Factors influencing real time internal structural visualization and dynamic process monitoring in plants using synchrotron-based phase contrast X-ray imaging
Bibliographic record
Abstract
Minimally invasive investigation of plant parts (root, stem, leaves, and flower) has good potential to elucidate the dynamics of plant growth, morphology, physiology, and root-rhizosphere interactions. Laboratory based absorption X-ray imaging and computed tomography (CT) systems are extensively used for in situ feasibility studies of plants grown in natural and artificial soil. These techniques have challenges such as low contrast between soil pore space and roots, long X-ray imaging time, and low spatial resolution. In this study, the use of synchrotron (SR) based phase contrast X-ray imaging (PCI) has been demonstrated as a minimally invasive technique for imaging plants. Above ground plant parts and roots of 10 day old canola and wheat seedlings grown in sandy clay loam soil were successfully scanned and reconstructed. Results confirmed that SR-PCI can deliver good quality images to study dynamic and real time processes such as cavitation and water-refilling in plants. The advantages of SR-PCI, effect of X-ray energy, and effective pixel size to study plant samples have been demonstrated. The use of contrast agents to monitor physiological processes in plants was also investigated and discussed.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".