance information was used for evaluating the external characteristics of cucumbers (i.e., skin color), transmittance for internal defect detection (hollow center), and the combined reflectance and transmittance for predicting flesh firmness. The prototype was tested on ‘Journey’ pickling cucumbers harvested in 2006 and 2007 for predicting skin and flesh color, flesh firmness, and internal defect. Hyperspectral images were processed to extract mean spectra for individual cucumbers, and partial least squares analysis was performed to predict flesh firmness, skin and flesh color, and the presence of internal defect. The prototype performed relatively well in predicting skin color with the coefficient of determination of 0.76 and 0.75 for chroma and hue respectively; however, it had poor prediction of flesh color and firmness. Transmittance data in the spectral region of 675-1000 nm provided excellent detection of internal defect for the pickling cucumbers, with the detection accuracy greater than 90%. The hyperspectral imaging technique would be useful for online inspection of surface color and internal defect on picking cucumbers.

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