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Record W2255039690 · doi:10.21273/hortsci.40.4.1004b

(30) Edaphic Factors on Crack Development of Cut and Peel Carrots

2005· article· en· W2255039690 on OpenAlexaff
P. J. Joy, Rajasekaran R. Lada, Cameron Fullerton, Brian Williams, Angus Ells

Bibliographic record

VenueHortScience · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPostharvest Quality and Shelf Life Management
Canadian institutionsOxford Frozen Foods (Canada)Nova Scotia Department of Agriculture
Fundersnot available
KeywordsEdaphicMaterials scienceComposite materialHorticultureEnvironmental scienceBiologySoil science

Abstract

fetched live from OpenAlex

The quick-frozen (QF) cut and peel processing industry is growing and has significant economical importance. Crack development formation (CDF) and enhancement is a major obstacle in QF carrot processing since it lowers product quality, profitability and consumer preference. Studies were initiated to determine the role of edaphic factors on crack development. Carrot samples (var. Sugarsnax) were collected from nine different fields before processing, after processing, and after 8 weeks of -8 °C freezer storage. Samples were tested for the percent cracked; the length, width, and depth of cracks; and membrane stability using electrical conductivity per gram (EC/g). Membrane injury index (MII) was also analyzed on freezer-stored samples. Very few cracks and low EC readings were observed in treatments prior to processing, with the exception of field VC38. Samples taken at the end of the processing line had a higher percentage of visual cracks and significant differences were found between fields in EC/g and length, but not in width or depth of cracks. Freezer-stored samples had significant differences in all parameters, including EC/g, MII, crack length, width, and depth, indicating that the length of freezer storage time can increase the potential for crack development. Samples from V49 cracked heavily during 8 weeks in freezer storage compared to the samples from other fields. A significant interaction between field and time was also observed in processed samples, indicating that CDF is dependent on both field parameters and freezer storage time. Significant differences were observed among different fields in terms of crack morphology, especially after 8 weeks in freezer storage.

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 score0.725
Threshold uncertainty score0.196

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 head0.048
GPT teacher head0.249
Teacher spread0.201 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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