Effect of Cattle Manure Application on the Gaseous Regime of a Sandy Soil
Bibliographic record
Abstract
Organic amendments are essential to the sustainability of soils, as they help maintain the soil's physical and chemical properties. But, when applied in large dosage amounts, these amendments can drastically change the soil gas composition and have detrimental effects on plant roots and the microbial population. For 208 h, the present study monitored the O2 deficit and loads of CO2 and NH3 in 750 mm deep sand columns, after applying cattle manure at rates equivalent to 0, 20, 40 and 80 tons/ha, within a layer at a depth of 150 mm to 250 mm. Also, a first order model using a manure biological oxygen demand (BOD) reaction rate coefficient k1 and a soil re-aeration rate k2 were used to model the O2 deficit occurring over time in the soil columns. The results indicated that all three gases demonstrated a peak O2 deficit, and loads of CO2 and NH3 after 16 h of manure application and in proportion with the rate of manure application. These peaks dropped quickly during the next 24 h, followed by a steady state up to 168 h and then a gradual loss of gas deficit and loads thereafter. This indicated that the manure/soil layer, at a depth of 150 mm to 250 mm, started to loose its permeability, 24 h after applying the manure. The first order model adequately simulated the soil column O2 deficit and loads of CO2 and NH3, as long as the value of the re-aeration rate k2 drops exponentially with time, as of 24 h. More research work is required to be able to predict the manure/soil gas permeability and its effect on the soil's gaseous regime.
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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".