Direct Estimation of Maize Leaf Area Index as Influenced by Organic and Inorganic Fertilizer Rates in Guinea Savanna
Why this work is in the frame
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Bibliographic record
Abstract
Leaf area index (LAI) plays an important role in radiation capture, crop growth and yield formation. However, there is limited quantitative data on the influence of poultry manure (PM) and NPK fertilizer rate (NPK) on LAI, as estimated directly. Using a split-plot design with three replications, a field experiment was conducted to determine the effects of three PM rate (0, 2 and 4 t/ha) as main plot and three NPK rate (0:0:0, 60:30:30 and 120:60:60 kg N P2O5 K2O/ha) as sub plot, on LAI and maize grain yield. The maize was planted at a density of 106,666 plants/ha; two rows on a ridge, one plant per stand at 75 × 25 cm. Linear regression was used to establish predictive equations among correlated variables and to describe the degree of associations. The application of PM in maize increased (p < 0.05) number of leaves/plant (NL) at 8 and 10 weeks after sowing maize (WASM). NL, leaf area constant at 6 and 10 WASM, leaf area (LA) and LAI were significantly affected by NPK. LAI correlated positively with NL, LA and grain yield. The coefficient of determination between actual and estimated LA was in the range of 0.85-0.97. The PM × NPK interaction was significant on maize grain yield. The results suggest that small-scale maize farmers faced with challenges in obtaining and transporting large quantities of poultry manure can use 2 t PM/ha with either 60:30:30 kg N P2O5 K2O/ha or 120:60:60 kg N P2O5 K2O/ha to increase grain yield of maize.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 it