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Record W1971998253 · doi:10.1155/2014/384604

Managing Soil Biota-Mediated Decomposition and Nutrient Mineralization in Sustainable Agroecosystems

2014· article· en· W1971998253 on OpenAlexafffund
Joann K. Whalen

Bibliographic record

VenueAdvances in Agriculture · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNutrientMineralization (soil science)Environmental scienceSoil biologyCrop residueAgroecosystemNutrient cycleAgronomyFertilizerSustainable agricultureAgricultureEcologyBiologySoil waterSoil science

Abstract

fetched live from OpenAlex

Transformation of organic residues into plant-available nutrients occurs through decomposition and mineralization and is mediated by saprophytic microorganisms and fauna. Of particular interest is the recycling of the essential plant elements—N, P, and S—contained in organic residues. If organic residues can supply sufficient nutrients during crop growth, a reduction in fertilizer use is possible. The challenge is synchronizing nutrient release from organic residues with crop nutrient demands throughout the growing season. This paper presents a conceptual model describing the pattern of nutrient release from organic residues in relation to crop nutrient uptake. Next, it explores experimental approaches to measure the physical, chemical, and biological barriers to decomposition and nutrient mineralization. Methods are proposed to determine the rates of decomposition and nutrient release from organic residues. Practically, this information can be used by agricultural producers to determine if plant-available nutrient supply is sufficient to meet crop demands at key growth stages or whether additional fertilizer is needed. Finally, agronomic practices that control the rate of soil biota-mediated decomposition and mineralization, as well as those that facilitate uptake of plant-available nutrients, are identified. Increasing reliance on soil biological activity could benefit crop nutrition and health in sustainable agroecosystems.

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 score0.238
Threshold uncertainty score0.947

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.003
GPT teacher head0.203
Teacher spread0.200 · 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

Citations44
Published2014
Admission routes2
Has abstractyes

Explore more

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