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Record W3192591219 · doi:10.5539/jas.v13n9p97

Productivity Responses of Buckwheat IPR 91 Baili to Different Doses of NPK in Brazil

2021· article· en· W3192591219 on OpenAlexvenueno aff
Giovani Mansani de Araujo Avila, Gislaine Gabardo, Henrique Luis da Silva, Djalma Cesar Clock

Bibliographic record

VenueJournal of Agricultural Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouseHuman fertilizationFertilizerCultivarCropMathematicsField experimentProductivitySignificant differenceCrop yieldAnimal scienceAgronomyToxicologyHorticultureBiologyStatistics

Abstract

fetched live from OpenAlex

Buckwheat (Fagopyrum esculentum Moench) is a prominent crop in today’s agriculture. However, information about its behavior at different doses of NPK fertilization is scarce. The aim of this work was to determine the ideal fertilizer dose for the buckwheat cultivar IPR 91 Baili by establishing the dose-response curve. Two experiments were carried out (greenhouse and in the field). The treatments consisted of different doses of NPK (0, 100, 200, 300, 400 and 500 kg ha-1). After the crop cycle, productivity was obtained. There was a statistical difference between the treatments and the control, in both experiments. The lowest yields were obtained in the controls, 2,301.156 and 2,262.500 kg ha-1, and the highest 4,052.023 and 4,027.778 kg ha-1 at the dose of 500 kg ha-1, in the greenhouse and in the field, respectively. There was no statistical difference between the NPK doses for the yield obtained. The rural producer must use the lowest dose (100 kg ha-1). Future experiments are needed to evaluate the culture response to doses below 100 kg ha-1.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

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)0.0010.000

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 head0.017
GPT teacher head0.241
Teacher spread0.224 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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