Diagnosis of Induced Resistance State in Tomato Using Artificial Neural Network Models Based on Supervised Self-Organizing Maps and Fluorescence Kinetics

The aim of this study was to develop three supervised self-organizing map (SOM) models for the automatic recognition of a systemic resistance state in plants after application of a resistance inducer. The pathosystem Fusarium oxysporum f. sp. radicis-lycopersici (FORL) + tomato was used. The inorgan...

Descripción completa

Detalles Bibliográficos
Autores principales: Pantazi, Xanthoula Eirini, Lagopodi, Anastasia L., Tamouridou, Afroditi Alexandra, Kamou, Nathalie Nephelie, Giannakis, Ioannis, Lagiotis, Georgios, Stavridou, Evangelia, Madesis, Panagiotis, Tziotzios, Georgios, Dolaptsis, Konstantinos, Moshou, Dimitrios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416397/
https://www.ncbi.nlm.nih.gov/pubmed/36015731
http://dx.doi.org/10.3390/s22165970

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416397/
https://www.ncbi.nlm.nih.gov/pubmed/36015731
http://dx.doi.org/10.3390/s22165970

Ejemplares similares