Setting the Record Straight on Precision Agriculture Adoption

There is a perception that adoption of precision agriculture (PA) has been slow. This study reviews the public data on farm level use of PA in crop production worldwide. It examines adoption estimates for PA from completed surveys that utilized random sampling procedures, as well as estimates of adoption using other survey methods, with an objective to document the national or regional level adoption patterns of PA using existing data. The analysis indicates that Global Navigation Satellite Systems (GNSS) guidance and associated automated technologies like sprayer boom control and planter row or section shutoffs have been adopted as fast as any major agricultural technology in history. The main reason for the perception that PA adoption is slow is because PA is often associated with variable rate technology (VRT)—just one of many PA technologies, one of the first adopted by many farmers, but that now rarely exceeds 20% of farms. This level of adoption suggests that farmers like the idea of VRT, but are not convinced of its value. VRT adoption estimates for niche groups of farmers may exceed 50%. The biggest gap in PA adoption is for medium and small farms in the developing world that do not use motorized mechanization.

Download journal article aj-0-0-agronj2018.12.0779.

Digital Agriculture Posts

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,...

two students lean over a counter as the tinker on a remote controlled car together

Digital Ag Club’s Scarecrow-bot making its debut at Boiler Gold Rush

Thumping hind legs. Two pointed ears. White, fluffy cottontails. The markers of an enemy to...