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Record W4390708072 · doi:10.1016/j.fochx.2024.101129

Effect of plasma-activated lactic acid on microbiota composition and quality of puffer fish (Takifugu obscurus) fillets during chilled storage

2024· article· en· W4390708072 on OpenAlexaff
Xiaowei Sheng, Longfei Yan, Lanqing Peng, Luling Zhao, Fanwei Dai, Ling Wang, Yulong Chen, Mingqiang Ye, Jin Wang, Jianhao Zhang, Vijaya Raghavan

Bibliographic record

VenueFood Chemistry X · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMcGill University
FundersNational Key Research and Development Program of ChinaGuangdong Academy of Agricultural Sciences
KeywordsFood scienceFish filletShelf lifeFish <Actinopterygii>BiologyLactic acidChemistryFisheryBacteria

Abstract

fetched live from OpenAlex

Fresh puffer fish (Takifugu obscurus) are susceptible to microbial contamination and have a very short shelf-life of chilled storage. Hence, this study aimed to evaluate the effects of plasma-activated lactic acid (PALA) on microbiota composition and quality attributes of puffer fish fillets during chilled storage. The results showed that PALA treatment effectively reduced the growth of bacteria and attenuated changes in physicochemical indicators (total volatile basic nitrogen, pH value, K value, and biogenic amines) of puffer fish fillets. Additionally, insignificant changes were observed in lipid oxidation during the first 8 days (p > 0.05). Illumina-MiSeq high-throughput sequencing revealed that PALA effectively inhibited the growth of Pseudomonas in puffer fish fillets and maintained the diverse characteristics of the microbial community. In combination with sensory analysis, PALA extended the shelf life of puffer fish fillets for 4 days, suggesting that PALA could be considered a potential fish fillet preservation method.

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)0.000
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 score0.012
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.247
Teacher spread0.226 · 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

Citations19
Published2024
Admission routes1
Has abstractyes

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