Physical Properties of an Alfisol Under Biofuel Crops in Ohio
Bibliographic record
Abstract
There is an increasing need to develop renewable energy sources from biofuel crops to replace fossil fuels. Biofuel crops may also enhance ecosystem functions such as soil quality, water availability, and nutrient reserves. Therefore, the effects of four biofuel crops (corn (Zea mays), switchgrass (Panicum virgatum), indiangrass (Sorghastrum nutans) and willow (Salix spp.) were evaluated on soil quality at three sites in Ohio to assess the effects of crop species on soil bulk density (ρb), soil moisture characteristics (SMC), water stable aggregate distribution (WSA), and aggregate tensile strength (TS) to 40 cm depth. Overall, results were site-specific, with most differences occurring for the clayey soil at the Northwest site. At the Jackson site, soil in the 0-10 cm layer under switchgrass had a higher moisture content (θ) between 0 and 100 kPa than that under indiangrass. At the Western site, θ under corn at 1500 kPa was higher at 30-40 cm depth. At the Northwest site, soils under corn in the 0-10 cm depth tended to have the lowest θ at 0 and 3 kPa, while soils under switchgrass and willow had 50% more large macroaggregates and fewer small microaggregates than that under corn. Soil TS in the 0-10 cm depth under corn was nearly 160% more than that under other perennial crops. These results suggest that management of perennial biofuel crops can improve soil physical quality. Changes over seven years occur first in the surface soil layers, but further differences may evolve in subsoil layers with increase in time.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".