The project is the first step in the company’s strategy to digitalize biological products to improve their consistency and efficiency and make them easier to use through machine learning and digital solutions.
Probelte and North Carolina State University are partnering on a digitization project to identify climate and phenological indicators related to Botrytis and build personalized biological treatments. The objectives of this study are to develop improved Botrytis forecasting models with which to design affordable, infield sensor arrays that can be readily deployed to support model testing and production. The research will be carried out in strawberry fields and demonstrate the successful integration of models, infield monitoring and biotechnological product application..
Weather-based predictive modelling for Botrytis forecasting in Strawberries
Botrytis causes massive losses in many crops worldwide. As with other fungi, Botrytis cinerea is closely related to environmental conditions and the local climate. Preventing the disease is complex because many biological and contextual factors determine its appearance, and it is not always possible to use products that ensure efficiency due to its dependency on time and application conditions.
For these reasons, understanding the causes of the appearance of botrytis, or the conditions that promote it, is vital, although extremely complex, to anticipate. Thanks to these models, protective products and techniques can be applied preventively and more efficiently, saving crop losses and unnecessary phytosanitary expenses.
The great benefits of digitization: personalized treatments for maximized crop production and sustainability
The collection of data – and its management and processing – and the conversion of these into useful information for the farmer or field technician, require sophisticated digital tools.
Through this partnership, Probelte and North Carolina State University show the important strategic scope digitalization has for the agrobiotechnology sector. Developing this type of predictive model is a preliminary and basic step to achieving the personalization of crop treatments and, thus, maximum rationalization of resources.
Probelte establishes the values it has been pursuing in the last years through this important collaboration with NC State, making the application of digitization a reality to obtain solutions that help in a custom and specific way in the field.
Botrybel: the biological fungicide digitally applied
For the tests, the researchers will work with a biocontrol called Botrybel, based on a living microorganism strain, Bacillus amyloliquefaciens AH2, which has been isolated and registered for a patent by Probelte.
Botrybel is a foliar biofungicide designed to prevent pests caused by pathogenic fungi in crops, like Botrytis in Strawberries. The product will be applied preventively in different moments and conditions and will be considered in the predictive models generated. With the results, new strategies can be obtained to enhance the effect of biological products, seeking greater efficiency and consistency over time, thus reaching maximum sustainability.