Multi-model risk assessment of pesticide residues in seasonal fruits based on integrated targeted/non-targeted screening: Implications for vulnerable populations
Wenshuai Si , Yiqing Song , Can Guo , Zhiying Huang , Lei Chen , Fei Xu , Bing Bai , Kaixuan Huo , Shouying Wang
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引用次数: 0
Abstract
This study comprehensively analyzed multiple pesticide residues and their characteristics in commercially available fruits using integrated targeted and non-targeted techniques, with a focus on assessing health risks for children and pregnant women based on cumulative dietary risk models. Results showed 745 samples (7 categories) identified 54 pesticides (88.6 % detection rate; 1.1 % exceeding legal limits), with strawberries and peaches of the highest detection rates (98 %), and grapes the most diverse residues (avg. 6/sample). Risk ranking analysis flagged difenoconazole and indoxacarb as high-risk. Chronic cumulative exposure risks were dominated by hepatotoxic triazole fungicides. Acute risk assessments revealed potential hepatotoxicity concerns for children (3–6 years) and pregnant women consuming grapes/peaches. The Relative Potency Factor (RPF) model, accounting for synergism, showed 4–7 times higher neuro/hepatotoxicity risks than the Hazard Index (HI) model. This first integration of non-targeted screening with multi-model risk assessment provides evidence for strengthening pesticide regulation and protecting sensitive subpopulations.
期刊介绍:
Food Chemistry: X, one of three Open Access companion journals to Food Chemistry, follows the same aims, scope, and peer-review process. It focuses on papers advancing food and biochemistry or analytical methods, prioritizing research novelty. Manuscript evaluation considers novelty, scientific rigor, field advancement, and reader interest. Excluded are studies on food molecular sciences or disease cure/prevention. Topics include food component chemistry, bioactives, processing effects, additives, contaminants, and analytical methods. The journal welcome Analytical Papers addressing food microbiology, sensory aspects, and more, emphasizing new methods with robust validation and applicability to diverse foods or regions.