Efficient Use of Nitrogen and Water in High-density Apple Orchards
Bibliographic record
Abstract
In irrigated apple orchard systems, the magnitude and timing of plant demand for nitrogen (N) and retention of N in the root zone to allow root interception are important factors for efficient management of N fertilizer. Results from five experiments in high-density plantings of apple ( Malus domestica ) on dwarfing (`Malling 9') rootstocks are reported. All experimental plots received daily drip irrigation and N applied through the irrigation system (fertigation) with different regimes according to experimental design. Labelled fertilizer applications, whole tree excavation and partitioning and removal of N in fruit and senescent leaves were used to assess tree N demand. Nitrogen requirements ranged from 8 to 40 lb/acre (8.8 to 44 kg·ha -1 ) over the first 6 years after planting and N use efficiency was often low (<30%), likely because supply exceeded demand. Annual growth is supported by N remobilized from storage and taken up by roots. Root uptake of labelled fertilizer was negligible during early spring and the commencement of rapid uptake was associated with the end of remobilization and the start of shoot growth, rendering prebloom fertilizer applications ineffective. Thus timing of N supply to periods of high demand is crucial for improving efficiency. Comparisons were made to determine the effects on N leaching and tree N utilization of irrigation scheduled to meet evaporative demand and irrigation applied at a fixed rate. Water losses beneath the root zone were greater for fixed rate than scheduled irrigation during the coolest months (May, June and September) of irrigation application. Nitrogen leaching followed a similar pattern during times of N fertigation (May and June). Greater N use efficiency was also measured for trees when irrigation was scheduled to meet evaporative demand rather than applied at a fixed rate. The most N efficient management system was for trees receiving a low [50 ppm (mg·L -1 )] fertigated N supply, at 0 to 4 or 4 to 8 weeks following bloom with scheduled irrigation.
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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 | 0.001 | 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 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".