Diseases are some of the most difficult types of plant injury to diagnose and manage. The SensorSentry data platform contains a suite of complex disease models for:
Data from the SensorSentry remote monitoring solution can be used to calibrate the model for specific microclimates. Adjusting the parameters will result in better management of pest and disease over a several-season growing period. The analysis function allows for custom calculations using the pest and disease models. A special feature alerts the grower when the incidence of the pest or disease is high, to allow for preventive action.
These disease models have been comprehensively validated to ensure that they provide the most accurate warnings on disease infections and proliferation. The precise calculations are displayed on the intuitive SensorSentry data platform, which facilitates easy dissemination and more timely interpretation of information.
The disease warnings generated from these models advise when high-risk disease periods have occurred and spray applications are required to minimize potential infection. The SensorSentry data platform can be invaluable when structuring successful disease prevention strategies.
Plant diseases prevent the plant from functioning properly and as a result adverse affects are observed. Serious infections can make a high proportion of the crop totally unmarketable—dramatically reducing crop revenue. Adequate control of disease to ensure optimum crop health is therefore imperative season after season.
Disease occurs when a susceptible plant (the host) is attacked by a pathogen under environmental conditions that favor the infection and proliferation of that pathogen. This complex interaction is known as the Disease Triangle. By changing one side of the triangle you can dramatically increase or reduce the likelihood of disease development. For example: unfavorable weather conditions or a disease tolerant variety will reduce disease incidence. On the other hand favorable weather conditions, a particularly susceptible variety and a high over-wintering pathogen inoculum will dramatically increase the likelihood of disease manifestation.
In most crop situations the plant (host) is susceptible to the disease. The disease (pathogen) is invariably present as either dormant spore-bodies that are waiting for the right weather conditions to release spores or as existing spore producing lesions. Environmental conditions are the one variable that ultimately determines whether disease infection and spread will occur. Diseases need specific conditions to develop, with temperature and moisture being the two main driving factors. Monitoring weather conditions enables the risk from disease development to be ascertained and procedures can then be adopted to reduce the potential for disease development.
The best disease management strategies involve the prevention of disease infection, however, knowing when a specific infection event occurred increases the likelihood of a successful eradication strategy post infection. Disease models use weather data to determine the risk of disease infection and spread. The user can set specific disease thresholds tailoring the model workings for their particular situations. The information on infection periods and daily/cumulative risk indexes is then presented enabling disease management strategies to be optimized.
Weather data recorded by sensors installed in the field enable disease models to generate accurate warnings on the state of the disease. This enables specific strategies to be adopted that can control the disease with the minimum amount of resources. The information from disease models assist and complement the observations of crop scouters, providing a better service through this ideal disease warning and management solution.