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THE USE OF A NATURAL CLAY ADSORBENT IMPROVES QUALITY RETENTION IN THREE CULTIVARS OF RASPBERRIES STORED IN MODIFIED ATMOSPHERE PACKAGES1

2002· article· en· W2152502458 on OpenAlexaffabout
P.M.A. Toivonen, Chaim Kempler, S. Stan

Bibliographic record

VenueJournal of Food Quality · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsAdsorptionRipeningModified atmosphereRubusChemistryAtmosphere (unit)CultivarHorticultureFood scienceShelf lifeOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Abstract The effect of a natural clay adsorbent on quality retention in modified atmosphere packaged raspberries (Rubus idaeus L., cvs‘Chilliwack’, ‘Malahat‘, and ‘Qualicum‘) was tested. Fruit packaged with the natural clay adsorbent was much firmer, had less decay, and had fewer dark red overripe fruit after 14 days than those packaged without any adsorbent. The addition of the natural clay adsorbent almost eliminated all the condensation inside the package after 14 days of storage at 1C. The reduction in decay on the fruit could be attributed to the reduction in condensed water in the package. However, effects on firmness retention and the slowing of ripening of the fruit could not be attributed to any measured effect of the clay in this study. The results suggest that a water/ volatiles adsorbent, such as the natural clay used in this study, could be useful in prolonging the shelf‐life and improving the quality of modified atmosphere packaged red raspberries grown in a wet climate.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.166
GPT teacher head0.294
Teacher spread0.128 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2002
Admission routes2
Has abstractyes

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