Repository with Ag Data

PURR is the Purdue University Research Repository. PURR publishes and archives digital datasets from researchers across campus and welcomes all kinds of open data from images and videos to spreadsheets and source code. PURR has nearly 4000 data management plans, over 4000 registered researchers, and over 1500 research projects (as of early 2020). You can search for datasets of interest.

In particular, there are several agronomy datasets that might be of interest to researchers and practitioners alike. They cover topics including: corn, alfalfa, sorghum, nitrogen, soil, remote sensing, and much more.

Another set of data regards GPS tracks for machine harvest of wheat in Colorado. this one is an outcome of the Purdue Open Ag Technology and Systems Center (OATS).

Some undergraduates compiled and packaged weather and USDA corn and soybean statistics.

You may want to search PURR for data applicable to your research question, your management decision, or that might be useful in a class project.

Digital Agriculture Posts

Field of corn with sun shining in background

Ignacio Ciampitti returns to Purdue as co-director of IDAAS and professor of agronomy

Purdue University’s College of Agriculture recently welcomed Ignacio Ciampitti, an...

Close-up of Hunsoo Song in front of the pink blossoms of a crabapple tree

Hunsoo Song, the civil engineer who speaks (in algorithms) for the trees

Fire, metal, water, earth and wood. In South Korean tradition, these five elements explain...

Purdue-led TOMI project receives $3.5M grant to turn a decade of data into new tools and strategies for tomato farmers

Indiana ranks third in the nation for tomato production. Lori Hoagland, a professor in Purdue...

Purdue research team uses a computer on top of a drone to gather data

Purdue researchers acquire and analyze data through AI network that predicts maize yield

Artificial intelligence (AI) is the buzz phrase of 2024. Though far from that cultural spotlight,...

Siddhartho Paul and his students use a RTK GPS in a soybean field to get precise location information

Satellites and soils: NIFA and AgSEED grants fund remote sensing data collection and machine-learning models to predict soil properties at farm-to-landscape scales

The few inches of soil you pick up on the tip of your shovel are part of a much bigger picture....

Data-Driven Seminar Series

Purdue College of Agriculture presents a seminar series featuring experts in data science,...