Development and Productivity of Jatropha curcas Plants Treated With Growth Regulators
Bibliographic record
Abstract
The objective of the present work was to evaluate the effect of plant growth regulators (PGR) on the vegetative development and productivity of Jatropha curcas plants. A field experiment was conducted at the Goiás State University, Brazil, using two-year-old J. curcas plants planted with spacing of 3 × 2 m, using foliar applications of two PGR—trinexapac-ethyl and prohexadione-Ca. A randomized block design was used with four treatments (trinexapac-ethyl at 1 ml plant-1—T1; prohexadione-Ca at 2 mg plant-1—T2; trinexapac-ethyl at 1 ml plant-1 plus prohexadione-Ca at 2 mg plant-1—T3; and Control—T4), five replications, and plots consisting of two plants. Two applications of a 300 ml plant-1 solution with the treatments were performed with a 30-day interval after the leaf emergence period (late September and October 2017). The trinexapac-ethyl and prohexadione-Ca plant growth regulators increased the grain yield of Jatropha curcas plants by increasing their vegetative growth, and number of inflorescences, and female and hermaphrodite flowers, but had no effect on the uniformity of fruit maturation. The treatment in which both plant growth regulators were used presented the best results, generating more vigorous and productive plants.
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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) | 0.001 | 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) | 0.001 | 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".