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Assessment of tomato plant status in greenhouse using electrophysiology and supervised machine learning.

Institutional Repository Agroscope

Tran Q. T. D., Camps C., Dutoit F., Najdenovska E., Mazza M., Raileanu L. E., Wallbridge N., Plummer C.

Assessment of tomato plant status in greenhouse using electrophysiology and supervised machine learning.

In: Annual Biocontrol Industry Meeting - ABIM. 21.10., Congress Center Basel, Switzerland. 2019, 1.

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Link: ABIM-2019

Zusammenfassung:

Context: Electric signals are a universal method to rapidly transmit information in living organisms In plants, electric signal has been studied for more than a century In animals, bioelectrical activity measurements in the heart (ECG) or the brain (EEG) provide information about health status Objectives: Development and test of an electrophysiological sensor Enables real-time measurements of electric signal in production conditions, without a Faraday cage Supervised machine learning and automatic classification to detect biotic & abiotic stress

Publikations-ID (Webcode): 42692 Per E-Mail versenden

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Mitarbeitende

Assessment of tomato plant status in greenhouse using electrophysiology and supervised machine learning.