High-value utilization of agricultural residues based on component characteristics: Potentiality and challenges
Bibliographic record
Abstract
Agricultural residues (ARs) mainly consist of lignocellulose materials, such as crop straws and by-products from agricultural processing, with a global annual output exceeding 1.9 billion tons. Currently, effective waste management and resource utilization have garnered significant attention. Over the past decades, the results of numerous studies have shown that the use of ARs to produce organic fertilizers, biofuels, and new bio-based materials is an effective strategy for mitigating the global energy crisis and environmental degradation. Pretreatment technology has become a major focus of value-added transformation due to the heterogeneity and complexity of AR. However, most studies mainly concentrated on innovations in pretreatment technology and product quality, with few systematically addressing the comprehensive framework that encompasses composition analysis, pretreatment, transformation path, and energy assessment. This paper reviews the value-added conversion system of AR and analyzes its composition characteristics and pretreatment technologies. It provides a forward-looking perspective and an overview of technological advancement in diverse value-added pathways, such as physical utilization, thermochemical conversion, and biological fermentation. Additionally, it comprehensively evaluates energy consumption and environmental impacts across different conversion methods, addressing a significant gap in systematic evaluation in this field. This study identified key research trends by analyzing 8 641 high-quality articles using VOSviewer software based on Web of Science data from the past decade. The focus has progressively shifted from pretreatment technologies, including “steam explosion”, “microwave” and “enzymatic hydrolysis” to primary products, such as “bioethanol” and “biogas” toward evaluating higher echelon of economic and environmental benefit, including “circular economy”, “carbon emission” and “sustainability”. In addition, this review directly addresses current research challenges, such as technical limitations, cost-benefit analysis, and standardization of environmental impact assessment. It also offers constructive suggestions for future research to enhance the efficiency, environmental friendliness, and sustainability of the value-added transformation of AR.
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How this classification was reachedexpand
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 | 0.000 | 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 teacher head, 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".