Soil Chemistry and Cucumber (Cucumis sativus L.) Yield as Influenced by 16 Years of Composted Poultry Litter Addition
Bibliographic record
Abstract
Poultry litter is increasingly used as organic amendment in market gardening in Côte d’Ivoire. To know about the sustainability of this practice, its impacts on soil quality should be known. This study aimed at assessing the effect on soil fertility of composted poultry litter addition for 16 years following two distinct ways, and identifying soil parameters driving cucumber yield. Trials were laid out in a Fisher randomized block design with 3 treatments replicated 5 times each: Control (C), Surface-applied compost (SAC) and Buried compost (BC). Soil (0-20 cm) chemical characteristics and cucumber growth and yield parameters were measured. Values of all parameters were higher with compost addition compared to the control, except for the C:N ratio. SAC and BC showed similar values of organic C, total N, CEC, pH and available phosphorus. However, Ca2+, Mg2+, K+ and base saturation were higher in SAC than in BC. Relative to values in the control, the greatest changes in soil parameters were observed with exchangeable cations, followed by soil organic matter. Soil organic C and total N concentrations have doubled in SAC while Ca2+, Mg2+, and K+ increased at greater rate (702.4, 400.9 and 186.67% respectively). Also, cucumber growth parameters were the highest with compost addition compared to the control. Significant effect of the compost application way on cucumber was also observed: collar diameter, leaf area and fresh fruit yield in SAC (0.72±0.02 cm, 258.9±12.3 cm2, 11.1±1.3 t ha-1, respectively) were higher than in BC (0.56±0.01 cm, 230.2±2.5 cm2, 5.4±0.5 t ha-1 respectively). Fruit yields in SAC and BC were four times and twice higher than in the control (2.6±0.3 t ha-1), respectively. Cucumber growth parameters were determined by soil concentration in Mg2+ while yield was determined by Ca2+. Composted poultry litter should be promoted for a sustainable soil fertility management in vegetable farming 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) | 0.001 | 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".