# Strategies to Determine and Mitigate Pesticide Residues in Food

**Authors:** Ana Rita Oliveira, Sílvia Cruz Barros, Duarte Torres, Ana Sanches Silva

PMC · DOI: 10.3390/molecules31010063 · Molecules · 2025-12-24

## TL;DR

This paper reviews methods to reduce pesticide residues in food, including household techniques and AI-driven solutions, to ensure safer food.

## Contribution

The paper highlights the emerging role of AI in mitigating pesticide residues alongside traditional and industrial methods.

## Key findings

- Washing with running water can reduce pesticide residues by up to 77% in some vegetables.
- Industrial methods like ozonated water and cold plasma offer high efficiency in residue reduction.
- AI enhances precision agriculture and regulatory analytics for safer food supply.

## Abstract

This review provides a comprehensive overview of strategies to mitigate pesticide residues in food, examining both household and industrial processing techniques alongside the emerging role of Artificial Intelligence (AI). Simple household methods, such as washing, peeling, and thermal processing (e.g., boiling, frying), are effective. For instance, washing with running water achieves a reduction of up to 77% in residue for some vegetables. Additionally, processes like jam-making or frying can significantly reduce specific residues. Industrially, advanced methods such as ozonated water washing, ultrasonification, and cold plasma are employed for high efficiency while preserving food quality. Critically, AI is emerging as a powerful, indirect tool through predictive modelling, AI-assisted sorting/screening, and consumer guidance, enhancing precision agriculture and regulatory analytics. The review paper concludes that a combination of these diverse methods is essential for minimizing pesticide exposure and ensuring a safer food supply.

## Full-text entities

- **Chemicals:** water (MESH:D014867)

## Full text

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## Figures

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## References

140 references — full list in the complete paper: https://tomesphere.com/paper/PMC12787089/full.md

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Source: https://tomesphere.com/paper/PMC12787089