A comprehensive review of conversion of rice biomass into sustainable products: A green approach toward a circular economy
Bibliographic record
Abstract
• A comprehensive analysis of rice husk and straw utilization in biomass valorization. • Exploration of innovative technologies such as enzymatic saccharification, and advanced pretreatment methods to enhance biomass conversion efficiency. • Emphasis on the environmental benefits of reducing agricultural waste, lowering greenhouse gas emissions, and promoting sustainability through the circular economy. • The review focussed on economic opportunities in industrial applications, including energy, agriculture, and materials, by repurposing rice biomass. Rice biomass, often regarded as agricultural waste, holds immense promise as a renewable resource for producing various bioproducts through biorefinery processes. The current trends of circular economy motivate the exploration of the valorization of rice biomass, particularly rice husk and straw, emphasizing their potential to promote environmental sustainability and economic viability. This review highlights recent advancements in pretreatment techniques, enzymatic saccharification, and bioconversion processes that improve the efficiency of rice biomass utilization. Key innovations, such as deep eutectic solvents (DES), microwave-assisted methods, and chemical modifications, have significantly enhanced enzymatic digestibility, facilitating bioethanol production and other value-added products. Despite these advancements, challenges in large-scale industrial adoption persist, including cost-effectiveness, feedstock variability, and process integration. The study also addresses the economic and environmental benefits of utilizing rice biomass for bio-based products, energy generation, and wastewater treatment, underscoring the role of nanomaterials like rice husk biochar in environmental remediation. Future opportunities for rice biomass valorization lie in enhancing process efficiency, waste stream valorization, and the integration of biorefinery concepts to produce multiple high-value products. Furthermore, fostering a sustainable bioeconomy requires continuous research, public policy support, and industry collaboration to overcome existing barriers. Ultimately, this review presents rice biomass as a critical resource in advancing sustainable development, contributing to reduced greenhouse gas emissions, circular resource use, and a greener future.
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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 | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".