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Record W3158458475 · doi:10.1016/j.dib.2021.107102

GC-HRTOF-MS dataset of metabolites extracted from sorghum and ting (a fermented product) produced using two strains of Lactobacillus fermentum (singly and in combination)

2021· article· en· W3158458475 on OpenAlexfundno aff
Janet Adeyinka Adebiyi, Patrick Berka Njobeh, Eugénie Kayitesi, Oluwafemi Ayodeji Adebo

Bibliographic record

VenueData in Brief · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersUniversity of JohannesburgNational Research FoundationUniversity of Alberta
KeywordsLactobacillus fermentumFermentationSorghumChemistryFood scienceMetaboliteChromatographyLactic acidLactobacillus plantarumBiologyBacteriaBiochemistryAgronomy

Abstract

fetched live from OpenAlex

This data article reports the untargeted metabolite profile of whole grain sorghum (Sorghum bicolor L.) and fermented ting samples obtained using two strains of Lactobacillus fermentum. The sorghum grains were obtained from Agricol Johannesburg (South Africa) and fermentation was done at 34 °C for 24 h. Controlled fermentation with two Lactobacillus fermentum strains (L. fermentum FUA 3165 and L. fermentum FUA 3321), was done using the strains singly and in combination. The samples obtained thereafter were freeze-dried and acetonitrile/methanol/water (v/v/v) were used as extraction solvent, before analyses on a gas chromatography high resolution time of flight mass spectrometry (GCHRTOF-MS) system. Data obtained showed the presence of different compounds, classified into metabolite groups such as acids, alcohols, benzenes, furan, esters, hydrocarbons, terpenes, phytosterols, etc., with their retention time, molecular formula, observed mass and average peak areas reported herein. These data can be used for finding biomarkers for sorghum and their derived fermented products.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.360

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 head0.065
GPT teacher head0.294
Teacher spread0.229 · 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 designObservational
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

Citations4
Published2021
Admission routes1
Has abstractyes

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