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Record W7110267848 · doi:10.5539/jas.v18n1p42

Nitrogen Accumulation and Response in Potatoes by Slow-Release Fertilizers With the 15N Isotopic Technique in a Gypsum Soil

2025· article· W7110267848 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Agricultural Science · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPotato Plant Research
Canadian institutionsnot available
Fundersnot available
KeywordsFertilizerUreaGypsumUreaseNitrogenPotassiumIsotope dilutionSoil water

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.274
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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