Remote sensing as a useful tool in strawberry cultivation

The need to accurately monitor plant health and forecast productivity at a farm level is more apparent than ever in an increasingly competitive strawberry market. The typical means by which growers make assessments about plant health and forecast supply is through visual inspection. Such methods however are subjective, time consuming and demanding on resources, particularly labour. Image processing appears to offer a way to automate current in-field visual inspections. The hypothetical 'optimal plant health' remains a rather theoretical concept. It is generally accepted that plants experiencing stress differ in some way (e.g., biomass, leaf area index, biochemical parameter content (chlorophyll, anthocyanins, photosynthetic efficiency) compared to plants grown under optimal conditions. These characteristics can therefore be used as indices of plant health. Remote detection, mapping and monitoring of such plant health parameters provides essential information for making timely and effective management decisions. A compact hyperspectral imaging system (COSI) was designed and developed by VITO (Flemish Institute for Technological Research). The lightweight camera system is sensitive to subtle changes in vegetation colour and able to detect differences in plant height. The system can produce high resolution maps (2.5 cm, from altitude of 60 m) allowing single plant assessments. A photogrammetry based processing chain transforms the acquired images into information maps which in turn highlight anomalies in vegetation health enabling the detection of disease and plant stress at an early stage. Based on this information, management decisions can be better targeted within agricultural fields. Several test flights over a strawberry field at pcfruit with a small remotely piloted aircraft (VITO) has demonstrated the functionality of this system. Drought stress, nitrogen deficiency and plant health problems can be brought to the forefront.