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Record W2060082864 · doi:10.4141/p02-189

Season of year effect on response of orchardgrass to N fertilizer in a maritime climate

2004· article· en· W2060082864 on OpenAlexvenueno aff
Shabtai Bittman, Bernie J. Zebarth, C. G. Kowalenko, Derek Hunt

Bibliographic record

VenueCanadian Journal of Plant Science · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil Carbon and Nitrogen Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsFertilizerCropNitrateAgronomyDactylis glomerataAmmonium nitrateYield (engineering)Animal scienceGrowing seasonEnvironmental scienceChemistryBiologyPoaceaeEcology

Abstract

fetched live from OpenAlex

This study compared the response of harvests taken in May, June, August and September-October in terms of crop responses (yield, N uptake, and concentrations of crude protein and nitrate) to N fertilizer and residual soil nitrate and ammonium. Three trials were conducted in south coastal British Columbia in 1990–1992 to evaluate the response of an established sward of orchardgrass (Dactylis glomerata L.) to a range of N fertilizer rates. Both yields and daily crop growth rates were highest in cut 1, lowest in cut 4 and intermediate in cuts 2 and 3. For all four cuts, 95 and 90% of maximum yield was attained at about 136 and 82 kg ha-1 of applied N, respectively. Crop N supply from non-fertilizer sources ranged from 36 to 90 kg N ha-1, of which about 52% was attributed to nitrate present in the soil prior to growth and about 48% was N released from the soil, translocated from roots or deposited from the atmosphere. At 95% of maximum yield, crude protein concentrations ranged from 147 g kg-1 in the higher yielding cut 1 to 189 g kg-1 in cuts 2 and 4, while at 90% of maximum yield concentrations were 10 g kg-1 lower in each cut. Plant nitrate concentrations were close to levels that are toxic to cattle for the 95% target yield, but relatively safe at the 90% yield. The crop removed about 50 kg ha-1 more N when fertilized for 95% of maximum yield than for 90%, which translates to over 300 kg ha-1 more crude protein. High relative yield leaves behind more soil nitrate after harvest. The results suggest that the first cut should be managed for 95% of maximum yield with about 130 kg N ha-1. Cuts 2 and 3 should be managed for 90% of maximum yield, to avoid high plant nitrate concentrations, with 100–110 kg N ha-1. Cut 4 should be given no more than 50 kg N ha-1 for less than 90% of maximum yield because of the risk of residual soil nitrates. This study shows for the first time the benefits and disadvantages of applying N at different rates for each harvest over the growing season. Key words: Plant nitrate, nitrogen use efficiency, nitrogen recovery, Dactylis glomerata, relative yield, maximum economic yield

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

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 head0.010
GPT teacher head0.214
Teacher spread0.203 · 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

Citations10
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Plant Science→Same topicSoil Carbon and Nitrogen Dynamics→French-language works237,207→