Submitted to: Applied Engineering in Agriculture
Publication Type: Peer reviewed journal
Publication Acceptance Date: 8/29/2005
Publication Date: 9/15/2005
Citation: Liu, Y., Chen, Y.R., Wang, C.Y., Chan, D.E., Kim, M.S. 2005. Development of hyperspectral imaging technique for the detection of chilling injury in cucumbers: Part I. Spectral Analysis. Applied Engineering in Agriculture. 22:101-111. Interpretive Summary: Exposure to low temperature environment during the storage and transportation process could induce chilling injury in cucumbers. 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 portions. 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. However, to select specific key wavelengths in spectral imaging processing, it is necessary to explore the fundamental spectral features of good and chilling injured cucumber skins. Here, we reported the determination of characteristic bands in visible and NIR region for chilling damaged cucumbers from region of interest (ROI) 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 were acquired before and during cold storage treatment as well as during subsequent room temperature (RT) storage 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 cold storage treatments at 0°C or 5 °C, showed a reduction in reflectance intensity during multi-day post-chilling periods of RT storage. Large spectral differences between good-smooth skins and chilling injured skins occurred in the 700-850 nm visible/NIR region. A number of data processing methods, including simple spectral band algorithms, second difference, and principal component analysis (PCA), were attempted to discriminate the ROI spectra of good cucumber skins from those of chilling injured skins. Results revealed that using either a dual-band ratio algorithm (R811 nm / R756 nm) or a PCA model from a narrow spectral region of 733-848 nm could detect chilling injured skins with a success rate of over 90%. The results also suggested that chilling injury was relatively difficult to detect at the stage of the first 0-2 days of post-chilling RT storage, due to insignificant manifestation of chilling induced symptoms.