AUTHOR=Tran Daniel , Camps Cédric 

TITLE=Early Diagnosis of Iron Deficiency in Commercial Tomato Crop Using Electrical Signals

JOURNAL=Frontiers in Sustainable Food Systems

VOLUME=Volume 5 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/sustainable-food-systems/articles/10.3389/fsufs.2021.631529

DOI=10.3389/fsufs.2021.631529

ISSN=2571-581X

ABSTRACT=Adequate plant nutrition is essential for commercial crop production. There are 18 nutrients that are essential for proper crop development. Each is equally important to the plant, although they are required in vastly different amounts. The absence of any one of these nutrients has the potential to decrease crop yields by negatively affecting associated growth factors and therefore crop yields and quality. Hence, early diagnosis of nutrient imbalances or deficiencies is of crucial importance for farmers. 
In this work, we provide compelling evidence that electrical potential variations in a commercial tomato crop contains information, which can be modelled to detect iron (Fe) deficiency before visual symptoms appear. The proposed supervised machine learning model showed accurate prediction on test data of above 75%. A model built to classify normal conditions (full nutrients) vs. strong Fe deficiency conditions (visible symptoms), enables early detection of slight Fe deprivation i.e. six days prior the appearance of the earliest visual symptoms. Continuous real-time monitoring of crop electrical signals and deployment of predictive algorithms could help farmers improve yields and optimise fertiliser application.