Assessing the efficacy of washing methods in reducing multi-pesticide residues in Brown, milled long, and milled basmati Rice

IF 6.5 1区 农林科学 Q1 CHEMISTRY, APPLIED
Filipa Carreiró , Sílvia Cruz Barros , Carla Brites , Patricia Cazón , Duarte Torres , Fernando Ramos , Ana Sanches Silva
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引用次数: 0

Abstract

Pesticides are vital for protecting crops from diseases but pose risks to human health and the environment, requiring careful evaluation. This study examines pesticide residues in rice and strategies for their removal. Brown, long-milled, and basmati-milled rice samples were spiked with 121 pesticides from different categories (e.g., carbamates, organophosphates, neonicotinoids, triazolobenzothiazoles) at 20 and 50 μg/mL to evaluate residue levels. Pesticides were extracted using the QuEChERS (quick, easy, cheap, effective, rugged, and safe) method and analyzed via High Performance Liquid Chromatography coupled with mass spectrometry. Residue removal was tested using washing methods with and without vinegar. Results showed that long-grain milled rice had higher pesticide residues, and adding vinegar significantly enhanced their removal. These findings contribute to improving food safety practices by providing insights into effective pesticide residue mitigation in rice.
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来源期刊
Food Chemistry: X
Food Chemistry: X CHEMISTRY, APPLIED-
CiteScore
4.90
自引率
6.60%
发文量
315
审稿时长
55 days
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.
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