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Record W2471135956 · doi:10.35196/rfm.2016.1.41-47

EFFECT OF POTASSIUM NITRATE ON THE PRODUCTION OF RICININE BY Ricinus communis AND ITS INSECTICIDAL ACTIVITY AGAINST Spodoptera frugiperda

2016· article· en· W2471135956 on OpenAlexaff
Antonio Flores‐Macías, Gilberto Vela-Correa, Ma. de Lourdes Rodríguez-Gamiño, Yasmin Akhtar, Rodolfo Figueroa‐Brito, Víctor Pérez-Moreno, Miguel Ángel Rico Rodríguez, Miguel Ángel Ramos-López

Bibliographic record

VenueRevista Fitotecnia Mexicana · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicToxin Mechanisms and Immunotoxins
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRicinusChemistryNitrogenSpodopteraLarvaBotanyAnimal scienceFood scienceBiologyBiochemistryRecombinant DNAOrganic chemistry

Abstract

fetched live from OpenAlex

The effect of four nitrogen levels (KNO3: 5, 10, 15 and 20 meq L-1) on the production of ricinine was studied using a semi-hydroponic system. The insecticidal activity of methanolic extracts of Ricinus communis L. leaves against Spodoptera frugiperda Smith larvae was also tested. A dosage – response relationship showed strong positive correlation (R2 = 0.92, P ≤ 0.05) between the nitrogen concentration in the hydroponic solution and ricinine percentage in leaves. A strong correlation (R2 = 0.94, P ≤ 0.05) was also shown for nitrogen content in tissues and ricinine percentage. The use of nitrogen in the form of KNO3 increased the production of ricinine, and it also affected mortality of S. frugiperda larvae. LC50 for ricine methanolic extracts of R. communis leaves on S. frugiperda were 13,469.12, 15,754.34, 16,046.11 and 18,155.75 mg mL-1 for nitrogen concentrations of 20, 15, 10 and 5 meq L-1 respectively. Increased nitrogen concentration in the hydroponic solution associated with increments in leaf area and ricinine concentration. This indicates that nitrogen concentration can be manipulated to improve production of this alkaloid, and the extracts used for crop protection.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueRevista Fitotecnia MexicanaSame topicToxin Mechanisms and ImmunotoxinsFrench-language works237,207