Unfortunately, extreme swings in weather seem to be the new “normal” for growers. With historic flooding in some areas, late snowfall for some and seemingly never-ending rain for others, this year’s planting season for most in the Midwest was a roller-coaster to say the least. With most areas experiencing significant delays and disruptions many growers ended up with significantly different planting dates across their fields. This creates additional challenges for farmers later during the growing season in managing their crop protection plans. In addition to potential yield reductions from late-planting, monitoring each field for disease risk and other threats is more difficult since many of their fields will be at different growth stages because of the staggered planting dates.

Years like 2019 highlight the benefit and necessity for growers to utilize available technology and tools to monitor their crops efficiently, optimize crop protection application timing and save time so they can get the most out of their crop.

Digital technology can be very helpful to farmers who are experiencing increased crop risks from unpredictable weather. It can be easy to miss the right time for a fungicide application during a delayed or disrupted planting season or when plagued with excessive precipitation during the growing season compressing the application window. But growers can take advantage of emerging technologies such as predictive modeling to help them better understand disease risks in each field and identify the optimal application timing which is critical to maximize fungicide disease protection.

Predictive modeling leverages big data, machine learning and artificial intelligence to provide field specific information to growers about growth stage and disease risk based on seed variety, planting date, tillage practices and weather. Data mining aggregates millions of data points on factors that affect crop health—while machine learning creates algorithms to effectively predict disease risk and optimal fungicide application timing for each specific field, constantly learning and improving recommendations each time more data is captured. Using this data, Artificial Intelligence then identifies threats to fields and send updates to farmers in real-time when disease risk is increasing and a fungicide application is likely to be needed.

Real time updates allow farmers to respond better to emerging challenges like disease. Once disease symptoms are present, it becomes difficult to manage and will likely have an impact on yield and crop quality. And since fungicides are typically preventative applications, it becomes all the more important in a challenging year to get the application right and maximize the ROI and effectiveness of a fungicide.

Time and resources are precious commodities for farmers. Digital technologies can help them make more informed decisions about their crops that, in the end, will increase the likelihood of a profitable season despite the challenges posed by extreme weather.

—David Gray is the head of U.S. Commercial Operations for Global Digital Farming at xarvio.

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