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Record W2318336670 · doi:10.5539/ijb.v8n2p92

Quantification of Seed Oil Content and Fatty Acid Profile of Jatropha cucas L. from Guizhou, China

2016· article· en· W2318336670 on OpenAlexvenueno aff
Hamidou Senou, Cai Xia ZHENG, G. Samake, Mamadou Traoré, Fousséni Folega, Bakary M. TRAORE

Bibliographic record

VenueInternational Journal of Biology · 2016
Typearticle
Languageen
FieldEngineering
TopicBiodiesel Production and Applications
Canadian institutionsnot available
FundersDirectorate for Biological SciencesBeijing Forestry UniversityChina Scholarship Council
KeywordsJatropha curcasLinoleic acidChemistryStearic acidOleic acidFood sciencePolyunsaturated fatty acidPalmitic acidFatty acidBiodieselComposition (language)JatrophaIodine valueBotanyBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

<p class="1Body">The methyl esters of fatty acids composition of the oil from <em>jatropha curcas</em> seeds were analyzed by gas chromatography-mass spectrometer GC-MS. Fourteen components were found to be representative with 99.52% of the total content of seed oils. The main constituents were unsaturated fatty acids (71.93%) and saturated fatty acids (27.59%). For the saturated fatty acids composition such as palmitic and stearic acid, the rate was 15.80% and 10.79%, respectively. Linoleic acid (39.58%) and oleic acid (30.41%) were obtained in highest concentration among the unsaturated fatty acids identified in the seeds oil of <em>Jatropha curcas</em> from Guizhou. This value also justifies the fluidity of the oil at room temperature. A high percentage of polyunsaturated fatty acids (39.58%) and a slightly lower rate of monounsaturated fatty acids (32.35%) were also observed. The seed oils profile of Guizhou <em>Jatropha curcas</em> presents the desirable fatty acid C14 to C18 and interesting features for the biodiesel production.</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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.155

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 head0.030
GPT teacher head0.265
Teacher spread0.235 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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