Evaluation of a Seed Coating Containing Essential Oil-Loaded Mesoporous Silica Nanoparticles against Pea Bacterial Blight
Notice bibliographique
Résumé
Extended Abstract The current lack of preventive and treatment measures available against bacterial diseases affecting crops is an important problem in agriculture. The use of antibiotics and copper compounds is restricted and can cause bacterial resistance and negative impacts on the environment [1, 2]. Nevertheless, other successful treatment methods have not been fully established. Promising natural compounds exist which have been proven to have strong antimicrobial properties, such as essential oils, and could be used to target bacterial phytopathogens. However, the volatile nature of these compounds limits their application and use in agriculture and a suitable delivery method is extremely desirable. The aim of this study is to evaluate the use of mesoporous silica nanoparticles (MSNPs) to encapsulate essential oils and be used as a preventive and control measure against Pseudomonas syringae pv. pisi, the causative agent of pea bacterial blight [3]. MSNPs allow for a targeted and controlled delivery of the essential oil in the presence of the bacterial pathogen. Essential oils are an environmentally-friendly and safe alternative to antibiotics and other antibacterial agents and the use of nanoparticles as a delivery vehicle allows the oils to be maintained in their active form for long periods of time until their release is needed. MSNPs can protect the loaded biocide from evaporation or degradation while improving their stability and miscibility in aqueous solutions. Additionally, silica is a safe, biodegradable and biocompatible material [4] that is naturally present in plant systems and has been shown to have mainly positive effects on plant growth and development [5, 6, 7, 8]. The present study evaluated the effect of 41 essential oils against P. syringae pv. pisi and compared it to the effect on two other bacterial strains; Pectobacterium carotovorum and Pseudomonas fluorescens. The effect was shown to be strainspecific and one of the most effective oils against P. syringae pv. pisi, ajwain oil, was selected for encapsulation into the MSNPs, which were then incorporated into an alginate seed coating to treat the seeds prior to sowing. Using a seed treatment as a biocide application method reduces the quantity of antimicrobials needed, as well as the amount of nanoparticles released to the environment, when compared to other methods such as soil or foliar applications. This decreases the risk of microbial resistance to biocides while increasing the safety and efficacy of the product. The effect of different alginate formulations on the plant’s germination, growth and development was studied to assess the influence of MSNPs and the use of this technology as a seed treatment against seed-borne pathogens. Peas coated with loaded MSNPs appeared to better resist infection and grow taller than control seeds. Further experiments will be performed to optimise the loading of the MSNPs and maximise the killing efficacy against the pathogens. Additionally, the applications of this study can be extended to both other pathogens as well as other host plants. To our knowledge, this is the first report of MSNPs loaded with a natural biocide and incorporated into an alginate seed coating to protect peas from bacterial phytopathogen Pseudomonas syringae pv pisi. The development of novel and safe biocide delivery methods is essential to optimise food production and achieve a sustainable agriculture in the future.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».