Fertigation Method Affects Performance of `Lapins' Sweet Cherry on Gisela 5 Rootstock
Bibliographic record
Abstract
`Lapins' sweet cherry ( Prunus avium L.) trees on Gisela 5 ( Prunus cerasus × Prunus cansecens) rootstock were maintained for the first four growing seasons with eight different fertigation treatments. Treatments involved N application at low (42 mg·L -1 ), medium (84 mg·L -1 ), and high (168 mg·L -1 ) concentrations via sprinkler-fertigation of Ca(NO 3 ) 2 each year about 8 weeks after bloom. The medium N treatment was also applied with P fertigation in early spring or with K fertigation in June. Nitrogen was also broadcast in early spring at 75 kg·ha -1 or followed with medium N sprinkler-fertigated postharvest in August. As a final treatment the medium root zone N concentration was maintained for 8 weeks postbloom via drip fertigation. Throughout the study, irrigation was scheduled to meet evaporative demand based on an electronic atmometer. Drip fertigation, which wet a smaller portion of the orchard floor, considerably reduced per-tree water applications. Tree vigor and pruning weights were reduced for drip-fertigated as compared to sprinkler-fertigated trees although cumulative yield was not significantly different during the study. Fruit size, however, was smaller for this treatment when crop load was at a maximum at year 4. Future research is warranted to insure fruit size can be maintained for heavily cropping drip-fertigated trees. Leaf and fruit N increased linearly as N concentration of sprinkler-fertigating solution increased from low to high values. Optimum yield and highest fruit quality were associated with the medium N treatment. Sprinkler fertigation of P and K did not increase leaf and fruit concentration of either nutrient or meaningfully affect tree performance.
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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".