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Record W4384067866 · doi:10.1111/jfpe.14410

Comparative evaluation of drying characteristics and antioxidant quality of raspberry by different drying methods

2023· article· en· W4384067866 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

VenueJournal of Food Process Engineering · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsMcGill University
Fundersnot available
KeywordsBlowing a raspberryAnthocyaninFood scienceChemistryFreeze-dryingDPPHAntioxidant capacityShelf lifeAntioxidantVacuum dryingPolyphenolScanning electron microscopeMaterials scienceChromatographyComposite materialOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Four drying methods, hot air drying (HAD), microwave constant temperature drying (MWD), microwave vacuum temperature‐controlled drying (MIVD‐T50), and freeze drying (FD), were investigated for their effects on raspberries in terms of drying time, color, microstructure, rehydration, water activity, phenolic compounds, flavonoids, anthocyanins, and DPPH scavenging ability. It was found that microwaves combined with vacuum took the shortest time. The color of MIVD‐T50 is similar to that of FD and much better than that of HAD and MWD. A smooth surface and fluffy and porous structure inside were observed in the FD and MIVD by scanning electron microscopy (SEM) images. FD has the highest energy consumption, followed by HAD, MIVD‐T50 and MWD. The retention rates of total phenols and flavonoids in HAD, MWD and FD were lower than those in MIVD‐T50, and FD had the advantage of retaining anthocyanin content. In general, MIVD‐T50 has significance for the commercial production of raspberry. Practical applications The use of natural antioxidants in food processing not only enhances the shelf life of products but also improves their nutritional value. Raspberry is a rich source of antioxidants and is widely used in food processing. However, the drying process is crucial in preserving its antioxidant quality, and different drying methods affect the antioxidant content differently. According to the results of the experiments, the drying method has a considerable impact on the energy usage and quality of dried raspberries. Compared with the HAD and MWD treatments, both FD and MIVD‐T50 showed better nutrient content preservation and antioxidant activity, which may be caused by the lower temperature drying process of FD or the stronger efficiency of MIVD‐T50. However, the drying time of FD is longer, and the energy consumption is higher. Therefore, MIVD‐T50 is a promising raspberry drying technology with low energy consumption, a short drying time, and high quality. It has huge development potential and broad commercial scale production market prospects.

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)0.002
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 score0.273
Threshold uncertainty score0.194

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 head0.133
GPT teacher head0.381
Teacher spread0.248 · 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