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Record W2918650326 · doi:10.1080/07373937.2019.1570248

Sublimation conditions as critical factors during freeze-dried probiotic powder production

2019· article· en· W2918650326 on OpenAlexaff
Stephanía Aragón-Rojas, Y. Ruíz, Alan Javier Hernández‐Álvarez, María Ximena Quintanilla‐Carvajal

Bibliographic record

VenueDrying Technology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsnot available
FundersUniversidad de La SabanaDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsMaltodextrinFreeze-dryingSublimation (psychology)Food scienceChemistryWater contentProbioticMoistureMaterials scienceSpray dryingChromatographyBacteriaBiology

Abstract

fetched live from OpenAlex

The aim was to study the effect of sublimation temperature (from –20 °C to –10 °C) and sublimation time (from 18 to 40 h) on the viability of Lactobacillus fermentum K73, the moisture content and the texture features by response surface methodology. The stability of the freeze-dried powders was studied; these powders were stored at 4 °C, 25 °C, and 37 °C for 36 days. Four different matrices were used: culture medium (8% total solids), the mixture of this solution with maltodextrin: whey (0.6: 0.4), with maltodextrin or whey (40% total solids). Results showed that the sublimation conditions to increase cell viability (>8.755 log CFU/g) and to decrease moisture content (<4.087% [wet basis]) in the mixtures were –10 °C and 18 h. The image analysis successfully correlated sublimation temperature and time with the structural characteristics of the powders, cell viability, and moisture content. The shelf life study showed that the specific rate of cell viability loss was lower when the freeze-dried powders were stored at 4 °C, being the denatured whey solution the best cryoprotectant matrix during the freeze-drying process and shelf life.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.232
Teacher spread0.222 · 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

Citations25
Published2019
Admission routes1
Has abstractyes

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