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Effect of Hot Water Treatments on Quality of Highbush Blueberries

2008· article· en· W2106078558 on OpenAlexaff
Lihua Fan, Charles F. Forney, Jun Song, Craig Doucette, M.A. Jordan, K. B. McRae, Brad Walker

Bibliographic record

VenueJournal of Food Science · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsTitratable acidBotrytis cinereaHorticulturePopulationChemistryMohoAnimal scienceBotanyBiologyFungi imperfectiMedicine

Abstract

fetched live from OpenAlex

Highbush blueberries, cv 'Burlington', were treated with 22, 45, 50, or 60 degrees C water for 15 or 30 s along with an untreated control. Fruit were then stored for 0, 1, 2, or 4 wk at 0 degrees C and 2 or 9 d at 20 degrees C prior to evaluation of microbial population and fruit quality. After 4 wk of storage, the hot water treatment at 60 degrees C resulted in 92% marketable berries, followed by 90% at 50 degrees C, 88% at 45 degrees C, and 83% at 22 degrees C compared with 76% in untreated controls. Decay incidence was reduced to 0.6%, 1.2%, 1.4%, or 2.8% with 60, 50, 45, or 22 degrees C water treatments, respectively, compared with 5.1% in controls following 4 wk at 0 degrees C and 2 d at 20 degrees C. After an additional 7 d at 20 degrees C, decay in fruit treated at 60 degrees C for 15 or 30 s remained at 1.8% and 0.4%, respectively, compared to 37.4% in controls. Weight loss of berries treated with hot water was 0.4% against 3.8% in controls, and shriveled and split berries were also reduced compared to controls (P<0.001). Aerobic plate count and yeast and mold count were reduced by 0.45 to 0.7 log at 60 degrees C for 30 s. Botrytis cinerea and Colletotrichum sp. were the dominant fungal pathogens causing decay of Burlington blueberries during storage. Hot water treatments also immediately induced an increase in ethanol and reduced fruit titratable acidity and soluble solids content, but had no significant effect on fruit firmness, pH, or most flavor volatile concentrations.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.179

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.062
GPT teacher head0.297
Teacher spread0.236 · 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

Citations39
Published2008
Admission routes1
Has abstractyes

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