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Record W1986991432 · doi:10.2134/agronj2006.0355c

The Early History of Wheat Improvement in the Great Plains

2008· article· en· W1986991432 on OpenAlexaboutno aff
Gary M. Paulsen, J. P. Shroyer

Bibliographic record

VenueAgronomy Journal · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarAgronomyAgricultural experiment stationGeographyAgricultureWhite (mutation)BiologyArchaeology

Abstract

fetched live from OpenAlex

More than 60% of U.S. wheat is grown in the Great Plains. Three classes of common wheat ( Triticum aestivum L.)—hard red spring, hard red winter, and hard white—and durum ( T. turgidum L. var. durum ) occupy 16 million ha in the region and provide most of the U.S. grain for baked goods and pasta. This article relates the early history of the four classes and the key persons involved in their establishment. Pioneers faced many difficulties in settling the Plains, but the need for adapted cultivars was paramount. Three cultivars—‘Red Fife’ hard red spring wheat, ‘Turkey’‐type hard red winter wheat, and ‘Kubanka’ durum wheat—were the foundation for the industry. Red Fife was selected by D.A. Fife of Ontario in 1842. The cultivar spread to the northern U.S. Plains during the 1860s and dominated production for 40 yr. Turkey hard red winter wheat was introduced to Kansas by Mennonite settlers from the Ukraine, particularly B. Warkentin, in 1873 and was advanced by C.C. Georgeson, who recognized its potential. Another cultivar, ‘Kharkof’, introduced by M.A. Carleton in 1900, stimulated spread of the class throughout the Plains. Carleton also introduced Kubanka in 1900 and promoted its utilization to start the U.S. durum industry. The most recent class, hard white wheat, was initiated by E.G. Heyne and approved by the USDA in 1990. These wheats transformed American agriculture by opening a vast area for production, shifting the center of cultivation to the Plains, and changing the country into a major grain exporter.

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 score0.708
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.237
Teacher spread0.193 · 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
Published2008
Admission routes1
Has abstractyes

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