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Record W2167219880 · doi:10.4141/s06-016

Tillage and root heat stress in wheat in central Alberta

2007· article· en· W2167219880 on OpenAlexvenueaboutno aff
H. Wang, R. Lemke, T. Goddard, C. Sprout

Bibliographic record

VenueCanadian Journal of Soil Science · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
Fundersnot available
KeywordsTillageLoamAgronomyEnvironmental scienceGrowing seasonSoil waterBiologySoil science

Abstract

fetched live from OpenAlex

Heat stress occurs often in wheat on the Canadian Prairies especially during reproductive growth, which has markedly negative impacts on yield. As previous studies reported that wheat growth was affected more by heat stress in roots than in shoot, we suspected that the cooling effect of no-till (NT) on soil may reduce the risk of root heat stress and benefit the yield compared with conventional tillage (CT). Data were collected between 2000 and 2003 from a tillage study using a continuous wheat cropping system on a Thin Black Chernozemic clay loam in central Alberta. Consistently lower soil temperatures at 5 and 10 cm in NT than CT were observed in the whole growing season every year. At the grain growth stage, NT mitigated heat shock (>32°C at 5 cm) which occurred in 2001 and 2002 under CT and considerably reduced root heat stress index (HSI), calculated as accumulations of hourly soil temperatures greater than 20°C, every year compared with CT. By reducing root heat stress especially during the grain growth stage and slightly increasing pre-seeding soil moisture, no-till increased above-ground biomass (33–160%) and grain yield (18–147%) every year except 2003 when heat and water stress were relatively mild. Key words: Heat stress, soil temperature, no-till, conventional tillage, wheat, root

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 score0.733
Threshold uncertainty score0.748

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 studies0.0000.000
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 head0.012
GPT teacher head0.210
Teacher spread0.198 · 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

Citations34
Published2007
Admission routes2
Has abstractyes

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