Long-term influence of compost on available water capacity of a fine sandy loam in a potato rotation
Bibliographic record
Abstract
An improved soil physical structure, associated with organic amendments in crop rotations, can be viewed as an emergent property. A study was conducted to evaluate the effect of applied compost on soil water retention and available water capacity, and other associative soil properties in a long-term 3-yr potato rotation established on a Charlottetown fine sandy loam (Orthic Humo-Ferric Podzol) in Prince Edward Island. Soil samples (0–10 cm) were obtained from two crop phases (barley and potato) during the fourth cycle of the rotation (after four compost applications) in the 12th year of the experiment. Except for particulate N, compost had little effect on soil organic matter. In comparison to the barley phase, a combination of compost and surface tillage in the potato phase was associated with improved soil porosity parameters and increased soil water contents at −33 kPa (“field capacity” ), −100 and −300 kPa matric potential, compared with the no-compost control. These results indicate that compost stabilized the tillage induced soil aggregates and macro-porosity in the potato phase. Regression analysis showed that soil volumetric water content at both −33 and −1500 kPa matric potential was significantly related to soil C concentration, although the soil available water capacity remained unchanged. The results imply that the “non-nutrient” compost effect on potato productivity was related to soil water retention. Key words: Soil water retention, soil physical and biochemical properties, compost amendment, tillage, potato rotation, eastern Canada
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 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) | 0.000 | 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 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".