Water management effects on potato production and the environment
Bibliographic record
Abstract
Potatoes (Solanum tuberosum) were grown in a fine sandy loam soil in southern Manitoba in a three-year field study comparing four water management treatments: No Drainage with No Irrigation (NDNI), No Drainage with Overhead Irrigation (NDIR), Free Drainage with Overhead Irrigation (FDIR), and Controlled Drainage with Subirrigation (CDSI). The objectives of the study were (i) to evaluate the effect of the four treatments on yield and quality of potatoes, (ii) to evaluate the effect of water management on the environment, (iii) to estimate the shallow groundwater contribution to potato water requirement, and (iv) to simulate the shallow groundwater hydrology using the DRAINMOD and HYDRUS 1-D model. Subsurface drains were installed at 0.9 m depth and at spacings of 15 m (FDIR) and 8 m (CDSI). Subirrigation was done by pumping water back into the tiles through the drainage control structures. Overhead irrigation was carried out using a travelling gun. Water table depth, soil water content, drainage outflow, nutrient concentration in drainage water, irrigation rate, weather variables, potato yield and quality parameters, and biomass were measured. Compared to the NDNI treatment, the potato yield increase in the other treatments ranged between 15-32% in 2011 and 2-14% in 2012. In 2011, potato yield from FDIR was higher than CDSI (p = 0.011) and NDNI (p = 0.001), and yield from NDIR was higher than NDNI (p = 0.034). In 2012, potato yield was higher in FDIR in comparison to NDNI (p = 0.021). In 2012, the NDIR gave higher dark ends (p = 0.008) compared to other treatments. Under dry conditions, up to 92% of the potato crop water demand could be met by shallow groundwater contribution. Compared to free drainage, controlled drainage was able to lower the nitrate export by 98% (p = 0.033) in 2010 and by 67% (p = 0.076) in 2011, and the phosphate export decreased by 94% (p = 0.0117) in 2010. A major part of the drainage flow and nutrient export took place between April and June in southern Manitoba. DRAINMOD was able to accurately predict the shallow groundwater hydrology for this particular research site.
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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 | 0.000 |
| 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) | 0.000 | 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".