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Record W7047911415

Identification et quantification des phytohormones dans les macroalgues de l'Est du Canada

2021· other· fr· W7047911415 on OpenAlexaboutno aff

Bibliographic record

VenueSémaphore (Université du Québec à Rimouski) · 2021
Typeother
Languagefr
FieldEngineering
TopicPulsed Power Technology Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSaccharinaEnvironmental factorQualitative analysisSolvent extraction
DOInot available

Abstract

fetched live from OpenAlex

RÉSUMÉ: L'agriculture biologique est en pleine expansion. Les macroalgues sont utilisées en agriculture biologique comme source de nutriments, mais également pour leurs propriétés biostimulantes lesquelles proviennent des phytohormones. Les macroalgues sont abondantes au Canada et peuvent conduire au développement de produits utiles pour l'agriculture. Le contenu en phytohormones peut mener, entre autres, à des produits qui stimulent la croissance et la résistance aux stress biotiques et abiotiques. L'objectif du projet de recherche est de développer une méthode simple et rapide de quantification des différentes phytohormones présentes à l'intérieur de quatre espèces de macroalgues québécoises, ce qui permettra d'effectuer le suivi lors du développement et de l'optimisation des procédés d'extraction et de filtration de concentrés de macroalgues. Les phytohormones sont extraites des macroalgues par macération et extraction accélérée par solvant (ASE), purifié par extraction en phase solide avant d'être quantifié en colorimétrie. Ces méthodes sont appliquées pour la première fois à notre connaissance à la Saccharina latissima. Par la suite, le développement de méthodes chromatographiques couplées à la spectrométrie de masse (GC-MS et LC-MS orbitrap) sera envisagé pour l'identification des phytohormones. Ceci sera une première étape de recherche dans la mise au point de méthode chromatographique. En usine pilote, des concentrés d'algues seront développés et optimisés à partir des méthodes analytiques existantes.Ce mémoire a permis de développer une nouvelle méthode analytique de quantification de l'acide indole-butyrique (IBA) dans la Saccharina latissima en colorimétrie avec le réactif d'Ehrlich. De plus, il a été possible d'identifier de façon qualitative la présence d'acide indole-acétique (IAA) dans les extraits d'algues de S. latissima au GC-MS et de séparer l'acide salicylique (SA), l'acide gibbérellique (GA), la kinétine (K), l'IAA et l'IBA contenu dans un mélange de standards au LC-MS. Ces derniers travaux préliminaires ouvrent la voie à de nouvelles recherches analytiques sur les algues. Le faible niveau de détection au GC-MS dû aux faibles concentrations en phytohormones et les limitations dans la disponibilité du LC-MS, n'ont pas permis davantage d'étude en chromatographie. -- Mot(s) clé(s) en français : Colorimétrie, phytohormones, auxines, cytokinines, cinétiques, optimisation, valorisation, biomasse. -- ABSTRACT: Organic farming is booming. Macroalgae are used in organic agriculture as a source of nutrients, but also for their biostimulant properties, which come from phytohormones. Macroalgae are abundant in Canada and can lead to the development of useful products for agriculture. The phytohormone content can lead, among other things, to products that stimulate growth and resistance to biotic and abiotic stresses.The objective of this project is to develop a simple and rapid method for quantifying the different phytohormones present in four species of Quebec macroalgae, which will allow the follow-up during the development and the optimization of the processes of extraction and filtration of macroalgae concentrates.Phytohormones are extracted from macroalgae by maceration and accelerated solvent extraction (ASE), purified by solid phase extraction before being quantified in colorimetry. These methods are applied for the first time to our knowledge for Saccharina latissima. Subsequently, the development of chromatographic methods coupled with mass spectrometry (GC-MS and LC-MS orbitrap) will be considered for the identification of phytohormones. This will be a first stage of research in the development of a chromatographic method. In the pilot plant, algal concentrates will be developed and optimized using existing analytical methods.This thesis has made it possible to develop a new analytical method for the quantification of indole-butyric acid (IBA) in Saccharina latissima in colorimetry with Ehrlich's reagent. In addition, it was possible to qualitatively identify the presence of indole acetic acid (IAA) in the extracts of algae of S. latissima with GC-MS and to separate the salicylic acid (SA), gibberellic acid (GA), kinetin (K), IAA and IBA contained in a mixture of standard by LC-MS. These preliminary work paves the way for further analytical research on algae. The low level of detection with GC-MS due to the low concentrations of phytohormones and the limitations in the availability of LC-MS, did not allow further study in chromatography. -- Mot(s) clé(s) en anglais : Colorimetry, phytohormones, auxins, cytokinins, kinetics, optimization, valorization, biomass.

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 score0.241
Threshold uncertainty score0.485

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.186
Teacher spread0.180 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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