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Record W2606981597 · doi:10.4141/cjps2011-204

Seasonal growth dynamics and carbon allocation of the wild blueberry plant (<i>Vaccinium angustifolium</i>Ait.)

2012· article· en· W2606981597 on OpenAlexaffvenue
Jatinder Kaur, David Percival, Lindsay J. Hainstock, Jean-Pierre Privé

Bibliographic record

VenueCanadian Journal of Plant Science · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBerry genetics and cultivation research
Canadian institutionsAgriculture and Agri-Food CanadaNova Scotia Department of Agriculture
Fundersnot available
KeywordsRhizomeVacciniumBerryPhenologyFructoseSucroseSugarBotanyShootGrowing seasonBiologyHorticultureChemistryFood science

Abstract

fetched live from OpenAlex

Kaur, J., Percival, D., Hainstock, L. J. and Privé, J.-P. 2012. Seasonal growth dynamics and carbon allocation of the wild blueberry plant ( Vaccinium angustifolium Ait.). Can. J. Plant Sci. 92: 1145–1154. Field studies were conducted at the Wild Blueberry Research Station, Debert, NS, to examine the carbon allocation dynamics within the wild blueberry (Vaccinium angustifolium Ait.). This was achieved with biweekly measurements of dry weight, soluble sugar and starch levels of the rhizomes, roots, stems/leaves and berries of plants in the vegetative (i.e., sprout phase) and cropping phases of production. Non-structural carbohydrate levels were determined using high-performance liquid chromatography (HPLC). Growth parameters included phenology, stem height, dry weights of the above-ground vegetation (stems and leaves), berries, rhizomes and roots. Interestingly, root growth was observed prior to upright shoot emergence and dry weight for rhizome remained higher compared with stems and leaves. The rhizomes acted as a carbohydrate source during stem and root growth. The developing berry crop appeared to be a strong sink for photo-assimilates, as berries were found to import sucrose and convert it to fructose and glucose during maturation, and HPLC studies further confirmed the increasing levels of fructose and glucose. Given the phenology of the wild blueberry, the results exemplify the importance of the rhizomes as a strong carbohydrate source, especially in the early stages of a growing season when the carbohydrate production is limited.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.981

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 head0.015
GPT teacher head0.202
Teacher spread0.186 · 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

Citations29
Published2012
Admission routes2
Has abstractyes

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