Infiltration Rate Assessment of Coastal Plain (Ultisols) Soils for Sustainable Crop Production in the Frontiers of Calabar-Nigeria
Bibliographic record
Abstract
The study on infiltration rate assessment of coastal plain soils for sustainable crop production in the frontiers of Calabar, Nigeria, was carried out in order to examine the infiltration rate of soils in the area and its implication in the overall crop production process. Double ring infiltrometer were driven at 5cm into the soil with the aid of a sledge hammer before water was poured simultaneously into the rings. Infiltration rates were taken at 5,10,15, and 30 minutes intervals. The assessment or determination of infiltration rate was preceded by laboratory analysis of soil samples for the particle size distribution. The mean values of 74.0, 12.0: and 12.6 for sand, silt and clay were obtained respectively. While infiltration rates were well above the recommended values for crop production. Result from different locations proved that the area has monolithic soil characteristics. The result equally showed that the least range of infiltration rate of 14.4-60.0 was well above the optimal range of 0.7-3.5 or the suitable infiltration range of 3.5 - 7.5. It would be said, that, given the increasing need for food production to cope with the demand in Calabar Metropolis, the effect of excessive water infiltration as evidence in this study, will continue to impede sustainable crop production except appropriate measures are contemplated. These measures may include adequate cover cropping, temporary abandonment of farm land or skeletal crop farming with compost, green or farmyard manures. This will help improve the structure and restore soil potentials. Apart from these, suitability evaluation of land in order to effectively categorize soils on the basis of their potential for optimal use could as well be imperative.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".