MétaCan
Menu
Back to cohort

Foliar application of methyl jasmonate does not increase terpenoid accumulation, but weakly elicits terpenoid pathway genes in sandalwood (<i>Santalum album</i> L.) seedlings

2014· article· en· W1986780712 on OpenAlexaff
Carsten K uuml lheim, Christopher G. Jones, Julie A. Plummer, Emilio L. Ghisalberti, Liz Barbour

Bibliographic record

VenuePlant Biotechnology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant biochemistry and biosynthesis
Canadian institutionsUniversity of British Columbia
FundersAustralian National University
KeywordsSandalwoodSantalum albumTerpenoidMethyl jasmonateBiologyBotanyEssential oilBiosynthesisHorticultureGeneBiochemistryTraditional medicine

Abstract

fetched live from OpenAlex

The sesquiterpenoid rich essential oils of sandalwood (Santalum album L.) stems and roots are a highly sought commodity in the fragrance industry. Plantations of sandalwood are being established in northern Australia, however the valuable heartwood essential oils do not accumulate in substantial amounts before 10 years, while commercially viable harvests do not normally take place for at least 15 years. Inducing essential oil accumulation at an earlier stage, or increasing oil yield in mature trees, may have the potential to enhance the oil productivity of plantations. In this study, we investigated the effects of foliar application of methyl jasmonate on less than one-year-old sandalwood seedlings. Essential oil accumulation was unaffected in both stems and roots. However, at the gene transcript level, several key genes early in the biosynthesis of sandalwood oil components were induced in both leaves and stems. These results suggest that terpenoid biosynthesis in S. album does indeed respond to foliar application of methyl jasmonate, however the effects are small and the full biosynthesis of santalols is likely to be developmentally regulated.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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.

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

Citations10
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePlant BiotechnologySame topicPlant biochemistry and biosynthesisFrench-language works237,207