Identification of Techno-Economically Viable Crop Residue Utilization in India
Bibliographic record
Abstract
India generates more than 140 million tonnes of surplus crop residue every year In Haryana, the agricultural sector alone produces 24.64 million tonnes of residue annually; of which only 71% is consumed in various domestic and commercial activities within the state. The rest of the material is burned causing severe contamination of air with smoke. There is an urgent need to identify suitable and sustainable conversion technologies that are efficient, eco-friendly as well as cost-effective for managing the huge available biomass not only in the state but also in the country. This paper reviews briefly the available crop residue and quantities burned, proposes a scheme to incorporate part of the residue in the field for its fertilizer value. The remaining biomass is harvested for animal feed and the excess is converted to bioenergy and biofuels. Among the developed and developing biofuels, the paper identifies biogas production from biomass for on-farm use. Pelletization is identified as an enabling technology to provide high quality feedstock for conversion to heat/power and in near future to advanced biofuels.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".