A Scanner-based Root Image Acquisition Technique for Measuring Roots on a Rhizotron Window
Bibliographic record
Abstract
A simple flatbed-scanner-based image acquisition system was developed for the measurement of `Gala'/M9 ( Malus × domestica Borkh.) apple tree root growth in rhizoboxes with a transparent acrylic sheet on one side. A tree was planted in the center of each rhizobox, and a modified flatbed scanner was periodically used to directly capture high-resolution digital images of roots growing against the transparent wall. Total root length in the images was either measured manually, or by computer mouse tracing, or automatically with a computer image analysis system. Correlations were made among the different measurements. High quality root images were obtained with the adapted scanner system. Significant linear relationships were found between manual and computer traced root length measurements (r = 0.99), traced and automatic measurements (r = 0.76) and manual and automatic measurements (r = 0.75). Apple roots appeared on the transparent wall 34 days after transplanting, and grew rapidly thereafter, reaching a maximum on the transparent wall 59 days after transplanting. Our results showed that the use of a flatbed scanner for the acquisition of root images combined with computer analysis is a promising technique to speed data acquisition in root growth investigations.
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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".