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Record W2407156012 · doi:10.1080/07373937.2016.1175472

Quality of dried haskap berries (<i>Lonicera caerulea</i>L.) as affected by prior juice extraction, osmotic treatment, and drying conditions

2016· article· en· W2407156012 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDrying Technology · 2016
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsExtraction (chemistry)ChemistryBerryYield (engineering)Food scienceWater contentAnthocyaninPressingChromatographyHorticultureMaterials science

Abstract

fetched live from OpenAlex

The effect of juice extraction conditions on the quality of haskap berries (Lonicera caerulea L.) dried at different temperatures (60, 100, and 140°C) was investigated. The conventional juice extraction (process A) consisted of a two-press process, where thawed berries were pressed, and osmotic treatment was applied before pressing again. This was compared with a modified extraction (process B), which applied osmotic treatment during fruit thawing and only one press was used for extraction. The quality parameters investigated included moisture content, pressed berry yield, extraction loss, drying yield, total anthocyanin content (TAC), vitamin C content, and the rehydration characteristics of the final dried berries. Pressing the berries to 70% juice yield resulted in a higher pressed berry yield and better physicochemical quality in the pressed product. The yield was 26.39 and 28.92% in the conventional and modified extraction, with moisture contents of 70.32 and 77.75%, respectively. The TACs of pressed berries from extraction processes A and B were 24.62 and 33.03 mg C-3-G g−1 DW and the vitamin C contents were 14.14 and 36.18 mg/100 g, respectively. Drying at 60°C until 25% moisture content was better than at higher temperatures, resulting in a better quality dried product. It revealed drying yields of 45.32 and 52.75%, TACs of 4.00 and 4.30 mg C-3-G g−1 DW, vitamin C contents of 2.97 and 4.91 mg /100 g, and rehydration ratios of 2.22 and 2.37 from processes A and B, respectively. Process B with the one-step extraction is recommended for higher pressed berry yield, higher drying yield, and enhanced quality of the pressed and dried products. It is also a more efficient process, in terms of time, cost, and energy.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.610

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.018
GPT teacher head0.332
Teacher spread0.314 · 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