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Record W2971510293 · doi:10.2134/agronj2019.04.0275

Nutrient Cycling in Organic Field Crops in Canada and the United States

2019· article· en· W2971510293 on OpenAlexaboutno aff
Patrick M. Carr, Michel A. Cavigelli, Heather Darby, Kathleen Delate, Jed O. Eberly, Greta Gramig, Joseph R. Heckman, Ellen B. Mallory, Jennifer R. Reeve, Erin Silva, David H. Suchoff, Alex Woodley

Bibliographic record

VenueAgronomy Journal · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsSoil fertilityCover cropEnvironmental scienceAgronomyNutrient managementManureGreen manureAgroforestryNutrient cycleCrop rotationNutrientCropSoil waterBiologyEcologySoil science

Abstract

fetched live from OpenAlex

Organic farmers have identified soil fertility and weed management as the two highest research priority areas. No review exists of research on soil nutrient management in organic field crop systems. We conducted a comprehensive review to identify the principles and factors governing nutrient management, knowledge gaps, and future research needs in organic grain and other field crop systems in Canada and the United States. We compared results from research conducted in different climates, soils, and crop rotational sequences. Results indicate that (i) dual‐use cover/green manure crops and/or animal manure are the most common sources of plant available N and other nutrients in organic field crop systems; (ii) soil nutrient deficiencies can develop through sole reliance on cover/green manure crops; (iii) dependence on animal manure can lead to N and P excesses; (iv) conventional soil testing procedures may not accurately predict crop nutrient needs; (v) greater knowledge of microbial processes governing nutrient cycling is needed; and (vi) better understanding of the impact of weeds on soil fertility may create weed and nutrient management synergies. Knowledge gaps include a lack in understanding of how the soil and plant biomes influence nutrient‐use efficiency and how crop diversity and rotations impact soil fertility, sustainability, and resilience in organic field crop systems. Likewise, interactions between weeds, crops, soil fertility, and weed management strategies are poorly understood. Core Ideas Soil, climate, fertility sources, and land use impact organic nutrient management strategies. Cover/green manure crops and animal manures are used to maintain soil fertility on organic farms. Conventional soil testing may not be ideally suited to organic systems. Tracking soil nutrient temporal changes can improve comprehensive nutrient management plans. More research of how weeds and soil microbial community structure/function impact nutrient cycling and crop production is needed.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.027
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.005
GPT teacher head0.170
Teacher spread0.165 · 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

Citations29
Published2019
Admission routes1
Has abstractyes

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