Research project Smart Farming 4.0 – IN4.0 ready hyperspectral image processing platform for disease detection in agriculture and fruit growing

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General introduction

Through a faster detection of plant diseases, farmers could gain in efficiency and minimize use of crop protection products. Within the project 'Proeftuin Smart Farming 4.0 ', the researchers chose two plant disease cases in which they wanted to raise the digital image recognition and the diagnostic interpretation to a (near) market ready level. First, it concerns alternaria (a fungal disease) in potato cultivation and, second, fire blight in apple and pear cultivation. For both diseases, manual field inspections were the norm for detection in the field.

Research approach

To investigate the possibilities of hyperspectral sensors, a prototype was developed for these specific crops and diseases, both based on a drone and tractor platform. Through field experiments and demonstrations with the hyperspectral image processing platform the performance was shown in both use cases. The critical gradual co-creative approach was essential to achieve a broader breakthrough and its eventual use in agriculture.


For the agricultural sectors concerned and their pioneers, as well as with the researchers and developers involved, walking through the typical experimental field steps and thus to participate in the measurements, changes and adjustments was highly revealing. Through experimental fields and demonstrations, the practical possibilities and benefits of a hyperspectral imaging platform were illustrated in both of these challenging cases. The models and processes developed in this project will be elaborated on in follow-up projects, eventually to anchor it in agricultural practice and provide practice-oriented advice for farmers.