Seasonal and Regional Chemical Variability of the Wild Population of Lantana camara Leaf Essential Oil From Kenya
Bibliographic record
Abstract
Studies examining the variability in wild plant metabolic expression propose that environmental factors significantly influence the essential oil (EO) quality and quantity in a plant. Lantana camara is a widely distributed invasive plant species worldwide. However, its immense metabolites can become a source of novel compounds to produce biopesticides in the agricultural industry. Although, the quality aspect has to be considered due to the environmental influence on the metabolites synthesised. Therefore, this research aimed to understand the influence of environmental factors and how it shapes the plant’s metabolite profile in multiple populations of L. camara. Leaf samples were collected from six different geographic regions of Kenya and the corresponding monthly climatic data and soil samples. GC-MS data from leaf EO were analysed with environmental variables (climate and soil data) using unimodally unconstrained and constrained ordination methods for untargeted metabolomics analysis. Partial Least Squares-Discriminant Analysis (PLS-DA) and Random Forests (RF) were used to confirm the variability further. Seasonal and regional variability was observed for secondary metabolites (SMs) in the leaf EO, which correlated to climatic factors and soil attributes. We highlight the season-al-geographic metabolism relationship for L. camara and the combined analytical approach to obtain data that contributes to understanding the influence of environmental factors on the synthesis and accumulation of SMs. This research will have all-embracing implications for maximising phytochemical uniformity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".