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RESEARCH ON THE INFLUENCE OF ORGANIC AND MINERAL FERTILIZERS ON RAPESEED YIELD AND ASH COMPOSITION OF ITS OIL SEEDS

2022· article· en· W4366181093 on OpenAlexaff
T.V. Zubkova, Svetlana Motyleva, D.V. Vinogradov

Bibliographic record

VenueVestnik of Ulyanovsk state agricultural academy · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsTellabs (Canada)
Fundersnot available
KeywordsRapeseedChemistryZeoliteFertilizerMineralComposition (language)AgronomyManureHuman fertilizationFood scienceHorticultureAnimal scienceBiologyOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The article presents results of a field experiment with application of mineral (NPK and zeolite) and organic fertilizers in the technology of spring rapeseed cultivation, as well as a comparative analysis of the ash composition of rape seeds of Rif variety, depending on the variants of the research. Six variants were studied: growing plants without fertilization (control); mineral fertilizer N60: P60: K60 alone and in combination with zeolite (5 t/ha); pure zeolite (5 t/ha); chicken manure (5 t/ha) alone and in combination with zeolite (5 t/ha). Accumulation of nine main elements (wt., %) contained in the ash of spring rapeseed seeds was studied by the method of energy dispersive spectrometry (X-Ray-analysis). The order of element accumulation was determined: P ≈ K>Mg ≥ Ca>Mo> S>Zn>Mn>Fe. The proportion of P is from 10.852 to 11.855 wt. %; the proportion of K is from 9.933 to 12.343 wt.%; Mg, Ca and Mo are present in rape seeds in similar concentrations within 4.0 -5.8 wt.%. Mutual usage of zeolite and organic fertilizer provided an increase of mineral accumulation in the seeds. Correlations between the elements were established. Higher level of macro- and microelements in seeds, necessary for humans, brings about good perspectives to create functional products based on the studied rape seeds for food enrichment. Positive effect of combined organo-mineral fertilizers on accumulation of mineral substances in rape seeds was established.

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)0.000
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 score0.706
Threshold uncertainty score0.259

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.048
GPT teacher head0.277
Teacher spread0.229 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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