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Record W2797687588 · doi:10.5539/jas.v10n5p312

Effects of Macronutrients in the Physiological Quality of Soybean Seeds

2018· article· en· W2797687588 on OpenAlexvenueno aff
Geliandro Anhaia Rigo, Luís Osmar Braga Schuch, Willian Silva Barros, Rodrigo Lamaison de Vargas, Vinícius Jardel Szareski, Ivan Ricardo Carvalho, João Roberto Pimentel, Cristian Troyjack, Lucian Alex dos Santos, Francine Lautenchleger, Tiago Corazza da Rosa, Velci Queiróz de Souza, Tiago Zanatta Aumonde, Tiago Pedó

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsCultivarPhosphorusPotassiumCalciumNutrientSulfurNitrogenChemistryAgronomyMagnesiumHorticultureBiology

Abstract

fetched live from OpenAlex

The aim of this work was to correlate macronutrient content of soybean seeds to physiological quality of different cultivars. The work was developed in the Federal University of Pelotas, in the facilities of the Seed Science and Technology Graduate Program. The experimental design was randomized blocks in arranged in four replicates. The following soybean cultivars were used: BMX Apolo RR (12 lots), BMX Ativa RR (13 lots), BMX Energia RR (26 lots), BMX Força RR (24 lots), BMX Impacto RR (35 lots), BMX Magna RR (16 lots), BMX Turbo RR (44 lots), BMX Potência RR (82 lots) and NA 5909 RR (28 lots), with seeds produced in northwest Rio Grande do Sul. The determination of nutritional contents found in plant tissues of soybean seeds, were measured: Nitrogen (N), Phosphorus (P), Potassium (K), Magnesium (Mg), Calcium (Ca), Sulfur (S). The macronutrient contents of the seeds vary according to genetic characteristics of the cultivars, with higher oscillations of nitrogen, phosphorus, magnesium and sulfur contents present in soybean seeds. Potassium and calcium are defined as the most stable nutrients for the cultivars and seed lots analyzed. High concentrations of nitrogen, phosphorus and calcium are determinants for the physiological quality of soybean seeds.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.270
Teacher spread0.249 · 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 teacher head, 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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

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