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Record W2287983946 · doi:10.14288/1.0088778

Short-term effects of graminaceous cover crops on autumn soil mineral nitrogen cycling in western lower Fraser Valley soils

2009· article· en· W2287983946 on OpenAlexaboutno aff
Leonard Simiyu Nafuma

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterAgronomyCyclingEnvironmental scienceNitrogenNitrogen cycleCover cropMineralSoil scienceChemistryGeographyBiologyEcologyForestry

Abstract

fetched live from OpenAlex

Proper cover crop management practices in autumn can minimize N0₃⁻-N leaching. Three experiments to study the effect of cover crop management on autumn soil mineral N conservation were conducted in the 1991-92, 1992-93 and 1993-94 winter seasons on a silty clay loam Rego Humic Gleysol in the western Lower Fraser Valley, British Columbia, Canada. The study tested short-term effects of planting date, autumn soil mineral N content and type of cover crop on biomass production and N uptake, residual soil mineral N (0-60 cm layer), plant composition of various N fractions of autumn-planted spring species at winter-kill, retention of accumulated N by autumn-planted spring species after winter-kill, and the C/N ratio of cover crops. Treatments involved two planting dates (late August and September), two simulated autumn residual mineral N levels (0 and 100 kg N ha⁻¹) and types of cover crops. In the first two seasons, the cover crop treatments were spring barley (Hordeum vulgare L.) and winter rye (Secale cereale L.) plus fallow for comparison purposes. In the third season, planting date was omitted and six cover crop treatments tested were spring barley, spring wheat (Triticum aestivum L.), spring oat (Avena sativa L.), winter rye and annual ryegrass (Lolium multiflorum Lam.) including fallow. Planting crops in August as compared to a month later increased biomass production by 56 to 135% and N uptake by 38 to 93% before winter leaching period. Large N uptake by cover crops that were planted in August was generally accompanied by significant reduction in soil mineral N (0-60 cm) from August to November. August-planted spring species N at winter-kill was largely composed of the protein fraction (insoluble and soluble) which increased with N supply in autumn when the initial mineral N contents in 0-60 cm layer of soil were suboptimal (< 100 kg N ha⁻¹) but was not affected when soil mineral N content was 200 kg N ha⁻¹ and more or when the cover crops were planted in September. There were indications that August-planted spring species can retain some of the soluble protein N fraction in the winter-killed residues during winter. Maximum plant N0₃⁻-N content represented about 15% (~ 20 kg N ha⁻¹) of the total N in the plant when cover crops were planted in August and autumn soil mineral N content (0-60 cm) was about 200 kg N ha⁻¹ or more. The proportion of NH₄⁺-N averaged only 3%. Spring species can be included in winter cropping systems in western Lower Fraser Valley. Spring species that were planted in August and winter-killed in late autumn showed greater potential to retain the N accumulated before winter-kill compared to the cover crops that were planted a month later. August-planted spring species increased soil mineral N (by 40 to 76%) in the 0-60 cm layer in spring relative to fallow plots while September-planted crops had little effect. It appears, spring species can play a significant role in autumn mineral N conservation by accumulating large amounts of autumn soil mineral N before winter leaching period, retaining it in winter-killed residues until spring and releasing the N in plant available form through decomposition and mineralization.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.794
Threshold uncertainty score0.409

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.007
GPT teacher head0.176
Teacher spread0.170 · 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 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

Citations3
Published2009
Admission routes1
Has abstractyes

Explore more

Same venuecIRcle (University of British Columbia)→Same topicSoil Carbon and Nitrogen Dynamics→French-language works237,207→