Effect of Farmyard Manure, Lime and Inorganic Fertilizer Applications on Soil pH, Nutrients Uptake, Growth and Nodulation of Soybean in Acid Soils of Western Kenya
Bibliographic record
Abstract
Soybean is an important crop with nutrition, economic and soil fertility improvement benefits to farmers. However, its production in western Kenya is partly constrained by low soil pH and soil fertility levels. A greenhouse pot study was conducted to evaluate the effects of inorganic fertilizers, farmyard manure and lime application on soil pH, nutrient uptake, growth and nodulation of soybean grown in acidic soils from western Kenya. The experiment was set up in a randomized complete block design with eight treatments: control; NPK; manure; lime; manure+lime; NPK+manure; NPK+lime and manure+lime+NPK. Significant effects of inorganic fertilizers, manure and lime applications were observed on all the variables. Manure, lime and manure+lime treatments increased soil pH by 1.33, 2.19 and 2.28, respectively, above the control treatment. The shoot N was lower under control (1.71-1.81%), NPK (1.85-1.98%) and manure (2.00-2.11%) than under all other treatments. Treatments NPK+lime and manure+lime+NPK recorded higher uptake of P and K nutrients than all other treatments. The control and NPK treatments recorded shorter plants and low leaf area and above-ground biomass compared to other treatments. The NPK+lime and manure+lime+NPK treatments recorded higher plant height and aboveground biomass than other treatments. Lime+manure treatment recorded highest nodule numbers and dry weights per plant. Positive relationships were observed between pH and N, P and K nutrient uptake (R2 ranged between 0.30 and 0.77) and between biomass and N, P and K nutrient uptake (R2 ranged between 0.68 and 0.99). From this study, use of manure and lime could result in improved soil pH for better uptake of nutrients, nodule formation and productivity of soybean in Western Kenya.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".