Multi-sensor plant imaging: Towards the development of a stress-catalogue

Agricultural production is limited by a wide range of abiotic (e.g. drought, waterlogging) and biotic (pests, diseases and weeds) stresses. The impact of these stresses can be minimized by appropriate management actions such as irrigation or chemical pesticide application. However, further optimization requires the ability to diagnose and quantify the different stresses at an early stage. Particularly valuable information of plant stress responses is provided by plant imaging, i.e. non-contact sensing with spatial resolving power: (i) thermal imaging, detecting changes in transpiration rate and (ii) fluorescence imaging monitoring alterations in photosynthesis and other physiological processes. These can be supplemented by conventional video imagery for study of growth. An efficient early warning system would need to discriminate between different stressors. Given the wide range of sensors, and the association of specific plant physiological responses with changes at particular wavelengths, this goal seems within reach. This is based on the organization of the individual sensor results in a matrix that identifies specific signatures for multiple stress types. In this report, we first review the diagnostic effectiveness of different individual imaging techniques and then extend this to the multi-sensor stress-identification approach.