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Record W2891679034 · doi:10.5539/jas.v10n10p144

Fatty Acid Profile of Sunflower Achene Oil From the Brazilian Semi-arid Region

2018· article· en· W2891679034 on OpenAlexvenueno aff
C. G. P. de Carvalho, Andressa Caldeira, Luciana Marques de Carvalho, H. W. L. de Carvalho, José Leonardo Ribeiro, J. M. G. Mandarino, José C. F. de Resende, Ariomar Rodrigues dos Santos, Marcos Reinaldo da Silva, Nair Helena Castro Arriel

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSunflower and Safflower Cultivation
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsAcheneStearic acidSunflower oilOleic acidLinoleic acidPalmitic acidFood scienceFatty acidSunflowerChemistryBotanyHorticultureBiologyBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The analysis of the fatty acid profile of an oil is important for optimizing its use in the processing and food industries. The present work evaluated the fatty acid profile from sunflower achene oil grown in the Brazilian semi-arid region and adjacent regions. The oleic, linoleic, palmitic and stearic acid contents were determined by gas chromatography (GC). An approximate 5 °C increase (from 19 °C to 24 °C) in the minimum temperature during lipid fraction (oil) formation in achenes yielded a 22.6% increase and a 21.9% decrease in the average oleic acid and linoleic acid contents (41.0% to 63.5% and 50.9% to 29.0%, respectively). The saturated fatty acids content tended to decrease as the minimum temperature increased, although the behavior depended on the environment and the tested genotypes. In general, genotypes Aguara 04 and CF 101 presented higher oleic acid and lower linoleic, palmitic and stearic acid contents than did the HELIO 250 and HELIO 251 genotypes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.020
GPT teacher head0.229
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2018
Admission routes1
Has abstractyes

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