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Revolutionizing Pesticide Detection with Raman-Based Spectroscopy
In their paper, “Recent Developments and Applications of Surface-Enhanced Raman Scattering Spectroscopy in Pesticides Detection: From Single Pesticides to Mixed Pesticides,” authors Peng Yu, Lin Ma, Xiaoyu Yang, Shun Xue, Zheng Zhang, Lei Sun, and Jiandong Cai explore both the technological innovations and practical implications of using SERS in detecting even trace levels of chemical residues in agriculture (1).
The team is affiliated with multiple research institutions across China, including the State Key Laboratory of Food Science and Technology at Jiangnan University, and the College of Food Science and Engineering at Ocean University of China (1).
Advanced spectroscopy detects even the trickiest pesticide chemical contamination © Atchariya63 -chronicles-stock.adobe.com
Why Detecting Pesticides Is Still a Challenge
Pesticide residues on fruits, vegetables, and grains pose serious risks to human health and the environment. While regulatory limits exist, the reality of modern agriculture often involves complex mixtures of chemicals that are difficult to detect, especially in low concentrations (1,2).
Traditional detection methods—such as gas chromatography and mass spectrometry—require extensive sample preparation, costly equipment, and skilled operators. SERS, however, offers a faster, non-destructive alternative capable of identifying chemicals based on their molecular fingerprint (1,2).
SERS: A Next-Gen Tool for Chemical Detection
Surface-enhanced Raman scattering amplifies the weak Raman signals of molecules when they are near nanostructured metallic surfaces, such as gold or silver nanoparticles. This amplification enables detection down to parts-per-billion or even parts-per-trillion concentrations (1,2).
The new study highlights recent advances in nanomaterial substrates that boost the sensitivity, reproducibility, and portability of SERS systems. These include silver nanowires, gold-silver core-shell nanoparticles, and flexible films that can be directly applied to food surfaces (1).
Yu and colleagues also explored the use of chemometric models—statistical tools that interpret complex spectral data—to accurately classify and quantify pesticide types and concentrations. These models were particularly crucial when dealing with mixed pesticide samples, a scenario increasingly common in real-world farming (1).
Detecting Single vs. Mixed Pesticides
One of the most important developments in the study is the expansion of SERS techniques from identifying single pesticide molecules to handling mixtures. Mixed pesticide detection requires resolving overlapping spectral features, which is significantly more difficult than analyzing a single compound (1).
To overcome this challenge, the researchers used multivariate statistical techniques like principal component analysis (PCA) and partial least squares regression (PLSR) to isolate and quantify each pesticide's contribution to the overall spectrum. These methods, combined with the improved nanostructured substrates, allowed for rapid and accurate detection even in complex matrices like fruit peels or soil extracts (1).
Toward Real-World Applications
The authors emphasize the practical potential of their work. They note that portable SERS devices—combined with advanced spectral libraries and data analytics—could soon be used for on-site testing in markets, warehouses, and farms (1).
According to the study, “SERS holds great promise as a non-destructive, fast, and sensitive method for detecting both single and multiple pesticide residues in agricultural products.”
However, the team acknowledges that challenges remain, particularly in substrate reproducibility and matrix interference (1). Ongoing work aims to develop standardized SERS substrates and expand chemometric algorithms for broader use (1,2).
The Road Ahead
As public demand for cleaner, safer food grows, technologies like SERS will play an increasingly central role in enforcing safety standards. This study represents a step forward in using spectroscopy not just to detect contamination, but to do so in real time, at low cost, and with precision.
With continued innovation in nanomaterials and data processing, SERS could soon become a go-to method for rapid pesticide screening across the agricultural supply chain.
References
(1) Yu, P.; Ma, L.; Yang, X.; Xue, S.; Zhang, Z.; Sun, L.; Cai, J. Recent Developments and Applications of Surface-Enhanced Raman Scattering Spectroscopy in Pesticides Detection: From Single Pesticides to Mixed Pesticides. ACS Omega 2025, in press. DOI: 10.1021/acsomega.5c02940
(2) Xu, M. L.; Gao, Y.; Han, X. X.; Zhao, B. Detection of Pesticide Residues in Food Using Surface-Enhanced Raman Spectroscopy: A Review. J. Agric. Food Chem. 2017, 65 (32), 6719–6726. DOI: 10.1021/acs.jafc.7b02504
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