Essential Oil of Baccharis dracunculifolia (Asteraceae) Decreases Alternaria Rot in Pitahaya
Bibliographic record
Abstract
Alternaria rot, caused by Alternaria alternata, is one of the most destructive diseases of pitahaya (Hylocereus spp.). We investigated the effect of the essential oil of Baccharis dracunculifolia (Asteraceae) (EOB) in the control of A. alternata. Two studies were performed in Petri dishes containing potato dextrose agar medium amended with concentrations of the EOB ranging from 5 to 1,000 µg mL-1 (first study) and from 30 to 2,000 µg mL-1. The diameter of the fungal colony was recorded daily. These data were used to calculate the the area under the mycelial growth progress curve (AUMGPC) and mycelial growth index (MGI). In the third study, the control of Alternaria rot in pitahaya fruits by EOB was investigated by adding the EOB into an edible coat based on cassava starch and sorbitol which was prepared in Tween 20. Three treatments, containing EOB at 500, 1,000 or 2,000 µg mL-1, were assessed. Two additional treatments, one containing water and another containing only the edible coating served as controls. Pitahaya fruits were immersed in those solutions for 10 min, allowed to dry and inoculated with A. alternata 48 h later. The EOB was found to inhibit the mycelial growth and a negative and quadratic model best described the relationship of the EOB concentrations with MGI and AUMGPC. Results from the experiment performed with pitahaya fruits showed that Alternaria rot was decreased with increasing EOB concentrations. Therefore, EOB is a promising and ecofriendly method that may be included in the management of Alternaria rot in pitahya.
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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) | 0.001 | 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".