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Record W4413377929 · doi:10.1002/jpln.70018

Development, Efficiency, and Impact Factors of Phosphorus Nanofertilizers in Agriculture: A Review

2025· article· en· W4413377929 on OpenAlexaff
Houssameddine Mansouri, Hamid Ait Said, Hassan Noukrati, Abdallah Oukarroum, Hicham Ben Youcef, Treavor H. Boyer, François Perreault

Bibliographic record

VenueJournal of Plant Nutrition and Soil Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversité du Québec à Montréal
FundersUniversité Mohammed VI Polytechnique
KeywordsPhosphorusAgricultureEnvironmental scienceAgronomyChemistryGeographyBiologyArchaeology

Abstract

fetched live from OpenAlex

ABSTRACT Modern intensive agriculture to feed the growing population of the world has been practiced in view of the limitations of arable land and water resources. However, overapplication of chemical fertilizers may pose severe environmental impacts, including soil degradation, water eutrophication, and pollution of groundwater. One of the current trends to reduce the adverse effects of fertilizers is the application of nanotechnology, which has an exciting potential to increase fertilizer efficiency and sustainability. We carried out a systematic literature review through Web of Science and Scopus. The used keywords were “nanofertilizers,” “phosphorus nanoparticles,” “nutrient‐use efficiency,” and “crop development.” Only studies that meet strict inclusion criteria regarding synthesis, application, plant uptake mechanism, and detailed insight into nanofertilizers were considered. To better understand the conditions that most foster nanofertilizer application, we reviewed the factors affecting nutrient‐use efficiency in plants. On this basis, focusing on phosphorus (P), we analyzed recent progress made on using P nanofertilizers and their effect on the development of various crops. The economic and environmental benefits and drawbacks of using nanofertilizers are both presented to make informed decisions by both farmers and industries on the use and manufacturing of the substances. Our review has established that nanofertilizers hold great promise for improving nutrient‐use efficiency and crop productivity, with special mention of phosphorus nanofertilizers, which can offer improved nutrient uptake, reduced environmental pollution, and possibly reduced fertilizer application rates. However, P nanofertilizers face adoption barriers such as unstudied long‐term environmental impacts, costly and unsustainable production methods, inconsistent performance across soils and crops requiring tailored formulations, and lack of regulations and safety guidelines. Transitioning to practical use demands prioritized research using long‐term trials and affordable green synthesis methods to address these gaps.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

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