MétaCan
Menu
Back to cohort
Record W6959910127 · doi:10.1139/cjss2013-093

Long-term tillage and crop rotation effects on soil quality, organic carbon, and total nitrogen

2014· article· en· W6959910127 on OpenAlexaboutno aff

Bibliographic record

VenueBioOne Complete (BioOne) · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPloughTillageCrop rotationLoamSoil qualityMulch-tillMinimum tillageCropCrop yield

Abstract

fetched live from OpenAlex

Van Eerd, L. L., Congreves, K. A., Hayes, A., Verhallen, A. and Hooker, D. C. 2014. Long-term tillage and crop rotation effects on soil quality, organic carbon, and total nitrogen. Can. J. Soil Sci. 94: 303-315. Long-term studies allow for quantification of the effects of crop production practices, such as tillage and crop rotation, on soil quality and soil C and N stores. In two experiments at Ridgetown, ON, we evaluated the long-term (11 and 15 yr) effect of tillage system and crop rotation on soil quality via the Cornell Soil Health Assessment (CSHA) at 0-15 cm and soil organic C (SOC) and total N at 5-, 10-, and 20-cm increments to 120 cm depth. The CSHA soil quality score and SOC and total N were higher with no-till (NT) than fall moldboard plough with spring cultivation (conventional tillage, CT) and rotations with winter wheat [soybean-winter wheat (S-W) and soybean-winter wheat-corn (S-W-C)] compared with rotations without winter wheat. In both long-term trials, NT had ca. 21 Mg ha-1 more or 14% higher SOC than CT in the 0- to 100-cm soil profile, a trend which contrasts previous research in eastern Canada. Thus, the two long-term trial results at Ridgetown suggest that to improve soil quality and storage of C and N, growers on clay loam soil in southwestern Ontario should consider adopting NT production practices and including winter wheat in the rotation.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.405

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.127
GPT teacher head0.221
Teacher spread0.095 · 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 designObservational
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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueBioOne Complete (BioOne)Same topicGenetic and Environmental Crop StudiesFrench-language works237,207