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Evaluating sulfoxaflor residues in pig tissues using animal modeling
Hyun-Woo Cho1, Kangmin Seo1, Jin Young Jeong1
1National Institute of Animal Science, Rural Development Administration, Wanju 55365, Korea.
Journal of Animal Science and Technology
|October 26, 2022
Summary
Small laboratory animals can accurately predict pesticide residues in livestock, reducing the need for animal testing. This study validates using rats to establish maximum residue limits (MRLs) for pesticides in animal feed.
Area of Science:
- Agricultural Science
- Toxicology
- Animal Science
Background:
- Maximum residue limits (MRLs) for pesticides in animal feed are crucial for public health and safe livestock products.
- In vivo experiments with livestock are traditionally used for reliable pesticide residue quantification.
Purpose of the Study:
- To assess if small laboratory animals can replace or reduce the use of monogastric livestock in pesticide residue quantification experiments.
- To evaluate the efficacy of using rats as a model for predicting pesticide residues in pigs.
Main Methods:
- Pigs and rats were fed varying doses of sulfoxaflor (0, 3, 9, or 30 mg/kg) for four weeks.
- Tissue samples (serum, muscle, fat, liver, kidney, small intestine) were collected and analyzed for sulfoxaflor residues using LC-MS/MS.
- Correlation and regression models were developed based on residue levels in rats and pigs.
Main Results:
- Sulfoxaflor residues in pig tissues significantly correlated with those in rat tissues.
- Model predictions of sulfoxaflor residues in both species showed over 90% similarity to measured values.
- Sulfoxaflor administration did not adversely affect animal growth or feed efficiency.
Conclusions:
- Small laboratory animals, specifically rats, can serve as a viable alternative to livestock for in vivo pesticide residue quantification.
- This approach can reduce the reliance on large-scale animal experiments for establishing MRLs.
- The findings support the use of rodent models for obtaining in vivo pesticide residue data, contributing to regulatory science.

