Development of a Simple Algorithm for the Detection of Chilling Injury in Cucumbers from Visible/Near-Infrared Hyperspectral Imaging

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. A large spectral difference between good, smooth skins and chilling-injured skins occurred in the 700–850 nm visible/near-infrared (NIR) region. Both simple band ratio algorithms and principal component analysis (PCA) were attempted to discriminate the ROI spectra of good cucumber skins from those of chilling injured ones. Results revealed that both the dual-band ratio algorithm (R_811nm/R_756nm) and a PCA model from a narrow spectral region of 733–848 nm can detect chilling-injured skins with a success rate of over 90%. The results also suggested that chilling injury is relatively difficult to detect at the initial post-chilling RT stage, especially during the first 0–2 days in storage, due to insignificant manifestation of chilling induced symptoms.