For digital agriculture to be successful, it must be economically viable, and be environmentally and socially sustainable as well.  In addition, digital technologies can enable new impacts well beyond production environments, such as product traceability and enabling environmental incentives.  As digital agriculture encompasses a related set of technologies that are often used differently depending on the region and production environment, it is difficult to make general statements about the economics or reasons for adopting digital agriculture.

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Pricing For Local Markets

The growth of local food movements offers farmers economic opportunities to access attractive markets for fresh locally-grown crops, such as farmers markets. Farmers markets, a key outlet for beginning and smaller growers, are considered the centerpiece of local food systems. These markets connect food producers…


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Data Driven Agriculture Webinar Series

During the Spring 2021 semester, Purdue Agriculture hosted a weekly webinar series featuring experts in data science and digital agriculture at Purdue University. Each Thursday from February through May, the Data Driven Agriculture webinars explored ways digital agriculture and data science can impact agriculture today and into the future. “Building on the momentum of last…


Public Data for the Public Good

Nicole Widmar, professor and associate head of agricultural economics at Purdue University recently presented as part of the Data Driven Agriculture webinar series. Public availability of data has helped U.S. agriculturalists engage in the worldwide marketplace in ways that would not have been possible otherwise. Widmar delves into ongoing research on public and consumer perceptions…


Key Terms

Artificial intelligence (AI)

The mechanism by which a machine can take input from the environment via sensors, process this input using the experiences it has gained and take rational and intelligent decision on the environment using actuators, much like how humans do.


An abbreviated term for binary digit, the smallest unit of computer data.


The repeatability of multiple measurements of the same object or condition.

Inverse distance weighting

An interpolation method that gives more weight to known data that is near the point of estimation than those that are farther away.