Tomato plant architecture as affected by salinity: Descriptive analysis and integration in a 3-D simulation model
Bibliographic record
Abstract
Limited information is available on the effect of salinity on plant architecture; not only on final plant height, number of leaves, and leaf area, but also on plant growth and development from the leaflet to the whole plant scale. Tomato plants ( Solanum lycopersicum L. ‘Marmara’) were grown in greenhouses at four salinity levels (4, 7, 10, and 13 mS·cm–1). Plant development (leaf and inflorescence initiation), leaf growth rate, and final leaf dimensions were measured along the stem according to leaf rank and treatment. A decrease in leaflet growth and in the number of leaflets per leaf was associated with a lower growth rate and longer growth period in salinity stressed plants. Stem internode length was also reduced by salinity. At the plant scale, plant height and leaf area decreased with an increase in salinity. These parameters were the main inputs of a 3-D model of plant architecture, which enabled a complete description of plant architecture from the elementary to the canopy scale. This model of plant architecture was evaluated by comparing hemi-spherical photos of the plant taken with a camera with those generated by the model. The model was used to estimate light interception which should be useful to calculate photosynthesis at the plant scale.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".