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.

featured article

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…


Current Posts

Fertilizer Recommendations Tool

The Tri-State Fertilizer recommendations are a collaborative effort among agronomists and like-minded experts from Indiana, Ohio, and Michigan. This spreadsheet implementation using Indiana-centric equations does the math for you. If you are new to this style of Excel spreadsheet, there is a brief tutorial video explaining how to use the tool. This Excel workbook also…


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…


Key Terms


A mathematical formula that may be used to control variable rate applications.

GIS (Geographic Information System)

A computer based system that is capable of collecting, managing and analyzing geographic spatial data. This capability includes storing and utilizing maps, displaying the results of data queries and conducting spatial analysis.

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.


A deviation or inconsistency in excess of the normal variation from what one would expect to observe.