Influence of Water Regimes and Potassium Chlorate on Floral Induction, Leaf Photosynthesis and Leaf Water Potential in Longan
Bibliographic record
Abstract
This study verifies the influence of water regimes and potassium chlorate (KC1O3) on photosynthetic rate, flower emergence and media moisture content of longan trees. The trees were grown in 150 liters lysimeter tanks filled with fine sand. The experimental design was a 2x2 factorial in completely randomized design (CRD) with 2 factors; 1) two levels of water regimes (well-watered and water deficit) and 2) two levels of KClO3 at 10 and 0 g. The results revealed that the well-watered treatment produced faster days of terminal bud break than that of the water deficit treatment. The 10 g KClO3 treatment induced 91 % flower emergence at 35 days after commencing the treatment, while the 0 g KClO3 treatment had 82 % leaf flushing and had no flower emergence. Water deficit or KClO3 treatments reduced the net carbondioxide (CO2) exchange, transpiration and stomatal conductance rates. Moreover, the combination of well-watered and 0 g KClO3 treatments gave the greatest values of the parameters. The well-watered treatment had higher volumetric water content in the growing medium and leaf water potential than the water deficit treatment, while for the 10 g and 0 g KClO3 treatments had similar the media moisture content.
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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 | 0.000 |
| 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 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".