Identification of tomatoes with early decay using visible and near infrared hyperspectral imaging and image‐spectrum merging technique

Abstract

AbstractEffective detection of tomatoes with early decay still remains one of the major problems in the post‐harvest processing. The feasibility of using visible and near infrared (Vis–NIR) hyperspectral reflectance imaging coupled with image‐spectrum merging processing and analysis technology to detect early decay on tomatoes was observed. Mean normalization method was used to correct the uneven illumination caused by the large curvature change and the reflective characteristics of tomato surface. Principal component (PC) clustering analysis of spectra was used to find the optimal PC that was then used to distinguish sound and decayed tissues of tomatoes. Based on the selected PC, three characteristic wavelengths images at 596, 666, and 858 nm were obtained and the new combination image was calculated. The pseudo‐color image processing and RGB (red, green, and blue) transformation were applied to enhance the contrast between decayed and sound regions on the combined image. G component of RGB image and the corrected single‐wavelength image at 666 nm were used for segmentation of the decayed region and stem‐end on tomatoes, respectively. All samples including 120 decayed and 120 sound tomatoes were used to assess performance of the proposed algorithm. The classification results indicated that 100% of the decayed fruit and 97.5% of sound fruit were accurately identified by proposed algorithm. This study demonstrated that Vis–NIR hyperspectral imaging coupled with image‐spectrum merging processing technology could be a potential approach for detection of tomatoes with early decay.Practical applicationsDecay will not only affect the quality of tomato products, but also cause serious food safety problems. Detection of decayed tomatoes has become an universal attentive and urgent solving question for tomato processing industry. Currently, there was no effective and rapid technology to classify between decayed and sound tomatoes. In this study, a novel method was developed and the decayed tomatoes were successful identified using only three characteristic wavelengths images. This study can provide a useful reference for development of fast multispectral imaging system for decayed tomato detection in practical on‐line grading applications.