Greece: Lab-in-the-field, multi-spectral imaging technology for early warning of plant stress and pathologies

Lab-in-the-field

Lab-in-the-field

The Mediterranean Agronomic Institute of Chania, the Hellenic Agricultural Organization Dimitra and QCELL, the inventor of field-deployable, real-time multispectral imaging technology, have joined forces to expand the applications of multi-spectral imaging in plant phenotyping. The SpectraPlant project supported by the Region of Crete and the Hellenic Ministry of Development and Investment uses the PhenoCheck lab-in-the-field device from QCELL to collect and classify spectral data for the early diagnosis of stress and pathological conditions in economically important crops. 

Chania, 26/03/2021

The project takes full advantage of the unique capabilities of QCELL’s PhenoCheck camera, a battery operated, wearable/handheld macro-imaging system to monitor crops in situ. The PhenoCheck camera collects spectral information from leaves, stems, fruits, etc. and can display, in real time, a vegetation index and spectral maps in reflectance and fluorescence imaging modes. The camera integrates a specially adapted dome illumination module for isolating ambient light and providing consistently calibrated illumination and reliable measurements. 

 The project partners are focusing on tomato, pepper, aubergine and other plants under biotic and abiotic stresses. At any selected spot, the PhenoCheck handheld camera instantly provides information about changes in the spectral phenotype and helps to monitor and control treatment options. For example, the device might provide early warning for fungal infections (e.g. Botrytis cinerea) before the effects become visible. In addition, the effects of salinity stress might be identified at an early stage and reliably quantified to guide intervention. Another important application of the PhenoCheck camera might be the fruit ripening assessment to predict the optimal harvest date. By offering spectral information in the Near Infrared (NIR) spectral range, internal quality attributes are obtained. These data, together with the measured spectra in the visible part of the spectrum, offer a better prediction of fruit ripeness. 

This technology could become a powerful tool in the hands of agricultural scientists and individual growers, with software modules that address a large array of applications for the smart farm. Accelerating the Agri-tech revolution, the SpectraPlant project team collects carefully curated spectral data and provides laboratory-based analyses of the specimens. The data are analysed with sophisticated mathematical models and artificial intelligence methods to improve the analytical power of the platform and expand its reach in various conditions that affect the plant phenotype. By integrating all these unique features, the PhenoCheck camera comprises a valuable tool for controlling and optimizing farming by enabling reduced use of fertilizers, pesticides and water.