Recent advances in the use of surface-enhanced Raman spectroscopy for thiram detection in food products

Abstract

Thiram is a broad-spectrum fungicide used to protect postharvest fruits and vegetables from pathogen infection. However, thiram has been related to major human diseases, leading to the establishment of strict MRLs. Here, we are reviewing for the first time the methods for the identification and quantification of thiram in food products based on SERS. The sensitivity and reproducibility obtained when using different preprocessing steps and metallic nanoparticles have been compared. SERS allowed the detection of thiram in situ, which provided a band at approximately 1377 cm¹ that could be used for thiram quantification. SERS provided higher intensity enhancements for thiram than for other fungicides, indicating that it is a suitable technique for the selective detection of thiram. The highest sensitivities were observed when using silver nanoparticles. Machine learning analysis is emerging as a suitable way to enhance SERS reproducibility in in situ analysis, to predict thiram concentrations in fruit and vegetable internal layers, and to simultaneously quantify thiram together with other fungicides. Overall, SERS provides unique advantages for thiram detection, rendering it a suitable method for the inexpensive and highly sensitive detection of this fungicide.