Functional foods provide nutritional and health benefits, yet they could be contaminated with residues like pesticides and polychlorobiphenyls. These residues affect the safety, quality, and consequently the commercial value of functional foods. Therefore, the validity and efficiency of residue determination methods constitute a major analytical concern. Reduction of matrix effect (ME) has always been the golden key for guaranteed sensitivity, selectivity, and high throughput analysis. This study aims for accurate determination and streamlined quantification of 200 pesticide residues in 16 matrices. Hence, QuEChERS protocol coupled to GC-MS/MS was then employed and separations were obtained in 25 min. Dilution of the final extracts of fresh and herbal samples was carried out to achieve an acceptable balance between sensitivity and peak characteristics. Dilution factors of 1x and 5x were selected for fresh and herbal samples, respectively. Principal component analysis (PCA) was then independently applied on the digitally exported total ion chromatograms (TICs) of the studied matrices and the calculated ME%. PCA score/loading plots of TICs demonstrated the key matrix constituents that influenced the obtained trends. Similarly, three main clusters were obtained after PCA of ME% indicating a dependent relationship between matrix type and the obtained effects. Out of the obtained three clusters, an appropriate representative matrix-matched calibration (R-MMC) was selected for ME compensation. Based on the EU validation guidelines, the proposed protocol was validated at 2 and 10 μg Kg⁻¹ with acceptable method performance. Four proficiency testing (PT) and commercial samples were successfully analyzed. The proposed protocol would help laboratories to increase sample processing capacity and to ensure the safety of functional food products. This work should serve in setting standards that warranty the quality/safety of functional foods by national regulatory authorities.

中文翻译：

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GC-MS / MS与主成分分析的耦合以评估基质效应：某些功能食品中农药残留的超低含量的有效测定

功能性食品可提供营养和健康益处，但仍可能被农药和多氯联苯之类的残留物污染。这些残留物会影响功能食品的安全性，质量并因此影响其商业价值。因此，残留物测定方法的有效性和效率构成了主要的分析关注点。降低基质效应（ME）一直是保证灵敏度，选择性和高通量分析的金钥匙。这项研究旨在准确测定和简化16种基质中200种农药残留的定量分析。因此，然后使用QuEChERS方案与GC-MS / MS偶联，并在25分钟内获得分离结果。对新鲜和草药样品的最终提取物进行稀释，以在灵敏度和峰特征之间达到可接受的平衡。新鲜样品和草药样品的稀释因子分别选择为1x和5x。然后将主成分分析（PCA）分别应用于所研究基质的数字输出总离子色谱图（TICs）和计算出的ME％。TIC的PCA得分/负荷图显示了影响获得趋势的关键基质成分。类似地，在ME％的PCA之后获得了三个主要的簇，表明基质类型与所获得的效果之间具有依赖性。从获得的三个簇中，选择适当的代表性矩阵匹配校准（R-MMC）进行ME补偿。根据欧盟验证准则，^-1，方法性能可接受。成功分析了四个能力验证（PT）和商业样本。拟议的方案将有助于实验室提高样品处理能力并确保功能性食品的安全性。这项工作应有助于制定国家监管机构对功能性食品的质量/安全性进行保证的标准。