New Analytical Method Enables Multi-Class Analysis of Pesticides in Corn Products
A new study introduces a comprehensive two-dimensional liquid chromatography coupled with tandem mass spectrometry (2D-LC–MS/MS) method for the analysis of 112 pesticides in corn-based products. The method exhibits high precision, lower limit of quantification values, and successful detection of trace levels of pesticides in real samples, offering promise for the analysis of complex matrices.
As the demand for organic food continues to rise, concerns regarding the presence of chemicals and pesticides in agricultural products persist. In response, scientists at the University of Messina in Italy have developed a novel analytical method for the detection and quantification of pesticides in corn-based products. The research, published in the Journal of Chromatography A, introduces a comprehensive two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC–MS/MS) approach capable of analyzing a wide range of 112 pesticides simultaneously (1).
Green corn field with corn cobs close up | Image Credit: © kyrychukvitaliy - stock.adobe.com
2D-LC–MS/MS is an advanced analytical technique used for the comprehensive analysis of complex samples. It combines two separate liquid chromatography (LC) dimensions with tandem mass spectrometry (MS/MS) to enhance separation and detection capabilities. In the first dimension of 2D-LC, the sample is subjected to one type of chromatography, such as reversed-phase or size exclusion, to separate the components based on their physicochemical properties. The eluent from the first dimension is then further separated in the second dimension using a different chromatographic mode, providing increased resolving power. Finally, the eluted analytes from the second dimension are introduced into the mass spectrometer for identification and quantification through MS/MS analysis.
This pioneering method utilizes a "reduced" QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) extraction and clean-up procedure prior to analysis. It allows for the accurate and efficient identification of pesticides in corn products. The researchers validated the method according to European legislation, and the limits of quantification were found to be lower than the regulatory standards. Additionally, the intra-day and inter-day precision demonstrated excellent reproducibility, with values below 12.9% and 15.1%, respectively, at a concentration level of 500 μg/kg.
The recovery rates of the analyzed pesticides were also evaluated, and over 70% of the compounds exhibited recovery values within the range of 70% to 120% at concentration levels of 50, 500, and 1000 µg/kg. The standard deviation values remained below 20%, indicating the method's reliability and accuracy. Furthermore, matrix effects, which can affect the accuracy of pesticide quantification, were determined to be between 13% and 161%.
To demonstrate the real-world applicability of their method, the researchers applied it to the analysis of actual corn product samples. Remarkably, trace amounts of three pesticides were detected in both samples, highlighting the sensitivity and efficiency of the developed technique. These findings not only underscore the importance of rigorous pesticide analysis in corn-based products but also provide valuable insights for future studies involving complex matrices.
The introduction of this comprehensive 2D-LC–MS/MS method for pesticide analysis in corn products represents a significant advancement in ensuring food safety and quality. By enabling the simultaneous detection of a wide range of pesticides, this technique will aid in monitoring and regulating pesticide levels in corn-based food products, thus contributing to consumer health and confidence in organic food choices.
Reference
(1) Martín-Pozo, L.; Arena, K.; Cacciola, F.; Dugo, P.; Mondello, L. Development and validation of a multi-class analysis of pesticides in corn products by comprehensive two-dimensional liquid chromatography-tandem mass spectrometry. J. Chromatogr. A 2023, 1701, 464064. DOI: https://doi.org/10.1016/j.chroma.2023.464064
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