# Fitness-for-Purpose Assessment of Methods for Glyphosate Determination in Food: Trade-Off Between Analytical Performance and Environmental Impact

## TL;DR

This paper introduces a tool to help choose the best methods for detecting glyphosate in food by balancing accuracy and environmental impact.

## Contribution

A decision-support tool integrating analytical performance and environmental metrics for pesticide method selection.

## Key findings

- LC-MS/MS is suitable for official control, while FI-MS/MS and LFA are suitable for self-monitoring.
- LFA has the lowest environmental impact with AGREE scores of 0.63 and 0.68.
- The tool provides a practical framework for selecting optimal analytical methods.

## Abstract

Selecting analytical methods for pesticide residues in food increasingly requires balancing regulatory compliance, analytical performance, and environmental sustainability. This study presents a decision-support tool that evaluates the fitness-for-purpose of pesticide analytical methods by integrating SANTE/11312/2021 v2 validation criteria with Analytical GREEnness (AGREE)-based environmental metrics. Implemented in Excel with VBA macros, the tool guides users through the input of method parameters for both quantitative and screening approaches, scoring each against acceptance criteria. Based on the results, methods are classified as suitable for risk assessment, official control, or self-monitoring. The tool also calculates greenness scores to assess environmental impact. Glyphosate analysis in cereals was selected as a case study, and three approaches were compared: liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS), flow-injection coupled to MS/MS (FI-MS/MS), and lateral flow assay (LFA). LC-MS/MS was identified as the only method suitable for official control, while FI-MS/MS and LFA met requirements for self-monitoring. The greenness assessment highlighted substantial differences, with LFA showing the lowest environmental footprint (AGREE scores of 0.63 and 0.68 for manual and automated LFAs). Overall, the tool provides a practical, user-friendly framework for selecting analytical methods that optimize both analytical performance and environmental sustainability, supporting informed decision-making in food testing.