Nitrogen Accumulation and Response in Potatoes by Slow-Release Fertilizers With the 15N Isotopic Technique in a Gypsum Soil
Bibliographic record
Abstract
Nitrogen (N) is the most widely used fertilizer in agriculture for that reason the efficiency and type of fertilizers are constantly generated and evaluated. The objective was to evaluate N in potato development by 15N by three slow-release fertilizers (FLL). Clay-urea and potassium (AUK), three FLLs manufactured and was evaluated with traditional fertilization (Trad); with two doses of 70 kg N ha-1 (N1) and 140 kg N ha-1 (N2) and a control (0 kg N ha-1) with 15N by the isotopic dilution technique. Accumulation in (1) vegetative growth (VG), (2) initiation of tuberization (IT), (3) tuber growth (TG), and physiological maturity (FM) was made. The Fertilizer N yield (RenNtot), the fertilizer N per difference (RenNfdif) and the isotopic method (RenNfiso), the recovery efficiency of N per difference (ERNdif) and isotopic (ERNiso) were determined. In RenNfdif and ERNdif, the higher dose was better and Trad outperformed FLL, in RenNfiso and ERNiso it was similar. Staged in RenNfdif, Trad outperformed the FLLs in all four stages and in RenNfiso, Trad and AUK1 showed better effect in all four stages. In FLL the source of N is Urea and in soils with alkaline pH the enzyme urease is not found and its effect was less than Trad, for that reason is not appropriate to use urea in these soils.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".