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Record W2028838125 · doi:10.3109/09637486.2013.869793

Shelf life stability of lactobacilli encapsulated in raspberry powder: Insights into non-dairy probiotics

2014· article· en· W2028838125 on OpenAlexaff
Kartheek Anekella, Valérie Orsat

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsMcGill University
Fundersnot available
KeywordsShelf lifeMaltodextrinFood scienceLactobacillus rhamnosusBlowing a raspberryProbioticSpray dryingWater activityLactic acidLactobacillus acidophilusLactobacillusChemistryBiologyBacteriaWater contentChromatography

Abstract

fetched live from OpenAlex

AIM: Study the shelf-life quality changes in raspberry juice with encapsulated lactobacilli (Lactobacillus rhamnosus NRRL B-4495 and Lactobacillus acidophilus NRRL B-442) obtained by spray drying and understand the various factors involved. METHODS AND RESULTS: Raspberry powder was obtained from spray drying lactobacilli and raspberry juice with maltodextrin as an additive. Shelf life of the powder was analyzed over a period of 30 d. Acid and bile tolerance and antibiotic resistance was compared before and after spray drying. Water activity, survival, and scanning electron microscope images were also measured during the shelf life. CONCLUSIONS AND SIGNIFICANCE: A combination of processing conditions: inlet temperature (°C), maltodextrin to juice solids ratio and inlet feed rate (ml/min) during spray drying had a significant role on the survival of lactobacilli during shelf life. Refrigerated storage provided a higher shelf-life stability with regards to CFU/g (as high as 84% on day 0 and 98% retention by the end of 30 d) compared to room temperature storage. Probiotic properties during shelf life are affected by the processing conditions and encapsulated food matrix. Thus, understanding these aspects in vitro during shelf life gives us a brief insight into the future of non-dairy probiotics.

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 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.146

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.018
GPT teacher head0.234
Teacher spread0.216 · 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 teacher head, 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

Citations15
Published2014
Admission routes1
Has abstractyes

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