Traditionally, analytical-based agricultural decision-making relied on mathematical models that are not optimized for the complexity of agricultural systems with strong interactions across time and space. Newer data science approaches (e.g. data mining, AI, and geospatial statistics) can leverage newly available datasets and other sources of information (e.g. remote sensing, georeferenced ground data, social media, video, text, voice, and other mobile phone-based data) to make sense of the complexity and provide actionable recommendations towards agricultural extension.

In this webinar, we will explore how to move from collective digital information to data-driven agronomy insights, the role of analytics in providing decision support to extension programs, and how to decide what analytical tool is most appropriate to create context-specific content.

Speakers:

• Alice Laborte –  Unit Leader of Spatial Transformation of Landscapes at the International Rice Research Institute (IRRI)
• Matt Miller – Lead Data Scientist at iSDA