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Record W2077965638 · doi:10.1002/jsfa.3851

Effect of short‐term air storage after removal from controlled‐atmosphere storage on apple and fresh‐cut apple quality

2010· article· en· W2077965638 on OpenAlexaff
P.M.A. Toivonen, Paul A. Wiersma, C.R. Hampson, Brenda Lannard

Bibliographic record

VenueJournal of the Science of Food and Agriculture · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsShelf lifeControlled atmosphereHorticultureChemistryCold storageRespirationModified atmospherePostharvestRespiration rateFood scienceBotanyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: One of the realities of apple distribution for long-term stored fruit is that a controlled-atmosphere (CA) storage room will be unsealed and fruit held in air storage and marketed over several weeks. This work was conducted to determine the effect of post-CA air storage of whole fruit on potential shelf life for fresh-cut apple slices. RESULTS: Fresh-cut slices of 'Spartan' and 'Delicious' apples held in post-CA air storage for 2 or 4 weeks showed the least changes in cut surface color as compared with those made from apples immediately on removal from CA. Shelf life was most improved by post-CA air storage in the 'Spartan' apples, which were more advanced in maturity as compared with the 'Delicious' apples. Internal ethylene concentration, firmness, and respiration changed significantly with post-CA air storage, suggesting a relationship between physiological status of the whole fruit and shelf life of slices made from that fruit. CONCLUSION: The results support the hypothesis that apples had suppressed physiological activity in CA storage and are susceptible to accelerated deterioration upon cutting. Holding fruit for 2 weeks in air storage allowed recovery of physiological activity, which resulted in greater resistance to deterioration in response to fresh-cut processing.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.740
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.235
Teacher spread0.225 · 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 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

Citations11
Published2010
Admission routes1
Has abstractyes

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