Age-related Changes in Response of Highbush Blueberry Plants to Drip Irrigation
Bibliographic record
Abstract
A study was conducted in the Fraser Valley of British Columbia, Canada, to determine the effects of drip configuration (one or two lines with emitters spaced every 0.3 or 0.45 m) and irrigation at moderate or heavy rates (5 or 10 L/plant) in a mature planting of ‘Duke’ highbush blueberry ( Vaccinium corymbosum L.). Results were compared with those published previously from the first 4 years after planting. Although plant size increased with irrigation rate when the plants were younger, there was no added benefit of heavy irrigation on growth in the older plants. However, the plants became more sensitive to soil water deficits with age and, therefore, unlike when they were younger, had greater yields when more water was applied. Berry size and fruit firmness were little affected by irrigation in the older plants, but antioxidants, measured as oxygen radical absorbance capacity (ORAC), were higher with than without irrigation, suggesting that irrigation has the potential to improve the health benefits of blueberries. Growth, yield, and fruit quality were unaffected by drip configuration in any year. Overall, the results revealed that the response of highbush blueberry to drip irrigation changed over time and indicated that irrigation management should be adjusted as a planting matures.
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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 | 0.001 |
| 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".