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Record W2043565582 · doi:10.2135/cropsci2013.01.0055

Sparse‐Flowering Orchardgrass is Stable Across Temperate North America

2013· article· en· W2043565582 on OpenAlexaff
Michael D. Casler, Y. A. Papadopolous, Shabtai Bittman, R. D. Mathison, Doohong Min, Joseph G. Robins, J. H. Cherney, S. N. Acharya, D. P. Belesky, S. R. Bowley, Bruce Coulman, R. Drapeau, Nancy Ehlke, M. H. Hall, Richard H. Leep, R. Michaud, J. Rowsell, G.E. Shewmaker, Chris D. Teutsch, W.K. Coblentz

Bibliographic record

VenueCrop Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of SaskatchewanUniversity of GuelphAgriculture and Agri-Food CanadaNova Scotia Department of Agriculture
Fundersnot available
KeywordsCultivarBiologyForageDactylis glomerataTemperate climatePanicleAgronomyGermplasmYield (engineering)RuminantPoaceaeCropBotany

Abstract

fetched live from OpenAlex

ABSTRACT Orchardgrass ( Dactylis glomerata L.) is a major component of many pastures in temperate North America. Early and profuse flowering in pastures is problematic due to livestock refusal to consume flowering stems. The objective of this research was to determine the stability and agronomic impact of recently developed sparse‐flowering orchardgrass populations across temperate North America. Six cultivars, three sparse flowering and three normal flowering, were grown at 21 locations in temperate North America and evaluated for panicle density, heading date, and forage yield. Sparse‐flowering cultivars had 57% fewer panicles than normal‐flowering cultivars, but this effect was highly dependent on mean winter temperature, with normal‐flowering cultivars showing twice as much temperature sensitivity compared to sparse‐flowering cultivars. Forage yield of sparse‐flowering cultivars was reduced by approximately 24 to 32% for first harvest and 2 to 9% for regrowth harvests compared to normal‐flowering cultivars and this reduction in forage yield was independent of mean winter temperature. The forage yield reduction associated with sparse flowering is most likely due to a combination of physiological load (loss of stems) and opportunity cost (lack of selection pressure for yield), suggesting an opportunity to improve forage yield potential of this sparse‐flowering germplasm pool.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score1.000

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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.027
GPT teacher head0.253
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

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

Citations6
Published2013
Admission routes1
Has abstractyes

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