We examined a number of large proficiency and control databases supporting the values reported for pesticide residues in agricultural commodities at fractions of a part per million (mg/kg). The average recovery from >100,000 recovery records in 13 databases was 94%. The overall average single-value relative standard deviation (RSD) of the reported recoveries was 17% at a mean concentration (C) of about 10(-7) (0.1 mg/kg). The average apparent HORRAT value (RSD found/RSDR predicted from the Horwitz formula [2*C(-0.1505)]) was 0.8. Analysis of variance indicated that about 60-70% of the variance could not be associated with any particular factor or combination of factors-analyte, commodity, method, laboratory, concentration, database, or their interactions. The most predominant factor, analyte, and its third-order interaction with laboratory and concentration contributed most of the assignable variance. These findings suggested that most of the variability of trace analysis for pesticide residues is "random" in the sense of being inherent and not assignable to specific factor fluctuations.
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Anal Methods
November 2017
College of Environmental and Chemical Engineering, Nanchang Hangkong University, Nanchang 330063, China.
A novel method was established using a restricted access material combined with a molecularly imprinted polymer (RAM-MIP) as the sorbent material in solid phase extraction (SPE) for clean-up of α-endosulfan, β-endosulfan, endosulfate, endosulfan-ether, endosulfan lactone, heptachlor, heptachlor--epoxide, and heptachlor--epoxide in pork and gas chromatography (GC) for determination. The RAM-MIP was prepared by precipitation polymerization by using endosulfan as the template, methacrylic acid (MAA) as the monomer, glycidyl methacrylate (GMA) as the pro-hydrophilic co-monomer, ethylene glycol dimethacrylate (EGDMA) as the crosslinker, azobisisobutyronitrile (AIBN) as the initiator, and toluene as the porogen. Ultraviolet spectroscopy (UV) and H-nuclear magnetic resonance (H-NMR) analysis verified that MAA interacted specifically with endosulfan in a ratio of 1 : 1 in the pre-polymerization solution.
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January 2025
Department of Electronics and Communication Engineering, Tezpur University, Tezpur, 784028, India. Electronic address:
Detection and analysis of organochlorine pesticides (OCP) residue is getting significant research importance because of their extensive use despite their hazardous effects on the health of people and the ecosystem. Despite the implementation of regulations and bans to safeguard human health and the environment, reports frequently reveal the continued use of these harmful chemicals in quantities exceeding the recommended limits set by regulatory boards. Data on the use of OCP from India, the most populous country, and African countries is not very encouraging.
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January 2025
School of Precision Instrument and Opto-electronics Engineering, Tianjin University, Tianjin 300072 China. Electronic address:
The detection of pesticide residues in agricultural products is crucial for ensuring food safety. However, traditional methods are often constrained by slow processing speeds and a restricted analytical scope. This study presents a novel method that uses filter-array-based hyperspectral imaging enhanced by a dynamic filtering demosaicking algorithm, which significantly improves the speed and accuracy of detecting pesticide residues.
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January 2025
Key Laboratory of Health Risk Appraisal for Trace Toxic Chemicals of Zhejiang Province, Ningbo Municipal Center for Disease Control and Prevention, Ningbo, Zhejiang 315010, China. Electronic address:
Novel core-shell flower-like polyamine/C dual-functional magnetic titanium dioxide-based oligopolymer (FeO@fTiO-PAPMA/C) microspheres were synthesized and used as a magnetic solid-phase extraction (MSPE) adsorbent to purify 52 pesticides in bayberry samples. The FeO@fTiO-PAPMA/C microspheres were fully characterized and it can obviously improve the purification ability of 52 pesticides in bayberry samples. Coupled to LC-MS/MS, the developed method indicated low limits of detection (LODs) and limits of quantification (LOQs) of 0.
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January 2025
Yunnan Dali Research Institute of Shanghai Jiao Tong University, Dali 671000, China.
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