Diagnosis of induced resistance state in tomato using artificial neural network models based on supervised self-organizing maps and fluorescence kinetics

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• who: Xanthoula Eirini Pantazi et al. from the Laboratory of Agricultural Engineering, School of Agriculture, Aristotle University of Thessaloniki, Thessaloniki, Greece have published the article: Diagnosis of Induced Resistance State in Tomato Using Artificial Neural Network Models Based on Supervised Self-Organizing Maps and Fluorescence Kinetics, in the Journal: Sensors 2022, 5970 of /2022/
• what: 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. Among the large variety of crops, tomato is . . .
  

   

  

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