The versatile biopolymer chitosan: potential sources, evaluation of extraction methods and applications
Bibliographic record
Abstract
Among the biopolymers, chitin and its derivative chitosan (CTS) have been receiving increasing attention. Both are composed of randomly distributed β-(1-4)-linked d-glucosamine and N-acetyl glucosamine units. On commercial scale, CTS is mainly obtained from the crustacean shells. The chemical methods employed for extraction of CTS from crustacean shells are laden with many disadvantages. Waste fungal biomass represents a potential biological source of CTS, in fact with superior physico-chemical properties, such as high degree of deacetylation, low molecular weight, devoid of protein contamination and high bioactivity. Researchers around the globe are attempting to commercialize CTS production and extraction from fungal sources. Fungi are promising and environmentally benign source of CTS and they have the potential to completely replace crustacean-derived CTS. Waste fungal biomass resulting from various pharmaceutical and biotechnological industries is grown on inexpensive agro-industrial wastes and its by-products are a rich and inexpensive source of CTS. CTS is emerging as an important natural polymer having broad range of applications in different fields. In this context, the present review discusses the potential sources of CTS and their advantages and disadvantages. This review also deals with potential applications of CTS in different fields. Finally, the various attributes of CTS sought in different applications are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".