Influence of Irrigation Water, Nitrogen and Phosphorus Nutrient Rates on Relative Weight Loss and Sprouting Characteristics of Seed Potato Tubers After Storage
Bibliographic record
Abstract
<!--[if gte mso 9]> Normal 0 false false false EN-US X-NONE X-NONE <![endif]--> Potato has overtime generated special importance in most parts of Kenya and the world as a means of strengthening food security and increasing revenue for farmers. However, potato productivity and industry expansion have been constrained by the poor quality seed tubers being produced in the informal seed sector due to inadequate supply of initial planting materials, improper fertilizer management practices and irregular rainfall patterns. A study was done at the Horticultural Research and Teaching Farm of Egerton University to determine the effect of integration of irrigation water, nitrogen and phosphorus rates on seed tuber relative weight loss and sprouting characteristics after storage. The three factors were tested in a split-split plot design where irrigation water supply was assigned to main plots, N to subplots and P to sub-subplots. The treatments were replicated three times and the trial repeated once. The treatments consisted of three irrigation water rates (40%, 65% and 100% field capacity), applied throughout the potato growth period through drip tube lines. Nitrogen was supplied as urea (46% N) at four equivalent rates of 0, 75, 112.5 and 150 kg N/ha, while phosphorus was supplied at planting time as triple superphosphate (46% P2O5) at four rates of 0, 115, 172.5 and 230 kg/ha P2O5, which translated into 0, 50.6, 75.9, 101.2 kg P/ha. Data collected included relative percentage weight loss, number of sprouts and sprouting percentage. Data collected was subjected to analysis of variance and significantly different means separated using Tukey’s Studentized Range Test at p ? 0.05. The 100% compared to 65% and 40% irrigation water rates resulted in relatively high weight loss, sprout length and reduced the number of sprouts and sprouting percentage of seed tubers. N and P rates generally decreased the relative weight loss, improved the number of sprouts and sprouting percentage. It is recommended to apply low to intermediate irrigation water, intermediate to high N and P rates to reduce the percentage relative weight loss and sprouting characteristics. <!--[if gte mso 9]>
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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) | 0.003 | 0.001 |
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".