Plant Waste in the Production of New Materials in Brazil: A Scientometric Analysis from 19912021
Bibliographic record
Abstract
Several plant residues can be generated during the stages of industrial processing, such as fruit peel, seeds and bagasse, and these can give rise to high-value products. The management and use of this waste is of global interest. The aim of this study was to evaluate the spatio-temporal evolution of scientific knowledge on the reuse of agroindustrial waste generated in Brazil through a scientometric analysis. To this end, a search was performed in the databases Scopus, Scielo, and Web of Science between the years 1991and 2021. The words used as indexers were agribusiness waste, vegetable waste, fruit waste, biomass waste, plant residue, and chemical characterization. The following selection criteria were adopted: search of indexers by title, scientific articles, articles in English and Portuguese, and articles on plant waste generated in Brazil. There was an increase in publications over the years, with a greater number of studies (21.46%) in the chemistry area, addressing mainly the physical-chemical characterization of materials. In Brazil, sugarcane (Saccharum officinarum L.) was the most studied species with a view to reusing its residues. We identified species from highly threatened Brazilian biomes, such as the Atlantic Forest and Cerrado, with the potential for transformation into new materials. The gaps in knowledge, evidenced in this analysis, suggest that more studies should be carried out on residues of native plant species which impact local communities. In particular, studies could focus on applicability in health and cosmetics, which are promising areas for plant materials and still little investigated.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.008 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".