Metabolite profiling of “Eretto Liguria”, an Italian local ecotype of Salvia rosmarinus, and antimicrobial activity against Pectobacterium carotovorum subsp. carotovorum
Bibliographic record
Abstract
A targeted NMR metabolomic approach was used to characterise Salvia rosmarinus “Eretto Liguria” ecotype, commonly used in Northwest Italy by farmers for cuttings and for marketing, with a view to application and registration processes for designation of protected geographical indications. Quali- quantitative NMR based investigation was perfomed by means of Chenomx (Chenomx NMR Suite 8.6, Chenomx Inc., Edmonton, 252 Canada) and NMRProcFlow tools, and was followed by multivariate data analysis. Self-organising maps (SOMs) showed that the accessions of “Eretto Liguria” appeared well characterised compared to the other commercial cultivars and ecotypes from the same geographical region, and had a good content in carnosic acid. Moreover, to evaluate the possibility of using the rosemary biomass, after the removal of cuttings or fronds marketable as flavouring, as a source of extracts and pure compounds with potential phytosanitary activity in organic farming, rosemary methanolic extracts and the pure abietane compounds were tested for their ability to reduce the pectolytic activity of the soft rotting P. carotovorum subsp. carotovorum on potato tissue. The in vitro assay on potato tuber slices showed the ability of rosemary methanolic extracts to reduce the pectolytic activity, and 7-O-methylrosmanol, carnosol and isorosmanol were showed to completely inhibit the pectolytic activity. In silico studies showed that these abietane diterpenoids may interact with P. carotovorum subsp. carotovorum pectinase enzymes (pectate lyase 1 and endopolygalacturonase), thus highlighting these rosemary components as starting points for the development of agents able to prevent soft rot progression in potato crops. Publication History Article published online: 16 November 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".