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Record W4412355205 · doi:10.1002/agg2.70175

Effects of liming on soil physical and chemical properties in Europe and North America: A review

2025· review· en· W4412355205 on OpenAlexafffund
Priscillar Wenyika, Rebecca Oiza Enesi, Linda Yuya Gorim, Miles Dyck

Bibliographic record

VenueAgrosystems Geosciences & Environment · 2025
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Management and Crop Yield
Canadian institutionsUniversity of Alberta
FundersWestern Grains Research Foundation
KeywordsEnvironmental scienceAgroforestry

Abstract

fetched live from OpenAlex

Abstract Soil acidity is one of the major constraints limiting crop production worldwide. About 50% of the global arable land is acidic. Liming remains an effective strategy for soil acidity amelioration and improvement of soil fertility. The objective of this review was to summarize information on liming effects on soil physical and chemical properties in the North American and European contexts. We reviewed how different lime products influence soil pH and various soil processes that contribute to soil physical and chemical health. Our findings were that, when applied at appropriate rates, liming materials generally increased soil pH, cation exchange capacity (CEC), exchangeable calcium and magnesium, nutrient availability and reduced toxicities of aluminum (Al), manganese (Mn), and heavy metals. Many studies showed that liming modifies soil properties and processes both in the short‐ and long‐term. While most studies reported improvements in nutrient availability, there were some differences in liming impacts on phosphorus (P) and potassium (K), mostly due to differences in soil type and composition. Liming improves structural properties including aggregate stability, soil friability, porosity, and water infiltration. Knowledge about liming impacts on soil physical and chemical properties is essential for optimizing liming rates to enhance soil health and improve productivity. Future studies should explore liming effects on CEC, associations of P and K with cations supplied by liming (e.g., Ca 2+ ), and use of some waste materials as lime alternatives.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.208
Teacher spread0.188 · 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

Citations10
Published2025
Admission routes2
Has abstractyes

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