Effects of Sampling Methods on Starch Granule Size Measurement of Potato Tubers under a Light Microscope
Bibliographic record
Abstract
Measurement of starch granules by lightmicroscope is the preferred approach in most laboratories because it is simple, rapid and visual and because both size and shape can be investigated. However, juice from potato tubers consists of starch granules of very different sizes and precipitation/movement speeds which can cause artefacts when sampling the juice and recording microscopic images. In the previously described method, a razor blade was used to scrape and transfer juice from potato tubers directly to a drop of water on a slide for microscopic observation. In this study we used chambers made from tape on microscopic slides to reduce the cover-slip-induced shifting of small and medium granules. We improved the starch measurement reproducibility by testing various juice sampling methods. The reproducibility between repeated experiments using 10 cultivars was increased from a correlation coefficient r = 0.815 in the razor-blade-scraping method to r = 0.923 in a squeezing-juice method. The largest starch granule detected was 151 μm in length. Sampling methods (using a razor-blade or a garlic press) strongly influenced the granule length values measured from the same potato tuber. The results indicated that (1) The squeezing- juice approach is more reproducible, and (2) The average length of starch granules is one of the most reproducible scores but varies according to juice-sampling methods.
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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 | 0.001 | 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 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".