Relationships between soil hydraulic properties, drainage efficiency and cranberry yields
Bibliographic record
Abstract
In cranberry production, efficient drainage systems are essential for the development of precision irrigation methods. Most cranberry fields are equipped with subsurface drainage systems used for water table control and excess water removal. Cranberries (Vaccinium macrocarpon Aiton) are highly sensitive to wet soil conditions, and decreases in crop yield are often caused by a malfunction of the drainage system. The main objective of this study was to identify the effect of soil hydrodynamic parameters on subsurface drainage efficiency and cranberry production. During the 2013 and 2014 cropping seasons, real-time measurement devices were installed in 15 fields in the Quebec region, to monitor water table drawdown. Characterization of the soil hydrodynamic properties was done on undisturbed soil cores collected from these 15 fields, and the relationships between drainage efficiency and soil properties were determined. The results of this study highlight the importance of soil hydrodynamic properties on water table drawdown and cranberry yield and showed that nearly 50% of the variance of water table drawdown and crop yield is explained by soil hydrodynamic properties.
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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 | 0.002 | 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 | 0.001 | 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 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".