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Record W4406205349 · doi:10.1016/j.jafr.2025.101643

Glyphosate in food: A narrative review

2025· review· en· W4406205349 on OpenAlexaboutno aff
Christelle Bou‐Mitri, Sabine Dagher, Alaa Makkawi, Zaynab Khreyss, Hussein F. Hassan

Bibliographic record

VenueJournal of Agriculture and Food Research · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeGlyphosatePsychologyArtBiologyBiotechnologyLiterature

Abstract

fetched live from OpenAlex

Glyphosate, a widely used broad-spectrum herbicide, plays a crucial role in global crop production due to its effectiveness and low cost. This paper provides an updated overview of the exposure routes, regulations, occurrence, dietary exposure and risk characterization of glyphosate in food products worldwide on recent years. Glyphosate had been detected in various staple food products, including maize, wheat and soybeans, in regions such as Europe, Canada and USA. The herbicide was associated with cancer, reproductive disorders, and development defects. To address safety concerns, maximum residue limits (MRLs) for glyphosate have been established by several international agencies. Notably, no studies to date have reported exceedance of the acceptable daily intake (ADI), and all calculated hazard quotients (HQ) suggested a very low risk. This review highlights a research gap at the intersection of glyphosate use, climate change, and sustainability. It calls for examination of how evolving environmental conditions and agricultural practices might affect glyphosate application and its implications for food safety and public health. • Glyphosate residues found in global food products, yet most remain below MRL limits. • Studies report no significant exceedance of ADI, posing low risk to human health. • Children show higher susceptibility to glyphosate due to increased intake and exposure. • Mediterranean diet shows low risk despite high glyphosate in vegetables. • Calls for more research on glyphosate's long-term health effects, especially in children.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.790
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.064
GPT teacher head0.382
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2025
Admission routes1
Has abstractyes

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