Effect of soil moisture deficit on marketable yield and quality of potatoes.
Bibliographic record
Abstract
Tuber yield and quality are the two main factors that can increase or decrease the market value of potatoes. Soil moisture availability and nutrient concentration within the potato root zone play a pivotal role in controlling tuber yield and quality. This study was conducted in Southern Manitoba to compare the effects of overhead irrigation (IR) and no-irrigation (NI) on marketable tuber yield and quality during the 2013- and 2014-growing seasons. The total yield of potato was not significantly different between the two treatments in both years. In 2013, the marketable yield of the irrigated (IR) treatment (36.89 MT/ha) was 20% higher (p = 0.017) compared to the non-irrigated (NI) treatment (30.74 MT/ha). However, no significant difference in marketable yield was found between the irrigated (39.0 MT/ha) and non-irrigated (43.7 MT/ha) treatments in 2014. Excess nitrate accumulation within the root zone tends to promote the formation of over-sized tubers. Although the incidence of hollow hearts and sugar ends showed a higher trend in the non-irrigated treatment it was statistically not significantly different from the irrigated treatment. Overhead irrigation was found to be economically advantageous to produce better quality potatoes with higher marketable yields.
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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".