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Record W2165480275 · doi:10.21273/horttech.16.2.0286

Carrot Yield, Quality, and Storability in Relation to Preplant and Residual Nitrogen on Mineral and Organic Soils

2006· article· en· W2165480275 on OpenAlexafffundabout
Sean M. Westerveld, Mary Ruth McDonald, A.W. McKeown

Bibliographic record

VenueHortTechnology · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgronomic Practices and Intercropping Systems
Canadian institutionsUniversity of Guelph
FundersAgricultural Adaptation CouncilMinistry of Agriculture, Food and Rural AffairsNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsAgronomyYield (engineering)NitrogenDaucus carotaEnvironmental scienceSoil waterNutrientAmmonium nitrateAmmoniumChemistryBiologySoil science

Abstract

fetched live from OpenAlex

The Nutrient Management Act (NMA) established in the province of Ontario in 2002 has prompted a re-evaluation of nitrogen (N) management practices. However, N management research in Ontario is currently outdated. The experiment in this 3-year study was designed to establish the yield response of carrot ( Daucus carota ) to N fertilization on mineral and organic soils and identify the relative yield effects of preplant and residual soil N. In 2002, N was applied at 0%, 50%, 100%, 150%, and 200% of recommended N application rates in Ontario as ammonium nitrate (organic soil: 60 kg·ha -1 preplant; mineral soil: 110 kg·ha -1 split 66% preplant/33% sidedress). Experimental units were split in half in 2003 and 2004, and N was applied to one half in 2003 and both halves in 2004 to identify the effects of residual N from the previous season on yield. Crop stand, yield, and quality were assessed at harvest, and storability was assessed by placing carrots into cold storage for 6 months. Nitrogen application rate had no effect on the yield, quality, or storability of carrots grown on organic soil. On mineral soil there were no effects of applied N in the first year of the 3-year study. In the second and third year on mineral soil, yield increased in response to increasing N, up to 200% and 91% of the recommended application rate, respectively, based on the regression equations. Yield declined above 91% of the recommended application rate in the third year due to a decrease in stand at higher N application rates. There were no effects of N on carrot quality or storability on mineral soil. On mineral soil, residual N from the 2002 season had more effect on yield at harvest in 2003 than N applied in 2003. This major effect of residual soil N on yield provides an explanation for the lack of yield response to preplant N application in previous studies conducted in temperate regions. These results indicate that there is no single N recommendation that is appropriate for all years on mineral soil. Assessing the availability of N from the soil at different depths at seeding is recommended to determine the need for N application.

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)0.001
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 score0.094
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.250
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 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

Citations21
Published2006
Admission routes3
Has abstractyes

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