Enhancing corn leaf fiber as phosphorus adsorbent material
Bibliographic record
Abstract
Abstract The contribution of dissolved phosphorus (P) from tile drain systems in agricultural lands is significant, leading to water impairment and promoting algae bloom development in water bodies. Hence, there is an urgent need for sustainable and efficient technology, such as absorbent material, that can effectively remove P at low concentrations in these systems. This study aimed to evaluate fiber extraction from corn leaves and its potential for reducing dissolved P. Corn fibers were extracted from corn leaves using alkali treatment by varying the concentration of sodium hydroxide (5–15%w/w), extraction temperature (85–95°C), and time (60‐120 min Results of the alkali extraction showed that the highest fiber recovery of 45.18 ± 0.39% g g −1 was achieved at 10% NaOH at 85°C for 60 min condition. To enhance the phosphorus adsorption capacity of the extracted corn fibers, kaolinite clay (0–30% w/w) and calcium carbonate (0–50% w/w) were incorporated into the leaf fiber. Adsorption tests revealed that corn leaf fiber alone reduced phosphate concentration by 8.75 ± 1.49% within 60 minutes. However, when enhanced with 30% w/w kaolinite clay and 35% w/w calcium carbonate, the phosphate concentration in the solution decreased by 79.40 ± 11.90%. Energy‐dispersive X‐ray fluorescence analysis confirmed the presence of phosphorus in the enhanced adsorbent material following treatment. This study demonstrates the potential of enhancing agricultural wastes like corn leaf fiber as a low‐cost alternative for phosphorus removal in agricultural tile drain systems that can later disposed of as fertilizer in a circular economy scheme. Practitioner Points Corn leaf fiber, extracted using alkali treatment, shows potential as a sustainable, low‐cost adsorbent material for phosphorus removal Enhancing corn leaf fiber with kaolinite clay and calcium carbonate significantly improves phosphate reduction Converting agricultural waste like corn leaf as adsorbent material can help manage phosphorus levels in agricultural tile drains
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.059 | 0.036 |
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; both teacher heads agree on what is shown here.
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".