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Record W4304636307 · doi:10.7717/peerj.14177

Enhancing yogurt products’ ingredients: preservation strategies, processing conditions, analytical detection methods, and therapeutic delivery—an overview

2022· article· en· W4304636307 on OpenAlexaff
Rahul Mehra, Harish Kumar, Shafiya Rafiq, Naveen Kumar, Harpal S. Buttar, Katarzyna Leicht, Charles Odilichukwu R. Okpala, Małgorzata Korzeniowska

Bibliographic record

VenuePeerJ · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBiotechnologyNovel foodFunctional foodBiochemical engineeringBusinessFood scienceChemistryBiologyEngineering

Abstract

fetched live from OpenAlex

As a dairy product, yogurt delivers nourishing milk components through the beneficial microbial fermentation process, improved by bioavailability and bioaccessibility–an exclusive combined food asset. In recent decades, there has been considerable attention to yogurt product development particularly in areas like influence by antioxidant-rich fruits, different factors affecting its probiotic viability, and the functionality of inulin and probiotics. Essentially, many published reviews frequently focus on the functionalities associated with yogurt products, however, those articulating yogurt ingredients specific to associated preservation strategies, processing conditions, and analytical detection techniques are very few, to the best of our knowledge. The knowledge and understanding of preservation strategies that enhance the ingredients in yogurt products, and their function as modern drug delivery systems are essential, given the opportunities it can provide for future research. Therefore, this overview discussed how yogurt product ingredients have been enhanced, from preservation strategies, processing conditions, analytical detection methods, and therapeutic delivery standpoints. The survey methodology involved major stages, from the brainstorming of research questions, search strategy, effective utilization of databases, inclusion and exclusion criteria, etc . The innovative successes of yogurts would be enhanced via the physicochemical, nutritional and therapeutic aspects of the ingredients/products. Besides processing conditions to influence the yogurt constituents, overall acceptability, quality, and shelf-life, the analytical assays would help detect the hidden product constituents, toxins, and other storage-related changes. The therapeutic role of yogurt-a modern drug delivery system, would be demonstrated via the supplementation (of yogurt) either alone or with bioactive ingredients. The future of yogurt requires the collective action of stakeholders to formulate unique variants with different natural blends, where synthetic ingredients become completely replaced by the plant’s derivatives, which enhance the acidification rate and extend 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 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 score0.681
Threshold uncertainty score0.466

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 studies0.0010.000
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 head0.077
GPT teacher head0.338
Teacher spread0.261 · 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

Citations22
Published2022
Admission routes1
Has abstractyes

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