Near-Infrared (NIR) hyperspectral imaging: theory and applications to detect fungal infection and mycotoxin contamination in food products

Abstract

Near-Infrared hyperspectral imaging system is a promising technique to detect various quality parameters associated with cereals and oilseeds. NIR hyperspectral imaging system can collect both spectral and spatial information of any given object and it can detect chemical constituents of food products, therefore it is also called chemical imaging. The image data obtained from hyperspectral imaging system are in the hypercube form, two spatial dimensions and the third spectral dimension. The image data in the hypercube form cannot be directly used for identification and classification, so the three dimensional data are transformed into two dimensional data using automatic thresholding, labelling and reshaping. The transformed two dimensional data subjected to principal component analysis provide significant wavelengths. Statistical features and histogram features extracted from the significant wavelengths are used in the statistical classification models. Fungal infection and mycotoxin contamination in food products disturb the original chemical composition of food products. The NIR hyperspectral imaging or chemical imaging has the potential to detect the chemical changes occurring in the sample. The NIR hyperspectral imaging system has the potential to detect fungal infection and mycotoxin contamination in food products.