Interaction of Irrigation and Soil Management on Sweet Cherry Productivity and Fruit Quality at Different Crop Loads that Simulate Those Occurring by Environmental Extremes
Why this work is in the frame
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Bibliographic record
Abstract
‘Cristalina’ and ‘Skeena’ sweet cherry cultivars ( Prunus avium L.) on Gisela 6 ( Prunus cerasus × Prunus canescens ) rootstock planted in 2005 were maintained since 2006 in a randomly blocked split-split plot experimental design with six blocks of two irrigation frequency main plot treatments within which two cultivar subplots and three soil management sub-subplots were randomly applied. The focus of this study was the growth, yield, and fruit quality response of sweet cherry to water and soil management over three successive fruiting seasons, 2009–11, in a cold climate production area. The final 2 years of the study period were characterized by cool, wet springs resulting in low yield and yield efficiency across all treatments. Soil moisture content (0- to 20-cm depth) during the growing season was often higher in soils that received high-frequency irrigation (HFI) compared with low-frequency irrigation (LFI). HFI and LFI received the same amount of water, but water was applied four times daily in the HFI treatment but every other day in the LFI treatment. Consequently, larger trunk cross-sectional area (TCSA) and higher yield were found on HFI compared with LFI trees. Soil management strategies involving annual bloom time phosphorus (P) fertigation and wood waste mulching did not affect tree vigor and yield. Increased soluble solids concentration (SSC) occurred with LFI. Decreased SSC occurred with delayed harvest maturity in trees receiving P fertigation at bloom. The largest fruit size was correlated for both cultivars with low crop loads ranging from 100 to 200 g fruit/cm 2 TCSA. Overall cool, wet spring weather strongly affected annual yield and fruit quality, often overriding cultivar and soil and water management effects.
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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 it