NIR hyperspectral imaging spectroscopy and chemometrics for the detection of undesirable substances in food and feed

Food and feed safety as well as quality control analyses are often carried out using reference methods that have limitations in terms of adequation for the optimum implementation at the different steps of the food/feed chain and for the control of the end-products. Recent developments in analytical instrumentation and data processing methods have led to increased use of spectroscopic techniques, being proposed to establish alternative methods replacing the reference techniques. In recent years, these improvements have included the development of NIR hyperspectral imaging methods combined with appropriated chemometric tools. The research aim of this paper is to show that combining NIR hyperspectral imaging spectroscopic technique with chemometrics can greatly improve food and feed safety and quality control. For this purpose, two case studies were conducted using two different NIR hyperspectral imaging systems combined with chemometric tools and spectral rules applied in a dichotomist way. The first study focused on the detection of impurities in cereals in order to integrate a complete methodology into an automatic cereal selection or production chain. The second study focused in the contamination of plants by pathogens and showed the potential of this combination for detecting and quantifying cyst nematodes in sugar beet roots.