Nitrogen absorption, translocation and distribution from urea applied in autumn to leaves of young potted apple (Malus domestica) trees
Bibliographic record
Abstract
We studied the absorption, assimilation, translocation and distribution of nitrogen (N) from urea applied in autumn to leaves of 1-year-old potted Fuji/M26 apple (Malus domestica Borkh) trees. In early October, all leaves of each tree were painted with either 3% urea (enriched to 10 atom % with 15N) or water (control trees). Four trees were harvested before the treatment and N and amino acid contents were determined. Four trees from each treatment were harvested at 2, 4, 7, 10, 15 and 20 days after urea or water application. Total N, amino acids and 15N in leaves, bark, xylem, shank and roots were analyzed to determine uptake and mobilization of N from urea. Most uptake of 15N by leaves occurred during the first 2 days following application of urea. The mean rate of absorption during these 2 days was 0.29 g m-2 day-1. Amino acids in leaves, bark and roots increased significantly after urea application compared with control values. The highest concentrations of amino acids in leaves and bark occurred 4 days after application, whereas the highest concentrations of amino acids in roots occurred 10 days after application. Total 15N content in leaves peaked 2 days after urea application and then decreased, whereas 15N content in roots and bark increased throughout the experiment. Total 15N content in xylem and shank was low. Leaves absorbed 35% of the 15N applied as urea, and 63.6% of absorbed 15N was translocated out of leaves within 20 days after urea application. We conclude that N from urea was converted to amino acids in leaves after foliar application in autumn, and roots and bark were the main sinks of N from urea applied to leaves.
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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 | 0.000 |
| 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".