Fourier-transform near-infrared spectroscopy as a fast screening tool for the verification of the geographical origin of grain maize (Zea mays L.)

Abstract

In this study, the ability of Fourier-transform near-infrared (FT-NIR) spectroscopy to trace back the geographical origin of grain maize used as feed material was investigated. 101 milled grain maize samples from five different countries (Spain, Ukraine, Slovakia, Peru and the USA) and three continents were analysed by FT-NIR spectroscopy. The spectra were used to develop a repeated cross-validated support vector machine classification, optimised in terms of pre-processing, model parameters and wavenumber selection. Spectral regions associated with proteins, starches and lipids were identified as suitable for determining the geographical origin of grain maize. A country-specific model composed of these selected regions achieved a mean accuracy rate of 95% for all samples. A similar overall result for country of origin classification was observed within a two-step approach starting with the continent level and then continuing with the country level within a continent. However, when differentiating between the geographical origins USA, Peru and Europe, all samples could be correctly classified. These results show the high potential of FT-NIR spectroscopy as a fast and cost-effective screening method for continent- and country of origin verification of grain maize samples in the context of feed authentication. • 101 milled grain maize samples were analysed by FT-NIR spectroscopy. • Spectral regions were identified that differ based on the geographical origin. • The geographical origin was verified using support vector machines. • The samples could be classified at the country of origin level with an accuracy of 95%. • No misclassification was observed on the continent level.