Early Nitrogen Applications Promote the Initiation of Sweetpotato Storage Roots
Bibliographic record
Abstract
A number of published studies have focused on the effects of N application timing on sweetpotato yield. However, none of them examined the influence of the timing of N fertilisation on the initiation of storage roots (SRs), which largely determines the number of tubers per plant and substantially affect the yield. A pot experiment was conducted in sand culture to evaluate the influence of N application timing (N applied on the planting day, 3, 7 and 14 days after transplanting (DAT), denoted T1, T3, T7 and T14, respectively, and a no N applied control T0) on the plant acquisition of N and the initiation of SRs of ‘Orleans’ cultivar. A previously-determined optimal N rate for the SR formation (Hoagland solution with 100mg/L N) in the experimental system was used. Rapid SR formation was found to require N during the first week after transplanting. No or late N application delayed the initiation of SRs and reduced the number of SRs. No or delayed N application inhibited the formation of regular vascular cambium (RVC) and anomalous cambium (AC) and led to an increase in lignification of stele cells leading to significantly higher proportion of lignified roots. By contrast, plants supplied with N within 7 DAT had a higher rate of SRs and lower rate of lignified roots. Also, earlier N application promoted total plant and root growth measured as higher biomass and storage root weight, as well as higher N accumulation in plants and higher nitrogen recovery efficiency (NRE). Results suggested that the SR formation required N during the first week after transplanting. Therefore, moderate N should be available in soil before or on planting day.
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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".