MétaCan
Menu
Back to cohort
Record W2172807604 · doi:10.4141/cjps2012-333

Characterization of volatile compounds in flowers from four groups of sweet osmanthus (<i>Osmanthus fragrans</i>) cultivars

2013· article· en· W2172807604 on OpenAlexvenueno aff
H. P. Xin, Benhong Wu, Haohao Zhang, Caiyun Wang, Jitao Li, Bo Yang, Shaohua Li

Bibliographic record

VenueCanadian Journal of Plant Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsnot available
Fundersnot available
KeywordsLinaloolOsmanthus fragransCultivarChemistryFuranMonoterpeneBotanyHorticultureEssential oilFood scienceOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Xin, H., Wu, B., Zhang, H., Wang, C., Li, J., Yang, B. and Li, S. 2013. Characterization of volatile compounds in flowers from four groups of sweet osmanthus ( Osmanthus fragrans ) cultivars. Can. J. Plant Sci. 93: 923–931. Headspace-solid-phase microextraction (HS-SPME) and gas chromatography-mass spectroscopy (GC-MS) were used to characterize the volatiles in flowers of four cultivar groups of sweet osmanthus (Osmanthus fragrans Lour.), including Thunbergii, Latifolius, Aurantiacus and Semperflorens Groups. A total of 72 volatiles were identified. Volatile compounds and their relative contents varied among the four groups or cultivars within each group. Briefly, β-ionone, cis-linalool oxide (furan), trans-linalool oxide (furan) and linalool were the most common volatiles in tested cultivars, while (E)-2-hexenal, (Z)-3-hexen-1-ol and hexanal were abundant in several cultivars. Principal component analysis showed that the Aurantiacus Group was rich in cis- and trans-linalool oxide (furan), whereas the Latifolius group had high levels of (E)-2-hexenal and (Z)-3-hexen-1-ol. Our results contribute to our understanding of the volatile composition and content in flowers from different osmanthus groups and will facilitate development of new osmanthus cultivars to meet requirements of the food and fragrance industries.

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 score0.090
Threshold uncertainty score0.498

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 science0.0010.000
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 head0.008
GPT teacher head0.185
Teacher spread0.177 · 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

Citations40
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Plant ScienceSame topicPlant biochemistry and biosynthesisFrench-language works237,207