MétaCan
Menu
Back to cohort
Record W2010787334 · doi:10.2135/cropsci2012.01.0052

Agronomic Performance of Spring Wheat as Related to Planting Date and Photoperiod Response

2012· article· en· W2010787334 on OpenAlexaffabout
S. P. Lanning, Pierre Hucl, Michael Pumphrey, Arron H. Carter, P. F. Lamb, G. R. Carlson, David M. Wichman, K. D. Kephart, Dean Spaner, John M. Martin, L. E. Talbert

Bibliographic record

VenueCrop Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsUniversity of AlbertaUniversity of Saskatchewan
FundersMontana Board of Research and Commercialization Technology
KeywordsSowingphotoperiodismBiologyCultivarLocus (genetics)Grain yieldAgronomyPoaceaeSpring (device)Yield (engineering)HorticultureWinter wheatBotanyGenetics

Abstract

fetched live from OpenAlex

ABSTRACT Photoperiod response impacts the adaptation of spring wheat ( Triticum aestivum L.) to specific areas of the world. Both photoperiod sensitive (PS) and photoperiod insensitive (PI) cultivars are grown successfully in the northern regions of the western United States and the Canadian plains. The goal of the present experiment was to determine the relative performance of PI and PS genotypes as related to planting date and to interpret results in view of climate trends for the region. Three sets of near‐isogenic lines that differed for alleles at the Ppd‐D1 locus for photoperiod sensitivity were tested at three planting dates in 15 environments in Montana, Washington, Saskatchewan, and Alberta. Results showed that PS lines headed later than PI lines at all planting dates. Grain yield was significantly greater for PS lines at the first two planting dates although no difference between PS and PI lines occurred for the latest planting date. Our results suggest that PS lines are superior to PI lines for this region. This difference is likely to be significant for regional adaptation as planting date becomes earlier due to increasing spring temperatures.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.194

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 head0.014
GPT teacher head0.231
Teacher spread0.216 · 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 designBench or experimental
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

Citations21
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueCrop ScienceSame topicWheat and Barley Genetics and PathologyFrench-language works237,207