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Record W2086266906 · doi:10.4141/p04-070

Long-term effects of late-summer overseeding of winter rye on corn grain yield and nitrogen balance

2005· article· en· W2086266906 on OpenAlexvenueno aff
B. R. Ball Coelho, R. C. Roy, A. J. Bruin

Bibliographic record

VenueCanadian Journal of Plant Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSecaleAgronomyCover cropFertilizerTillageLeaching (pedology)Nitrogen balanceCropping systemNitrogenLong-term experimentEnvironmental scienceCropBiologyChemistrySoil waterSoil science

Abstract

fetched live from OpenAlex

Winter rye (Secale cereale) overseeded into standing corn (Zea mays L.) on sandy soil controlled NO 3 leaching over the short-term (3 yr). Long-term effects were unknown, so yield and N balance were monitored for an additional 6 yr with and without a rye cover crop under conventional (CT) and no-till (NT) management at six fertilizer N rates. Corn yield was greater with rye cover cropping than without in 6 of the last 7 yr. Response exceeded 1600 kg grain ha -1 (average 100–200 kg fertilizer N ha -1 ) by year 8 (wet following a dry year) and was greater under NT than CT in dry years (years 7 and 9). The response is attributed to improved soil physical properties and N availability. Rye N uptake increased with fertilizer N rate particularly following dry growing seasons, with shoots containing up to 73 kg N ha -1 . Post-harvest topsoil NO 3 was reduced by the rye in all but the initial year, and groundwater NO 3 -N concentrations only exceeded 10 mg L -1 without rye. The overseeding system facilitates utilization of conserved N and reduces movement of NO 3 to groundwater over the long term. Key words: Nitrogen management, Zea mays, Secale cereale, cover crop, soil nitrate, tillage

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score1.000

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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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

Citations28
Published2005
Admission routes1
Has abstractyes

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