A method for routine measurements of total sugar and starch content in woody plant tissues
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Several extraction and measurement methods currently employed in the determination of total sugar and starch contents in plant tissues were investigated with the view to streamline the process of total sugar and starch determination. Depending on the type and source of tissue, total sugar and starch contents estimated from samples extracted with 80% hot ethanol were significantly greater than from samples extracted with a methanol:chloroform:water solution. The residual ethanol did not interfere with the sugar and starch determination, rendering the removal of ethanol from samples unnecessary. The use of phenol-sulfuric acid with a phenol concentration of 2% provided a relatively simple and reliable colorimetric method to quantify the total soluble-sugar concentration. Performing parallel sugar assays with and without phenol was more useful for accounting for the interfering effects of other substances present in plant tissue than using chloroform. For starch determination, an enzyme mixture of 1000 U alpha-amylase and 5 U amyloglucosidase digested starch in plant tissue samples more rapidly and completely than previously recommended enzyme doses. Dilute sulfuric acid (0.005 N) was less suitable for starch digestion than enzymatic hydrolysis because the acid also broke down structural carbohydrates, resulting in overestimates of starch content. After the enzymatic digestion of starch, the glucose hydrolyzate obtained was measured with a peroxidase-glucose oxidase/o-dianisidine reagent; absorbance being read at 525 nm after the addition of sulfuric acid. With the help of this series of studies, we developed a refined and shortened method suitable for the rapid measurement of total sugar and starch contents in woody plant tissues.
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.
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 | 0.000 |
| 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 it