classification of grain maize (zea mays l.) from different geographical origins with ftir spectroscopy—a suitable analytical tool for feed authentication?

Feed is substantial in the production of animal food products and subject to regulations about traceability in the european union. the geographical origin as one feature of authenticity was approached by spectroscopic techniques such as fourier transform infrared spectroscopy. this fast and non-destructive method be used to identify suspicious samples and initiate further investigations. the aim of the feasibility study was the development of classification models based on authentic grain maize samples from three different countries. grain maize was used as demonstrator for unprocessed feed materials due to its wide cultivation and trade. attenuated total reflexion fourier transform infrared spectroscopy and multivariate analyses were applied to differentiate grain maize samples by their geographical origin (ukraine, usa, peru). several sample preparations and data preprocessings were tested based on the results of a hard and a soft classification method. model validation was performed with separate test sets and permutation tests. the use of an optimal data preprocessing resulted in 100% sensitivity for solid samples in both classification models, whereas oil extraction resulted in 100% and 70% sensitivity, respectively. these findings indicate the feasibility of ftir spectroscopy combined with multivariate classification to verify the geographical origin of grain maize.