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Record W1989866415 · doi:10.4141/cjps06001

Rate and time of fertilizer nitrogen application on yield, protein and apparent efficiency of fertilizer nitrogen use of spring wheat

2007· article· en· W1989866415 on OpenAlexfundvenueno aff
Bernie J. Zebarth, Elizabeth Botha, Harm van Rees

Bibliographic record

VenueCanadian Journal of Plant Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
FundersAgriculture and Agri-Food Canada
KeywordsFertilizerAgronomyNitrogenYield (engineering)Grain yieldCropAmmonium nitrateSeedingEnvironmental scienceMathematicsCrop yieldChemistryBiologyMaterials science

Abstract

fetched live from OpenAlex

Use of an in-season measurement of crop nitrogen (N) status to optimize fertilizer N management has been proposed as a means of optimizing yield of spring wheat while minimizing environmental N losses. This study determined the effect of the rate and time of fertilizer N application on the grain yield, grain protein, and apparent recovery of fertilizer N in grain and in the above-ground plant for spring wheat (Triticum aestivum L.) in 2001–2003, and evaluated the use of a SPAD-502 meter to measure crop N status in spring wheat. Sixteen N fertility treatments were used, including application of different rates of fertilizer N (0–160 kg N ha - 1 ) applied pre-seeding (ZGS 0), at tillering (ZGS 21) and at shooting (ZGS 32) as ammonium nitrate. Split N application provided no benefit in terms of grain yield or apparent recovery of fertilizer N. Application of fertilizer N at ZGS 32 reduced crop yield and apparent recovery of fertilizer N compared with N application at ZGS 0. Application of fertilizer N at ZGS 21 reduced yield and apparent recovery of fertilizer N in grain in 2 of 3 yr, but had no effect on apparent recovery of fertilizer N in the above-ground plant. Delayed fertilizer N application generally increased grain protein. Fertilizer N can be applied at ZGS 21 as required to optimize grain yield provided at least some fertilizer N is applied prior to seeding; however, crop N status cannot reliably be assessed at this time using a SPAD-502 meter. Crop N status can be assessed at ZGS 32 using a SPAD-502 meter; however, fertilizer N application at this time primarily influences grain protein rather than grain yield. These results highlight the need for a means of predicting soil N mineralization potential in order to optimize grain yield in humid environments where carry-over of soil nitrate from the previous growing season is limited. Key words: Triticum aestivum; N mineralization; soil N supply; SPAD-502 meter, leaf chlorophyll index

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.205
Teacher spread0.181 · 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 designBench or experimental
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

Citations37
Published2007
Admission routes2
Has abstractyes

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