Application of Near-Infrared Hyperspectral Imaging for Detection of External Insect Infestations on Jujube Fruit

Abstract

A hyperspectral imaging system has been built for detecting external insect damage and acquiring reflectance images from jujubes in the near-infrared region of 900-1700 nm. Spectral information was extracted from each jujube, and six optimal wavelengths (987, 1028, 1160, 1231, 1285, and 1464 nm) were obtained using principal component analysis. The first principal component images (PC-1) using the selected six wavelengths were obtained for further image processing. The detection algorithm was then developed based on principal component analysis and two-band ratio (R1160/R1464) coupled with image subtraction algorithm (R1160-R1464). An identification accuracy of 93.1% for insect-infested jujubes and 100% classification rate for the intact ones were achieved. The results of this research demonstrated that it is feasible to discriminate insect-infested jujubes from intact jujubes using the near-infrared hyperspectral imaging technology.