Visible-near infrared spectroscopy and near-infrared hyperspectral imaging for the detection of T-2 and HT-2 toxins in individual oat grains

Oat grains are increasingly consumed worldwide due to their health benefits, yet they are highly susceptible to contamination by Fusarium toxins, particularly T-2 and HT-2 toxins (T-2+HT-2). These toxins pose serious health risks and are unevenly distributed, with a few highly contaminated grains often driving a batch over legal safety limits. Current detection methods are destructive, slow, or inadequate for detecting contamination at the individual grain level. This study is the first to demonstrate the potential of visible-near-infrared (Vis-NIR) spectroscopy and near-infrared hyperspectral imaging (NIR-HSI) to detect T-2+HT-2 in individual oat grains nondestructively. 200 grains were scanned, and their toxin content quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Classification models were developed to identify grains exceeding both the European Union (EU) legal threshold (1250 μg/kg) and a higher risk level (10,000 μg/kg). Both techniques achieved high accuracy (up to 94.5 %) in identifying contaminated grains. Key wavelengths were identified (e.g., 1203, 1419, 1424 and 1476 nm in NIR; 440-455 nm in Vis), and reducing the model to 20 wavelengths preserved performance while simplifying computation. Critically, removing just 21.5 % of the most contaminated grains could reduce overall toxin levels by over 95 %. Moreover, sampling simulations revealed that analysing 30 % of grains guarantees detection of contamination above legal limits, whereas 0.5 % sampling yields only a 25-33 % detection chance. These findings highlight a feasible path for integrating spectroscopic screening into industrial oat sorting lines, improving food safety, reducing economic losses, and overcoming key limitations of conventional mycotoxin monitoring.

This work was supported by the Spanish Ministry of Science and Innovation (predoctoral grant FPU21/00073 and Project PID2020-114836RB-I00 funded by MCIN/AEI/10.13039/501100011033) and Cranfield University. The authors would like to thank Derek Croucher from Morning Foods for providing the contaminated oats samples for analysis.