326Understanding Yield Variability Across Spatial and Temporal Scales

Oral Session

Special Sessions

Two major challenges face precision agriculture today. The first challenge is that adoption of precision agriculture is slower than anticipated in spite of the proliferation of technology on the farm. Adoption lags in part because precision agriculture technologies produced large amounts of data but little of the information needed to support farm management decisions that increased their farming operation. A reason given by top farmers is that they do not understand the yield variability they have observed within their fields over more than a decade of yield monitoring and are uncertain how to manage it for improved crop yield and quality even though they apply inputs site-specifically. The second challenge for precision agriculture emerges from a credible notion that precision agriculture will be needed to achieve solutions to the global challenges of feeding the growing world population in a sustainable way in the face of depleting land, soil, water, and input resources and in response to climate change. Life science companies like Monsanto and Pioneer suggest much of that yield increase will come from improved crop varieties through breeding and genetics but that precision agriculture will be required to maximize seed potential in diverse environments found within fields. Precision agriculture must provide the knowledge and capability of varying crop variety and plant population through variable seeding rate and row spacing and match fertilizer, water, and crop protection inputs to that environment in verifiable sustainable and traceable ways.

Cosponsor(s):

S04 Soil Fertility & Plant Nutrition, Biometry and Statistical Computing, Agronomic Production Systems
Spatial Statistics Application Community, Precision Agriculture Systems Community