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Record W2059924980 · doi:10.2135/cropsci2011.05.0279

Wheat Production in the High Winter Stress Climate of the Great Plains of North America—An Experiment in Crop Adaptation

2011· article· en· W2059924980 on OpenAlexafffundabout
Brian Fowler

Bibliographic record

VenueCrop Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of Saskatchewan
FundersMinistry of Agriculture - SaskatchewanDucks Unlimited Canada
KeywordsOverwinteringAgronomyPopulationCultivarCropBiologyYield (engineering)Winter wheatCrop yieldAgroforestryGeographyEcologyDemography

Abstract

fetched live from OpenAlex

ABSTRACT The traditional winter wheat ( Triticum aestivum L.) production area on the North American Great Plains extended as far north as southern Alberta, Canada. This paper reviews a research and development program initiated with the objective of expanding production north and east into higher winter stress areas of the Canadian prairies. Winter survival was considered the main limitation to production in this region. However, the widespread adoption of no‐till seeding into standing stubble for snow trapping has proven to be a successful method of overwintering wheat if cold hardy cultivars are grown using recommended management practices. Plant breeding improvements have increased production potential and winter wheat has become western Canada's third largest wheat class. Average commercial yields of 149, 125, and 118% of spring wheat in Manitoba, Saskatchewan, and Alberta, respectively, have demonstrated the high yield potential that can be realized while employing environmentally sustainable crop management practices. In light of current environmental concerns, changing weather patterns, diminishing world wheat reserves, and an ever increasing global population to feed, one would assume that winter wheat production in western Canada would be widely embraced. However, marketing obstacles and difficulties inserting winter wheat into rotations, both of which have a direct influence on farmers’ net returns, remain to be overcome for this potential to be fully realized.

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)0.000
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 score0.621
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.044
GPT teacher head0.243
Teacher spread0.199 · 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

Citations36
Published2011
Admission routes3
Has abstractyes

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