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Short term nitrogen availability following overwinter cereal/grass and legume cover crop monocultures and mixtures in South Coastal British Columbia

2000· article· en· W1914998185 on OpenAlexaboutno aff
Jude J. O. Odhiambo, A. A. Bomke

Bibliographic record

VenueJournal of Soil and Water Conservation · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsVicia villosaSecaleMonocultureAgronomyLolium multiflorumCover cropBiologyLegumeSowingCrop

Abstract

fetched live from OpenAlex

This 1995 to 1996 study was conducted to determine the effects of cereal/grass and legume cover crop monocultures and mixtures on short term N availability. Cover crop treatments included winter wheat (Triticum aestivum L.), fall rye (Secale cereale L.), annual ryegrass (Lolium multiflorum L.) planted in monoculture and in mixtures with crimson clover (Trifolium incarnatum L.), crimson clover, winter wheat + hairy vetch (Vicia villosa) and bare control. Incubation studies using the cover crop residues were set up for a sixteen week incubation period under field conditions using the in situ resin core method. At the end of the incubation period, total net N release by winter wheat, fall rye, and annual ryegrass ranged from 48 to 80 kg N ha−1 in 1995 and 41 to 92 kg N ha−1 in 1996. Crimson clover mixtures with winter wheat, fall rye, or annual ryegrass had total net N released ranging between 42 to 106 kg N ha−1 in 1995 and 83 to 104 kg N ha−1 in 1996. In contrast, total net N released by winter wheat + hairy vetch was 160 kg N ha−1 in 1995 and 170 kg N ha−1 in 1996. Total net N released by crimson clover was 158 kg N ha−1 in 1995 and 41 kg N ha−1 in 1996. Critical N concentration above which N mineralization occurred was determined as 14.1 g kg−1 and this corresponded to a critical C:N ratio of 31.7. Winter wheat + hairy vetch mixture seems to be more reliable than cereal/grass + crimson clover mixtures in terms of N contribution on decomposition, and legumes in mixtures may reduce the potential for short term N immobilization.

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 score0.034
Threshold uncertainty score0.999

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 head0.009
GPT teacher head0.195
Teacher spread0.185 · 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

Citations15
Published2000
Admission routes1
Has abstractyes

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