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Record W2898326978 · doi:10.1002/9781119289470.ch18

Effect of Hexanal Vapor Treatments on Delay of Flower Senescence

2018· other· en· W2898326978 on OpenAlexaff
Priya Padmanabhan, Gopinadhan Paliyath

Bibliographic record

Venuenot available
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicFlowering Plant Growth and Cultivation
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsHexanalCarnationPostharvestPetalHorticultureFloricultureVase lifeBotanyBiologyChemistryCultivarFood science

Abstract

fetched live from OpenAlex

Floriculture is a major avenue of income for many people across the world. The senescence process in most flowers is essentially similar to that in fruits, initiated by ethylene and involving the catabolic breakdown of phospholipids. The carnation flower system is an ideal model system for studying the effect of compounds that may enhance the shelf-life and quality of flowers. Hexanal vapor treatment of carnation flowers at the tight bud stage delayed their development and flower opening. The spray application of hexanal compositions did not have any effect on the development of carnations. Postharvest hexanal vapor treatment of cut roses delayed flower opening and enhanced the visual appeal of flowers. Hexanal treatment appeared to enhance the quality of chrysanthemums flowers. The flowers were much larger and more appealing than those in the control and 1-methylcyclopropene treated sets.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.996

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)0.0050.000

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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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.

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

Citations0
Published2018
Admission routes1
Has abstractyes

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