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Record W1983589118 · doi:10.2135/cropsci2011.01.0039

Tiller Characteristics of Timothy and Tall Fescue in Relation to Herbage Mass Accumulation

2012· article· en· W1983589118 on OpenAlexaff
Perttu Virkajärvi, Kirsi Pakarinen, Maarit Hyrkäs, Mervi Seppänen, Gilles Bélanger

Bibliographic record

VenueCrop Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsAgriculture and Agri-Food Canada
FundersMaa- ja MetsätalousministeriÖ
KeywordsTiller (botany)AgronomyBiologyYield (engineering)Festuca arundinaceaDry matterField experimentPoaceae

Abstract

fetched live from OpenAlex

ABSTRACT Herbage dry matter (DM) yield of grasses is a function of the density and size of vegetative (VEG), generative (GEN), and elongating vegetative (ELONG) tillers. We determined the contribution of these three tiller types to DM yield accumulation along with their main morphological characteristics on three sampling dates during each of the primary growth and the regrowth of field‐grown swards of timothy ( Phleum pratense L.) and tall fescue ( Festuca arundinacea Schreb.). Our results provide the first quantitative characterization of ELONG tillers, which contributed to timothy DM yield by up to 28% in primary growth and 58% in regrowth. In tall fescue, VEG tillers were dominant in primary growth and regrowth (74 to 100% of DM yield). The GEN tillers were dominant (67 to 74% of DM yield) in the primary growth of timothy while in the regrowth, VEG tillers were dominant early (84% of DM yield) but ELONG tillers represented 58% of DM yield later on. Timothy and tall fescue had similar rates of DM accumulation. The greater DM yield on all sampling times of the regrowth of tall fescue confirms a greater growth before the first sampling, most likely due to the greater proportion of VEG tillers. The GEN tillers were large with low leaf to weight ratio (LWR) and proportion of attached senesced material whereas VEG tillers were small with high LWR and large proportion of attached senesced material. The ELONG tillers were intermediate in size and LWR but they had a low proportion of attached senesced material.

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 score0.827
Threshold uncertainty score0.080

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 head0.042
GPT teacher head0.281
Teacher spread0.238 · 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

Citations31
Published2012
Admission routes1
Has abstractyes

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