MétaCan
Menu
Back to cohort
Record W2047254508 · doi:10.2134/agronj2012.0283

Yield and Protein Response of Wheat Cultivars to Polymer‐Coated Urea and Urea

2012· article· en· W2047254508 on OpenAlexaboutno aff
Bhupinder S. Farmaha, Albert L. Sims

Bibliographic record

VenueAgronomy Journal · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsUreaCultivarAgronomyCoated ureaYield (engineering)Growing seasonBiologyGrain yieldNitrogenChemistryMaterials scienceBiochemistryMetallurgy

Abstract

fetched live from OpenAlex

Discount payments associated with low grain protein concentration in hard red spring wheat (HRSW, Triticum aestivum L.) in recent years has increased interest for using controlled‐release N fertilizers to increase protein concentration while maintaining optimal grain yields. Field experiments were conducted during 6 site‐years in Minnesota from 2007 to 2009 to examine effects of a polymer‐coated urea (PCU, Environmentally Smart Nitrogen [ESN], Agrium Inc., Calgary, AB, Canada) and non‐coated urea on grain yields and protein concentrations of two HRSW cultivars, Alsen and Knudson, that vary in grain yield and protein concentration potentials. Polymer‐coated urea and urea were applied in spring at six rates that supplied 0 to 110 kg N ha −1 in 2007 and 0 to 168 kg N ha −1 in 2008 and 2009. Because of genetic differences, Knudson produced greater grain yield than Alsen in environments (site‐years), which were cooler and drier early in the growing season and the yield differences between the two cultivars increased with increasing N rates. In the same environment, PCU decreased grain yield compared with urea, which could be related to a reduced N release early in the growing season. Compared with urea, higher N (at Zadoks scale 85) and protein concentrations (at Zadoks scale 92) with PCU were observed due to increased N availability later during the growing season. To increase wheat protein concentrations from using PCU, future studies should evaluate different mixtures of PCU and urea.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.245

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 head0.023
GPT teacher head0.227
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 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

Citations37
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueAgronomy JournalSame topicCrop Yield and Soil FertilityFrench-language works237,207