Evergreen FS awarded patent for crop disease prediction tool

Evergreen FS was recently awarded a U.S. patent (no. 12,029,147) for its Crop Disease Prediction and Associated Methods and Systems tool that uses direct-to-machine learning systems that predict crop diseases. 

The patent leverages data science and artificial intelligence to predict and manage plant diseases. The technology collects and analyzes various data points, such as weather conditions, soil, and pathogen pressure, to develop predictive models.

″This technology will really help the farmers we serve because the models can forecast potential disease outbreaks, enabling farmers to take proactive measures to protect their crops sooner,″ said Scott Plato, senior manager of agronomy innovation & technology for Evergreen FS. ″If fewer crops are damaged from disease, this can translate to higher yields and a positive financial impact for the farmer.″

Traditionally, fungicide applications have been scheduled based on human observations and crop growth stages, but sometimes, the treatments are applied too late to make a significant difference. 

″This tool uses data and machine learning to advise agronomists and farmers on the best window of time to apply treatments based on the risk level of disease,″ said Plato. ″The machine learning component has the benefit of compiling data and extrapolating insights that would otherwise go unseen by only relying on our human scouts to detect.″ 

A current example of the tool at work was its detection of Tar Spot and northern corn leaf pathogens earlier this year in Illinois. This insight would not have been known so early in the season, making it more challenging to know when to treat. The crop disease prediction tool will help farmers detect dangerous disease pathogens and stop them before plants can be damaged.

This and other disease detection features are part of Agtrinsic.