# Study on Detection Method of Sulfamethazine Residues in Duck Blood Based on Surface-Enhanced Raman Spectroscopy

## TL;DR

This study develops a fast and accurate method to detect sulfamethazine residues in duck blood using Raman spectroscopy and chemometric analysis.

## Contribution

A novel SERS-based detection method for SM2 in duck blood with optimized sample preparation and chemometric modeling is introduced.

## Key findings

- The CARS-MLR model achieved a high prediction accuracy with an Rp² of 0.9817.
- The method's limit of quantification was 0.75 mg/L, showing strong sensitivity.
- Air-PLS was identified as the best preprocessing method for SERS data.

## Abstract

Sulfadimethazine (SM2) is widely used in livestock and poultry farming, but its improper use can pose a serious threat to human health. Therefore, the detection of SM2 residues in livestock and poultry products, including duck blood, is of great significance for food safety. A rapid detection method for SM2 residues in duck blood based on surface-enhanced Raman spectroscopy (SERS) was proposed in this paper. Density functional theory (DFT) was employed to optimize the molecular structure of SM2 and perform theoretical Raman vibrational analysis, thereby identifying its characteristic peaks. The enhancement effects of four different substrates were compared. The sample pretreatment method and detection conditions were optimized through single-factor experiments, including the types and amounts of electrolyte aggregators, the amount of gold nanocolloids, and the adsorption time. Under optimal conditions, the SERS spectral data of the samples were preprocessed, and features were extracted to establish an optimal quantitative prediction model. The experimental results found that the adaptive iteratively reweighted penalized least-squares method (air-PLS) was the best preprocessing method, and the competitive adaptive reweighted sampling–multiple linear regression (CARS-MLR) model demonstrated the best prediction performance, with a coefficient of determination for the prediction set (Rp2) of 0.9817, a root mean square error of calibration (RMSEC) of 1.5539 mg/L, a relative prediction deviation (RPD) of 7.1953, and limits of quantification of 0.75 mg/L. The research demonstrated that the combination of SERS technology and chemometric methods was feasible and effective for the detection of SM2 residues in duck blood.