Yield and Yield Components of Potato (Solanum tuberosum) as Affected by Rock Phosphate in Standoff Soil, Southern Alberta Canada
Bibliographic record
Abstract
An experiment was conducted in Standoff, Southern Alberta in April, 2020. The object of the experiment was to investigate effect of rock phosphate organic fertilizer on growth and yield of potato crop grown in Standoff. The varying levels of rock phosphate were broadcasted into the soil at control (0 P Kg ha-1), Low P level (50 P Kg ha-1) and High P level (100 P Kg ha-1). The basal application of urea inform of nitrogen fertilizer was applied at 280 N Kg ha-1. Potato seeds were planted at a distance of 30 by 90 cm. The three treatments were replicated three times, resulting into nine plants. One plant was taken out of uniformly grown tallest plant in each of the treatment to measure yield parameters. The yield parameters collected were subjected to analysis of variance (ANOVA) using Duncan’s Multiple Range Test (DMRT) for separation of means. Results of the experiment indicated that High P and Low P rock phosphate fertilizer levels positively influenced weight of potatoes at 76 and 112 Days after sowing (DAS), respectively while High P rock phosphate fertilizer level got highest number of potatoes than Low P and control at 76 DAS. Furthermore, High P rock phosphate fertilizer level and control plots supported marketable number of potatoes at 76 DAS while High P rock phosphate fertilizer level favoured unmarketable number of potatoes at 112 DAS. It was quite obvious from the results that marketable weight of potatoes was positively influenced by High P rock phosphate level and Low P rock phosphate level at 76 and 112 DAS, respectively whereas unmarketable weight of potatoes was affected by High P rock phosphate fertilizer level at 112 DAS. These results revealed the beneficial use of rock phosphate for potato crop production
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.001 | 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".