Spectrophotometric assessment of leaf UV-B absorbing compounds and chemically determined total phenolic levels are strongly correlated
Bibliographic record
Abstract
Investigations concerning the two major ecological roles of phenolics use different methods to quantify these compounds (phenolics as antiherbivores, Folin-Ciocalteu chemical assay; phenolics as UV-B screening pigments, UV-B absorbance). Yet, comparisons of the corresponding results are not possible, since an empirical correlation between the two methods is lacking. In the present study, significant regressions between total phenolic levels (chemically determined with the Folin-Ciocalteu method) and leaf UV-B absorbing capacity (assessed from simple absorbance measurements of methanolic extracts at 300 nm) were found in all seven plant species tested, yet interspecies differences in regression equations were evident. Provided that a standard curve between UV-absorbance versus total phenolic levels is established for each test plant, the latter could be predicted from the former. The UV-absorbance method is preferable because it is time-saving, simpler, and less costly. Given the strong regression between the two variables, a comparison of the generalizations reached by the two lines of research using the corresponding methods for phenolic determination is attempted.Key words: UV-B absorbing capacity, phenolics, herbivory, Mediterranean plants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".