Direct quantification of low-density polyethylene microplastic in corn silage via handheld diffuse-reflection near-infrared spectroscopy

Microplastic (MP) contamination in terrestrial animal products poses an emerging threat to human and animal health, yet the extent of this contamination on farms is unclear. Current MP detection methods in animal feed require MP extraction from samples for quantification and characterization, a time-consuming process that varies based on the matrix composition. To address this limitation, handheld near-infrared spectroscopy (NIRS) was evaluated as a direct method to detect MP in corn silage (CS), a common cattle feed in northern Italy. Twelve CS batches from various farms were spiked with low-density polyethylene MP at concentrations ranging from 0 to 2.0% (w/w), yielding 240 samples. Calibration models were developed using two strategies: individual batch calibrations and batch-independent calibrations combining all samples. Partial least squares regression was applied with approximately 75% of samples for calibration and 25% for external validation. Individual batch calibration showed variable performance (R 2 P=0.81-0.98), with most models achieving sufficient accuracy for quality control purposes (RPD>3.0). The batch-independent calibration exhibited excellent performance (R 2 P=0.97, RPD=6.3) when spectra were averaged at each concentration level. These findings demonstrate that handheld NIRS can effectively monitor MP contamination directly in single batches for quality control and, through batch averaging, enable larger-scale regional assessments of feed. • MP quantitative calibration models using handheld NIRS were built without extraction • Model performance for single batches shows feasibility for quality control • LDPE MPs can be detected down to 0.35% in corn silages by NIRS • Batch-independent model showed high accuracy by averaging, apt for regional assay