Alexander M. Stuart · Environmental Science and Pollution Research 2023 · Narrative review and stakeholder consultation · n=?

Agriculture without paraquat is feasible without loss of productivity—lessons learned from phasing out a highly hazardous herbicide

Cited 66 times in the scientific literature.

Level 5 - mechanism / opinion, no new human data

Narrative review and expert consultation without systematic review protocol (by design analogy, not clinical CEBM)

OpenAlex W4313814049 · doi:10.1007/s11356-022-24951-0 · record verified 2026-08-27

What was done

The authors synthesized evidence from a literature review and stakeholder consultations to evaluate the feasibility of phasing out paraquat globally. They examined historical agricultural production trends following national bans, identified non-herbicide and alternative weed management or defoliation techniques, and assessed the operational experience of over 1.25 million farmers in low- and middle-income countries (LMICs) complying with private voluntary standards that prohibit paraquat.

What was found

Paraquat is banned in more than 67 countries but remains widely used in Asia and Latin America. The abstract reports that agricultural production data consistently showed no negative effects on productivity following paraquat bans. Over 1.25 million farmers in LMICs successfully cultivate food and fiber crops under standards prohibiting its use. Aside from these counts, the abstract provides no specific quantitative metrics, effect sizes, or cost comparisons for the alternative practices.

Why it matters

Paraquat is a major contributor to fatal acute pesticide poisonings and suicides globally. Demonstrating that agricultural productivity can be sustained without it offers actionable evidence for regulators and supply chains pursuing bans and safer agricultural alternatives.

Limits

This is a narrative synthesis rather than a formal systematic review or meta-analysis. The abstract provides no granular quantitative data on crop yields, labor requirements, economic costs, or implementation timelines across specific crops and regions. Selection bias in consulted stakeholders and reviewed case studies cannot be excluded.

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