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Record W2548870073 · doi:10.21273/hortsci.35.3.409c

118 1-MCP Controls Superficial Scald and Delays Softening in `Cortland' Apples

2000· article· en· W2548870073 on OpenAlexaff
Jennifer R. DeEll, H.P. Vasantha Rupasinghe, Dennis P. Murr

Bibliographic record

VenueHortScience · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
Keywords1-MethylcyclopropeneHorticultureSofteningRipeningCultivarChemistryEthyleneToxicologyBiologyMathematics

Abstract

fetched live from OpenAlex

`Cortland' is an apple cultivar with inherent poor storeability because of excessive vulnerability to the development of superficial scald in long-term storage. The objectives of this investigation were to evaluate the potential of the potent ethylene action inhibitor 1-methylcyclopropene (1-MCP; EthylBloc®) to counteract this constraint and to develop some basic procedures for its exposure. Eight hours after harvest, fruit were exposed to 1.0 mL·L –1 1-MCP for 0, 3, 6, 9, 12, 16, 24, or 48 h at 3, 13, or 23 °C. Following exposure, fruit were placed at 0 to 1 °C in air for 120 days, after which time they were removed to 20 °C and held 7 days for post-storage assessment of ripening and to allow development of physiological disorders. In general, and within our experimental limits, the higher the temperature of 1-MCP exposure the shorter the required exposure time to obtain similar effects. The desired effectiveness of 1-MCP could be achieved by exposing fruit for at least 3 h at 23 °C, for 6 h at 13 °C, or for 9 h at 3 °C. 1-MCP-treated apples were consistently 2 kg firmer than untreated apples. Scald incidence in untreated fruit after 120 days at 0 to 1 °C and 7 days at 20 °C was 100%, whereas 1-MCP reduced scald by 95% in treatments of long enough duration at any particular temperature.

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 score0.712
Threshold uncertainty score0.266

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 head0.011
GPT teacher head0.192
Teacher spread0.181 · 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

Citations2
Published2000
Admission routes1
Has abstractyes

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