Phosphorus Sorption Behavior of Torrefied Agricultural Byproducts under Sonicated Versus Non-Sonicated Conditions
Bibliographic record
Abstract
The application of agrichar derived from organic feedstocks has the potential to improve soil fertility and crop production by providing major nutrients like phosphorus (P) to the crop, and in some cases also reducing P leaching. The effect of agrichar on the leaching of P in soils is not uniform and can vary depending on the type of agrichar and amount applied. The objective of this study was to (i) evaluate the behavior of four agrichars (rice hulls RH, palm fronds PF, horse bedding HB, and bagasse BG) for their ability to retain/release P and (ii) determine the effect of wet sonication on P sorption behavior. The feedstocks were torrefied at 500 °C using a top-lit updraft gasifier and used in multiple batch incubation experiments to evaluate equilibrium phosphorus concentration, maximum P sorption capacity (Smax), and adsorption/desorption potential. Both, RH (12.6 g kg-1) and HB (11.5 g kg-1) contained 10-15 times higher total P concentration than PF and BG, rendering RH and HB as potentially suitable products to be used as soil amendments. However, this initial P content of the agrichar seemed to have an overriding effect on the P sorption behavior of the agrichar. PF had Smax of 676 (±127) mg kg-1 for the non-sonicated agrichar, and 237 (±91) mg kg-1 following sonication. There was significant increase in CEC for PF and BG agrichar upon sonication. PF agrichar increased from 27 (±3) cmolc kg-1 to 41 (±4) cmolc kg-1 with sonication. Similarly, BG agrichar CEC increased from 21 (±2) cmolc kg-1 to 45 (±5) cmolc kg-1 with sonication. Initial total P and Ca concentration and their ratios was found to play significant roles on P adsorption and desorption. Major cations like Ca, Fe, Al and Mn are found to act as active sorption site for phosphorus controlling its fate and mobility along with compounding effects of other physicochemical parameters.
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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) | 0.000 | 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) | 0.001 | 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 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".