Prohexadione-calcium changes morphological and physiological traits in strawberry plants and preconditions transplants to water stress
Bibliographic record
Abstract
Summary Prohexadione-calcium (ProCa) applied as foliar spray, increases root to shoot ratio and reduces specific leaf area (SLA) in strawberry plants ( Fragaria × ananassa Duch.). These effects may help treated plants to survive a transplant shock. Under mild water stress, ProCa caused a transient reduction in leaf stomatal conductance (gs) in 'Camarosa' and 'Sweet Charlie' plants. This reduction in gs was paralleled by a decrease in transpiration in treated plants, which was not attributable to differences in plant size or leaf area. Pressure volume curves of 'Sweet Charlie' plants revealed that ProCa application lowered leaf osmotic potential at both full and zero turgor, and increased the volumetric modulus of elasticity. ProCa treatment regulated the leaf morphology of strawberry and preconditioned strawberry plants to tolerate water stress. Under field conditions in the plasticulture fruit production system, newly transplanted bare-root strawberry plants had a progressively higher water potential (ψl) and gs with a longer overhead irrigation. Plants treated with ProCa had a higher ψl and gs than control plants at the same level of overhead irrigation. Application of ProCa to strawberry transplants may in part be able to replace overhead irrigation and at the same time maintain acceptable levels of fruit yield.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".