Clipped Cowpea (Vigna unguiculata (L.) Walp) Fodder Management: A Potential for Soil Organic Matter Enrichment in Degraded Savannah Soils of Nigeria
Bibliographic record
Abstract
Severe nutrient depletion of the soils of the savannah tropics of Africa over the years has made it difficult to improve the productivity of varieties of crops using cultural practices alone. But interestingly, it has been observed that when a cowpea (Vigna unguiculata (L.) Walp) crop is cut (clipped) before senescence; it can regenerate after defoliation (provided there is enough soil moisture). And when the clipped organic fodder is added and/or ploughed back into the soil, it enriches the soil organic matter (SOM) content that in turn enhances crop productivity. Thus, this study was carried out with the objective of determining the influence of intra-row spacing, clipping height and time on the productivity of cowpea and SOM; at the Institute for Agricultural Research, Ahmadu Bello University, Samaru, Zaria, Nigeria; during the 2002-2005 wet seasons. The experimental lay out was a Randomized Complete Block Design (RCBD), replicated three times. The collected data was analyzed statistically using the analysis of variance test (ANOVA); and the means separation was done using the Duncan Multiple Range Test (DMRT). Results showed that the textural class of the experimental site soil was loam silt; with a conducive pH of (6.6 in 2002 and 5.5 in 2005), for crop growth. The soil organic carbon content (SOC), nitrogen (N) and cation exchange capacity (CEC) were very low (0.30 g kg-1, 0.88 g kg-1 and 4.90 respectively) in 2002. These increased to 10.37 g kg-1, 2.2 g kg-1 and 11.10 respectively in 2005. Total rainfall in 2002 was 1007.9mm and 871.5mm in 2005. Mean air temperature, relative humidity and sunshine hours in 2002 ranged between 21.0-31.5 °C, 16.0-90.6 and 4.5-8.5 respectively; while mean air temperature and relative humidity ranged between 24.7-32.0 °C and 40.5-85.3% respectively in 2005. Total harvested clipped fodder yield was 15t ha-1; and this was added to the soil; and it effectively increased SOM content by about 42%. Consequently, it was concluded that the adoption of this innovative clipping management technology, holds great potential of improving soil pH, increasing soil CEC, SOM and crop productivity generally, for the low technology, resource poor, and subsistence farmers in the region. Without doubt, overcoming SOM decline is a major component in the development of more sustainable agro-systems.
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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) | 0.000 | 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".