Modeling the nonlinear elastic behavior of plant epidermis
Bibliographic record
Abstract
Cell growth and organ development in plants are often correlated with the tensile behavior of the primary cell wall. To understand the mechanical behavior of plant material, various mechanical testing techniques have been employed, such as tensile testing of excised tissue samples. The onion (Allium cepa L.) epidermis has emerged as a model system for plant tissue mechanics. In this study, we performed tensile tests on strips of adaxial onion epidermis. While the tissue appeared stiffer in the direction along the major growth axis compared with the transverse direction, the tensile strength of tissue was not significantly different between the two orientations, indicating a nontrivial link between the cell wall and tissue mechanical anisotropy. Importantly, we observed the stress–strain behavior of the onion epidermis under tension to be highly nonlinear. Several hyperelastic models were fitted to the test data to evaluate their capacity to describe the nonlinear deformation of onion epidermis. The Yeoh hyperelastic model could successfully simulate the uniaxial tensile test data. This study suggests that accounting for nonlinearity in the deformation of the primary tissue may be essential for the accurate interpretation of mechanical test data, and a better understanding of the mechanics of the primary plant cell wall.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".