Advanced Agrilytics Holdings, LLC has been granted a patent for their crop characterization index. Leveraging cutting-edge machine learning, the computing system they’ve developed offers a level of precision and insight that was previously unattainable in the agricultural sector.

With an initial focus on soybeans, the company found that most growers were unable to gain an understanding of the growing behavior of their crops in agricultural fields. Instead, growers would track characteristics with subjective descriptions – like tall, bushy, etc. In order to let these growers make more informed decisions, Advanced Agrilytics designed a machine-learning based tool to characterize soybean plants.

This system is engineered to receive comprehensive machine datasets associated with agricultural fields, processing this data through a trained machine-learned model. The outcome is the generation of predicted variety profile index values. These predictions, derived from labeled data inclusive of measured branch and stem bean weights, provide valuable insights into the distinct characteristics of soybean plants, such as how bushy they are and other key traits that determine their growth and health.

By focusing on aspects from the lower portion of the soybean plant, encompassing nodes from the first to the fifteenth above-ground node, the system can offer detailed and accurate characterizations. Moreover, the dataset used is not limited to conventional agricultural data but extends to include topographic data, images of the fields, biomass, and leaf area values. These extensive inputs create a comprehensive analysis that goes beyond traditional farming assessments.

The innovation extends further into its implications for the industry, promising to generate agricultural prescriptions based on the derived variety profile index values. This level of insight, generated by a system that is both highly precise and extensively detailed, has the potential to significantly impact decision-making and overall yield for growers, field managers, trusted advisors, and seed companies.

Advanced Agrilytics’ method comes as a response to the inadequacies of conventional soybean characterization techniques, which often rely on subjective assessments and intensive manual labor. By combining machine learning with comprehensive datasets, this revolutionary approach offers a way to streamline the understanding of soybean growth behavior, crop variety performance, and decision-making in the agricultural landscape.

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