Submitted to: Journal of Applied Spectroscopy
Publication Type: Peer reviewed journal
Publication Acceptance Date: 9/24/2004
Publication Date: 1/3/2005
Citation: Liu, Y., Chen, Y.R., Wang, C.Y., Chan, D.E., Kim, M.S. 2005. Development of simple algorithm for the detection of chilling injury in cucumbers from visible/near infrared hyperspectral imaging. Applied Spectroscopy. 59:136-143. Interpretive Summary: Cucumbers are usually kept at low temperatures during the storage and transportation process for safety and quality maintenance. However, they are sensitive to chilling temperatures, and the exposure to low temperature environment could induce chilling injury symptoms, including pitting, discoloration, internal browning, and decay. Symptoms of chilling injury develop very rapidly and might become sites for further fungal decay and bacterial infection after a few days at warmer temperatures. Such bacterial pathogens could be transmitted to humans by consumption of uncooked or mishandled cucumbers. Hence, one of the greatest concerns in vegetable industry is to detect chilling injury, ultimately providing the safety and quality guaranteed cucumber products for the consumers. Existing method in cucumber safety / quality assessment, such as human visual inspection, can provide reliable information about chilling injured spots. However, it is time consuming and unsuitable for on-line application. The development of fast, non-destructive, accurate, and on-line / at-line techniques is desired. Hyperspectral imaging spectroscopy could form the basis for such a technique due to the speed, non-invasive, and large sampling area. In this study, we reported the determination of characteristic bands in visible and NIR region for chilling damaged cucumbers from hyperspectral imaging spectra, and also the development of a number of classification methods for the discrimination of good cucumber skins from those of chilling injured ones. The results revealed that both dual-band ratio algorithm (R811 nm / R756 nm ) and principal component analysis (PCA) model from a narrow 733-848 nm spectral region can detect chilling injured skins with a great success of over 90%. This information is useful to vegetable packers, retailers, and researchers who are interested in applying both visible/NIR and imaging spectroscopy based safety/quality grading or classifying.
Technical Abstract: Hyperspectral images of cucumbers under a variety of conditions were acquired to explore the potential for the detection of chilling induced damage in whole cucumbers. Region of interest (ROI) spectral features of chilling-injured areas, resulting from chilling treatment at 0 °C, showed the reduction of reflectance intensity over the period at post-chilling room temperature (RT) storage. Large spectral variations between good-smooth skins and chilling injured skins occurred in the 700-850 nm visible/NIR region. Both simple algorithms and principal component analysis (PCA) were attempted to discriminate the ROI spectra of good cucumber skins from those of chilling injured ones. Comparison of identification results revealed that both dual-band ratio algorithm (R811 nm / R756 nm ) and PCA model from a narrow 733-848 nm spectral region can detect chilling injured skins with a success rate of over 90%. The results also suggested that chilling injury is relatively difficult to be detected at the initial post-chilling RT stage, especially during the first 0-2 days in storage, due to insignificant manifestation of chilling induced symptoms.