Department of Chemistry, Universidade Federal de Viçosa, Viçosa, Minas Gerais 36570900, Brasil.
Department of Soil, Universidade Federal de Viçosa, Viçosa, Minas Gerais 36570900, Brasil.
J Agric Food Chem. 2024 Nov 27;72(47):26098-26105. doi: 10.1021/acs.jafc.4c06366. Epub 2024 Oct 24.
This research proposes an alternative method to detect and quantify glyphosate residues in unroasted green coffee beans by LC-MS/MS. The sample preparation was conducted without derivatization steps, with integrated cleanup, which improves the analytical method's frequency. Validation results were consistent with the requirements of the regulatory guidelines employed. Specificity, linearity ( = 0.9991), precision (RSD ≤ 9%), and recovery (92-112%) were ensured, with a satisfactory limit of quantification (LOQ = 0.48 mg kg). These data demonstrate that the method is suitable for monitoring glyphosate residues in unroasted coffee beans while offering simplicity and speed in sample preparation. The method was applied to analyze authentic unroasted coffee bean samples, in which two of them were contaminated with glyphosate (<LOQ). These results exhibit the importance of glyphosate monitoring in coffee samples and enhance that the method can be successfully implemented as a tool to guarantee food quality and safety.
本研究提出了一种通过 LC-MS/MS 检测和量化未烘焙绿咖啡豆中草甘膦残留的替代方法。该方法在样品制备过程中无需进行衍生化步骤,采用一体化净化,提高了分析方法的频率。验证结果符合所采用的监管指南的要求。确保了方法的特异性(=0.9991)、线性(=0.9991)、精密度(RSD≤9%)和回收率(92-112%),并达到了令人满意的定量限(LOQ=0.48mgkg)。这些数据表明,该方法适用于监测未烘焙咖啡豆中的草甘膦残留,同时在样品制备方面具有简便和快速的特点。该方法已应用于分析真实的未烘焙咖啡豆样品,其中两个样品被草甘膦污染(<LOQ)。这些结果表明了在咖啡样品中监测草甘膦的重要性,并证明了该方法可以成功地作为一种工具来保证食品质量和安全。