Imaging techniques for the detection of stored product pests

Stored grains are subject to deterioration and losses through various factors, but mainly insects and fungi. Various techniques are employed to detect stored product pests; however, there is an urgent need for an industrial-scale on-line detection technique. Near-infrared hyperspectroscopic imaging and soft X-rays have shown the potential for real-time application. These techniques are particularly effective for detecting internal infestations of stored grains. The digital images of the scanned objects are analyzed for various spectral and image features using statistical techniques such as complex multivariate tools. Classification accuracies as high as 80-100 % have been achieved for various pest and grain combinations. Dual-energy X-rays have been shown to detect the concealed eggs of stored product insect pests. The main threats to stored cereals come from Aspergillus spp., Penicillium spp., and Fusarium spp., which may produce mycotoxins. These imaging techniques have shown good results in the detection of fungal infections of stored grain.