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Record W2954354765 · doi:10.1080/10408398.2019.1632788

Review of recent applications and research progress in hybrid and combined microwave-assisted drying of food products: Quality properties

2019· review· en· W2954354765 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical Reviews in Food Science and Nutrition · 2019
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsMcGill University
FundersUniwersytet Warmińsko-Mazurski w Olsztynie
KeywordsProcess engineeringFood productsBiochemical engineeringFood industryEnvironmental scienceMicrowave heatingMicrowaveQuality (philosophy)Consumer demandPulp and paper industryNanotechnologyComputer scienceMaterials scienceFood scienceEngineeringChemistryPhysicsTelecommunications

Abstract

fetched live from OpenAlex

The growing concerns over product quality have increased demand for high quality dried food products and encouraged researchers to explore and producers of such products to implement novel microwave (MW)-assisted drying methods. This paper presents a critical review of the key principles and drawbacks of MW-assisted drying as well as needs for future research. In this article, recent research into application of microwaves as an alternative heat source, applications and progress in hybrid MW-assisted drying that rely on various drying media and combined two or three stages of MW-assisted drying for the preservation of food products is reviewed critically. The effect of different MW-assisted drying methods, conditions and initial pretreatments on the thermophysical properties, color, nutritional value and rehydration potential of dried food products is discussed in detail along with the discussion on how the material properties evolve and change in structure, color, and composition during MW-assisted drying and recent attempts at mathematical modeling of these changes made for different fruits and vegetables. It should be noted that most of the published results were obtained in laboratory-scale dryers. Pilot-scale testing is needed to bridge the gap between laboratory research and industrial applications to fulfill the potential for novel hybrid and combined MW-assisted drying methods and to expand their role in food 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.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.812
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.419
GPT teacher head0.451
Teacher spread0.033 · 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