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Record W6958965019 · doi:10.7939/r3-gf4e-1v23

Best Management Practices for Implementing Ultra-Early Spring Wheat (Triticum aestivum L.) Growing Systems on the Northern Great Plains

2023· dissertation· en· W6958965019 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2023
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSowingYield (engineering)CultivarGrain yieldGrowing seasonSpring (device)

Abstract

fetched live from OpenAlex

Ultra-early planting of spring wheat (Triticum aestivum L.) between soil temperatures of 0°C and 7.5°C on the northern Great Plains allows the exploitation of longer growing seasons and the avoidance of the onset of extreme heat later in the season during sensitive physiological growth stages, including flowering and grain filling. Recent studies in western Canada assessed ultra-early planting, and the management practices and wheat cultivars required to successfully implement ultra-early wheat planting on the northern Great Plains. Planting wheat between soil temperatures of 2°C and 6°C optimized grain yield and grain yield stability in western Canada. Planting between 0°C and 7.5°C always resulted in greater grain yield and grain yield stability than delaying planting to a conventional planting time at 10°C soil temperature or higher. Current commercial Canadian hexaploid spring wheat varieties exhibited improved grain yield and grain yield stability when planted ultra-early. No differential in grain yield stability was present between specially-developed cold tolerant wheat lines and current commercial Canadian hexaploid spring wheats. When assessed at ultra-early and conventional planting times, no individual cultivar or group of cultivars representing a Canadian wheat market class, had greater grain yield or grain yield stability when planting was delayed to the conventional time. The grain yield and grain yield stability of ultra-early planted wheat can be improved with the implementation of optimized management practices in an ultra-early wheat growing system. An optimal sowing density of 400 seeds m-2 increased grain yield as well as grain yield stability for ultra-early planted wheat. Shallow sowing depths (2.5 cm) did not affect grain yield, but when assessed in combination with optimal sowing rates, improved grain yield stability of ultra-early planted wheat. Spring weed management using fall-applied residual herbicides reduced early season weed pressure, increased grain yield in some locations, and did not negatively affect grain yield stability of ultra-early planted wheat. An optimized growing system for ultra-early planted wheat on the northern Great Plains includes a regionally adapted, competitive, Canadian hexaploid spring wheat cultivar, planted at 2.5 cm depth when soil temperatures are between 2°C and 6°C, at an optimal sowing density of not less than 400 viable seeds m-2. Fall-applied residual herbicides can be safely used in the growing system to manage spring weed pressure if required. Ultra-early wheat growing systems can be immediately implemented to increase grain yield and grain yield stability on the northern Great Plains. Producers adopting ultra-early wheat growing systems will realize additional grain yield and grain yield stability benefits relative to conventional planting with the increases of daily average temperatures and atmospheric CO2 concentrations predicted to occur over the next thirty years.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.990

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.207
Teacher spread0.183 · 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 designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

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