MétaCan
Menu
Back to cohort
Record W2947920935 · doi:10.71318/apom.2002.56.4.219

Gibberellic Acid Increases Fruit Firmness, FruitSize, and Delays Maturity of ‘Sweetheart’ SweetCherry

2002· article· en· W2947920935 on OpenAlexaboutno aff
Frank Kappel, Richard A. MacDonald

Bibliographic record

VenueJournal of American Pomological Society · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGibberellic acidBiologyMaturity (psychological)HorticultureRipeningBotanyGermination

Abstract

fetched live from OpenAlex

Growers in British Columbia, Canada and the US Pacific Northwest use gibberellic acid (GA 3) to improve fruit quality of sweet cherries ( Prunus aviumL.). A single spray application of about three weeks before harvest has become the standard procedure. The objective of this trial was to determine if multiple applications of GA 3can further increase fruit firmness and size, and delay maturity of ‘Sweetheart’ sweet cherry, the second most important sweet cherry cultivar in British Columbia. Yield was not affected by a single application of 20 or 30 ppm or two or three weekly applications of 10 ppm GA 3in any of the three years of the trial. Fruit treated with GA 3were significantly firmer than fruit not treated; however, there were no differences in fruit firmness amongst the single or multiple GA 3treatments. Titratable acidity of GA 3-treated fruit was significantly higher than that of untreated fruit. There were no differences in titratable acidity within the GA 3treated fruit. Fruit treated with GA 3were significantly larger than untreated fruit and the fruit treated with 20 ppm GA 3were larger than the fruit treated with 30 ppm GA 3(single applications). In summary, GA 3-treated fruit could be harvested later and were larger and firmer than untreated fruit. There was no benefit to multiple applications of GA 3relative to a single application.

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 score0.858
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.223
Teacher spread0.197 · 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

Citations52
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of American Pomological SocietySame topicPlant Physiology and Cultivation StudiesFrench-language works237,207