MétaCan
Menu
Back to cohort
Record W2086067825 · doi:10.4141/p06-109

Prince Edward Island growers can reduce soil phosphorus buildup while maintaining carrot crop yield

2006· article· en· W2086067825 on OpenAlexaffvenueabout
Kevin Sanderson, J. B. Sanderson

Bibliographic record

VenueCanadian Journal of Plant Science · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsDaucus carotaPodzolAgronomyFertilizerYield (engineering)LoamPhosphorusCropEnvironmental scienceSoil waterCrop yieldField experimentNutrientMathematicsChemistryBiologySoil science

Abstract

fetched live from OpenAlex

Producers seek to manage the application of nutrients in a manner that maximizes economic crop returns; however, emphasis must now include sensitivity to environmental issues such as increasing soil phosphorus. To address this issue in carrot (Daucus carota L.) production, we studied the effect of soil-applied P fertilizers on yield and soil P content in Prince Edward Island. Six field studies over a 3-yr period evaluated the yield response of carrot on sandy to loamy sand Orthic Podzol soils. Treatments consisted of pre-plant broadcast applied P at 0, 33, 66, 99 or 132 kg ha -1 on sites where residual P levels ranged from 81 to 162 µg P g -1 . When the total yield response of carrots to increasing P levels was fitted to a quadratic response curve, 110 kg P ha -1 was required to achieve maximum yield, but an application of as little as 22 kg P ha -1 resulted in 95% of maximum marketable yield. This reduced application rate resulted in a saving of 88 kg P ha -1 and slowed the buildup of soil P levels. Therefore, by applying more conservative amounts of P fertilizer carrot growers can maintain excellent crop yield while reducing the potential for environmental damage caused by the buildup of soil P. Key words: Orthic Podzol soil P, tissue P, fertilizer P, maximum yield, Daucus carota L.

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)0.001
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 score0.445
Threshold uncertainty score0.875

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.199
Teacher spread0.182 · 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

Citations5
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Plant ScienceSame topicCrop Yield and Soil FertilityFrench-language works237,207