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Record W4400692608 · doi:10.17221/27/2024-swr

Does no-till cover crop influence in situ measured soil water potential and saturated hydraulic conductivity?

2024· article· en· W4400692608 on OpenAlexaboutno aff
Olivia Peters, Samuel I. Haruna

Bibliographic record

VenueSoil and Water Research · 2024
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsHydraulic conductivityCover cropEnvironmental scienceHydrology (agriculture)Cover (algebra)Soil scienceIn situAgronomySoil waterGeologyAgroforestryGeotechnical engineeringChemistryBiologyEngineering

Abstract

fetched live from OpenAlex

Soil water energy determines soil water balance, plant water uptake, and soil thermal properties, but the effects of cover crops (CCs) on in situ measured soil water energy and temperature are not well understood. This study investigated how CCs affect in situ measured soil water potential (SWP), temperature, and saturated hydraulic conductivity (Kfs) during 2 years, with the hypothesis that CC-induced water transpiration can lower SWP. The CCs used included crimson clover (Trifolium incarnatum L.), winter wheat (Triticum aestavum L.), hairy vetch (Vicia villosa), oats (Avena sativa), triticale (Titicale haxaploide Lart.), barley (Hordeum vulgare L.), flax (Linum usitatissimum L.), and winter peas (Lathyrus hirsutus L.). Soil water potential and temperature sensors were installed at 0–10, 10–20, and 20–30 cm depths. Additionally, Kfs was measured in situ using a Guelph permeameter. Results showed that actively growing CCs can lower SWP, leading to increased water transpiration from the field compared with no cover crop (NC) management. Also, by lowering soil temperature, CCs can increase evapotranspirational efficiency compared to NC management. Further, by increasing evapotranspirational efficiency, CC, management resulted in increased subsurface water infiltration and storage as shown by higher Kfs values compared to NC management. In general, CCs have the potential to reduce SWP and temperature during their growth stages and this can be beneficial to seed germination and microbial activities.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.020
GPT teacher head0.260
Teacher spread0.240 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations2
Published2024
Admission routes1
Has abstractyes

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