MétaCan
Menu
Back to cohort
Record W2178964278 · doi:10.1017/s1742170515000423

Combinations of cover crop mixtures and bio-waste composts enhance biomass production and nutrients accumulation: a greenhouse study

2015· article· en· W2178964278 on OpenAlexaff
Aimé J. Messiga, Mehdi Sharifi, Sheena Munroe

Bibliographic record

VenueRenewable Agriculture and Food Systems · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsTrent University
Fundersnot available
KeywordsCover cropAgronomyNutrientCropBiomass (ecology)PhosphorusFertilizerAmendmentEnvironmental scienceShootNitrogenChemistryBiology

Abstract

fetched live from OpenAlex

Abstract Improved farming practices are needed to produce more food in a sustainable way. This study assessed 12 combinations of cover crop mixtures and amendment treatments and their effects on shoot and root dry (matter (DM) weights, nitrogen (N), phosphorus (P) and potassium (K) uptakes in plants, Mehlich-3 extractable P (P M3 ) and K (K M3 ). Shoot and root DM weights were increased by 30–63% with combinations of clover-based cover crop mixtures and 65 Mg ha −1 of municipal solid food waste (MSFW) compared with synthetic fertilizer. The combination of clover-based cover crop mixtures with MSFW increased N uptake by 38 and 30%, P uptake by 57 and 40% and K uptake by 77 and 77% compared with fertilized and unfertilized treatments, respectively. The combination of vetch-based cover crop mixtures with MSFW had no effect on N uptake, but increased P uptake on average by 43%, and K uptake on average by 11% compared with fertilized and unfertilized treatments. The highest soil P M3 and K M3 values were obtained with additions of MSFW, while the lowest were obtained with synthetic fertilizer indicating that the amount of P and K added with MSFW were greater than cover crop needs. Combining cover crop mixtures and MSFW at levels recommended for N fertilization allows meeting cover crops’ nutrient needs and increases biomass inputs to agricultural soils, but long-term monitoring of soil P is required to limit potential P build-up.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.533

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 head0.044
GPT teacher head0.263
Teacher spread0.219 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueRenewable Agriculture and Food SystemsSame topicAgronomic Practices and Intercropping SystemsFrench-language works237,207