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Record W2059338459 · doi:10.1080/10942912.2013.784332

Color, Mechanical, and Microstructural Properties of Vacuum Assisted Microwave Dried Saskatoon Berries

2013· article· en· W2059338459 on OpenAlexaffabout
S. Avanthika Nagalakshmi, Pranabendu Mitra, Venkatesh Meda

Bibliographic record

VenueInternational Journal of Food Properties · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsChewinessBerryMicrowaveMicrostructureMicrowave powerFood scienceMaterials scienceResponse surface methodologyDried fruitLightnessPorosityVacuum dryingComposite materialChemistryHorticultureFreeze-dryingChromatographyOpticsBiology

Abstract

fetched live from OpenAlex

Saskatoon berries were dried using a vacuum assisted microwave technique. Central composite rotate design and response surface methodology were used to develop the regression models and to study the influence of drying processing variables (microwave power, drying time, and fruit load) on color, mechanical properties, and microstructure of dried berries. All the three variables had significant effects on the above mentioned properties (p< 0.05). Drying affected the color at variable levels and increased the lightness of dried berries compared to frozen berries. Hardness, gumminess, and chewiness of dried berries increased and springiness and cohesiveness of dried berries decreased with microwave power and drying time. The porosity and the destruction level in the microstructure of dried berries increased with the microwave power. The findings of this study will be useful to identify desirable microwave-vacuum drying operating conditions for targeted dried Saskatoon berry products.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.040
GPT teacher head0.210
Teacher spread0.170 · 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 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

Citations20
Published2013
Admission routes2
Has abstractyes

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