Incorporation of Oil From Hymenaea stigonocarpa and Hymenaea courbaril Into Biofilms Made From Arrowroot Starch: Physicochemical, Biodegradability and Antifungal Activity
Bibliographic record
Abstract
Incorporating of fixed oils in biodegradable packaging has an important action on the polymer matrix and biological activities on phytopathogens. This study aimed to evaluate the incorporation of fixed oils from the seeds of Hymenaea stigonocarpa and Hymenaea courbaril in the arrowroot starch biofilm matrix, evaluating the physicochemical parameters of biodegradability and antifungal activity on Colletotrichum acutatum, Colletotrichum gloeosporioides, Aspergillus tubingensis, Aspergillus fumigatus, Aspergillus niger and Rhizopus stolonifer. Both fixed oils from Hymenaea seeds showed biological antioxidant activity in reducing DPPH. Biofilms showed increasing variation in thickness ranging from 0.23-0.43 mm and decreasing moisture content and solubility 15.01-5.14% and 51.07-34.10%, respectively, as oil concentrations increased. The oil concentration also reduced the transparency rate, a considerable variation between the color and biodegradability parameters. However, the biofilms presented a mass reduction of more than 90% for this test. Biofilms still demonstrate considerable antifungal activity for the evaluated phytopathogens. The seed oil of Hymenaea stigonocarpa and Hymenaea courbaril played important roles in developing biopolymer matrices and special biological activity on potential phytopathological agents of fruits and grains.
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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".