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Record W2344742496 · doi:10.2135/cropsci2015.06.0351

Establishment and Impact of Cover Crops Intersown into Corn

2016· article· en· W2344742496 on OpenAlexafffundabout
Kimberly D. Belfry, Laura L. Van Eerd

Bibliographic record

VenueCrop Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsUniversity of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsCover cropVicia villosaAgronomyBiologyCropRaphanusCanopyMonocultureSowingBotany

Abstract

fetched live from OpenAlex

In temperate climates, corn (Zea mays L.) is often harvested too late for sufficient cover crop growth to meet grower objectives. This study was conducted to evaluate intersowing into standing corn in terms of cover crop establishment and growth and the impact on corn yield. Three experiments were conducted from 2009 to 2011 in southwestern Ontario sweet and hybrid seed corn production systems to assess timing of cover crop intersowing, utility of alfalfa (Medicago sativa L.) and 17 other cover crops species or multispecies mixes. In all 22 locations over 3 yr, corn yield was not affected in any of the three cover crop experiments. Sweet corn cover crop treatments exhibited poor stands of limited growth (<1% ground coverage) at corn harvest, attributed to sweet corn canopy closure. At seed corn harvest, early‐sown (corn V4–V6) cover crops accumulated 1116 kg ha−1 dry biomass and 42.4 kg N ha−1, which were 33% greater than the late‐sown (V10–V12) treatments. A lack of a cover crop effect compared with the no‐cover‐crop treatment in soil mineral N and corn yield indicates little N competition. Hairy vetch (Vicia villosa Roth), oilseed radish (OSR, Raphanus sativus L. var. oleoferus Stokes) and three of six cover crop blends were the only treatments to accumulate dry biomass over 1000 kg ha−1 by corn harvest. Of the cover crops evaluated, interseeding into hybrid seed corn production systems appears to be of little risk to yield and can provide ground cover during postharvest fallow periods.

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 score0.009
Threshold uncertainty score0.018

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 head0.020
GPT teacher head0.266
Teacher spread0.246 · 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

Citations60
Published2016
Admission routes3
Has abstractyes

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