Raman microspectroscopy in the analysis of plant cuticular membranes
Bibliographic record
Abstract
The outside of plants, including fruit, are covered by a cuticular membrane (CM). This membrane serves as protection from environmental factors. The basic composition of the CM is well understood, however, there are always variations among different species. The CM consists of a cutin matrix, which is the structural component, and cuticular waxes. The study of the CM for both structural and compositional features has been accomplished for a variety of species. The instrumentation methods used to complete these analyses have been mostly destructive and at most been able to provide spatial distribution information along the vertical axis. Raman microspectroscopy has been used previously to quantify and map triterpenoid concentrations in Prunus laurocerasus leaf CMs. This data showed transverse variations in concentration across the CM. The goal of the current work is to explore the viability of using Raman microspectroscopy to analyze other species and classes of compounds. Initially, alkylresorcinols in rye leaf waxes, artificial wax mixtures, and rye leaf CMs were examined. Using the current instrumentation it was not possible to quantify and detect alkylresorcinols in rye CMs, but it may become a viable option in the future. Based on the previous work with triterpenoids, this class of compounds was attempted next. Triterpenoids in tomato CMs were investigated resulting in the discovery that, while triterpenoids are not detectable in the tomato CM due to the presence of polysaccharides, lycopene can be detected. It was found that it is present in the remains of the epidermal cells after digestion of the cell walls (epidermal remnants), but not in the CM itself. The analysis of other species for triterpenoids was attempted including the leaves of Rosa canina, Ligustum vulgare, Kalanchoe daigremontiana, and the fruit of the Prunus avium and Prunus laurocerasus. While quantification of triterpenoids was not successful, a lot was learned about the variables which go into a successful Raman analysis of triterpenoids in plant CMs. These variables include the relative amount of triterpenoids to wax and wax to CM, along with the wax coverage (µg/cm²). These results will aid in future attempts at Raman analysis of triterpenoids in CMs.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".