Machine learning-based crop stress detection in greenhouses

HIGHLIGHTS

• who: Angeliki Elvanidi and Nikolaos Katsoulas from the Laboratory of Agricultural Constructions and Environmental Control, Department of Agriculture Crop Production and Rural Environment, University of Thessaly, Fytokou Str, Volos, Greece have published the article: Machine Learning-Based Crop Stress Detection in Greenhouses, in the Journal: Plants 2023, 52 of /2023/
• what: In this study a Machine Learning (ML) model which takes into account microclimate and crop physiological data to detect different types of crop stress was developed and tested. The reason of this is that, so far, crop physiological parameters were measured using time-consuming . . .
  

   

  

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