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Record W2515083109 · doi:10.5539/jas.v8n9p37

Cassava Biomass Transformation by Aspergillus oryzae

2016· article· en· W2515083109 on OpenAlexvenueno aff
Igor Albuquerque de Souza, Paulo Gustavo Barboni Dantas Nascimento, Daniela Castilho Orsi, Claure N. Lunardi

Bibliographic record

VenueJournal of Agricultural Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsFermentationAspergillus oryzaeChemistryFood scienceEthanol fermentationYeastMethanolHydrolysisBrixStarchBiochemistryOrganic chemistrySugar

Abstract

fetched live from OpenAlex

<p>The cassava spirit, known as <em>tiquira</em>, is produced mainly in the north region of Brazil and it is regulated by Brazilian legislation. This study aimed to evaluate the traditional method of<em> </em>cassava spirit production, using a controlled process with application of fermentation technology in a laboratory scale production. <em>Aspergillus oryzae</em> was used for liquefaction and saccharification of cassava starch. It was obtained wort with 13.03 °Brix and 6.80% of reducing sugars. Commercial<em> Saccharomyces cerevisiae</em> yeast was used for alcoholic fermentation. After alcoholic fermentation, it was obtained fermented wort with very low volatile acidity. The cassava spirit was obtained by a double distillation process, with separation of the fractions head, heart and tail. The heart fraction of the distillate showed alcohol content of 51.56<sup>o</sup>GL. The contents of aldehydes, esters, methanol and higher alcohols (n-propyl, isobutyl and isoamyl) were determined in cassava spirit using gas chromatography. According to the results, the cassava spirit showed methanol and higher alcohols contents above the limits imposed by Brazilian legislation.</p>

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.225
Teacher spread0.209 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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