How Choice Of Soil Sampling Strategy Impacts Application Accuracy And Economic Of Site-Specific Nutrient Management In Cotton?
Presented by: Dr. Simerjeet Virk, Assistant Professor and Extension Precision Ag Specialist, University of Georgia
Proper nutrient management is important to attain high-yielding cotton. Several soil sampling strategies including both traditional and precision methods –grid and zone –are commonly used by growers across the Cotton Belt to determine nutrient requirements prior to fertilization. With high fertilizer prices, it is important to utilize a soil sampling strategy that not only effectively depicts the actual nutrient spatial variability within a field but is also cost-effective. Information on how different precision soil sampling strategies, especially different grid sizes and zones based on different spatial layers, influence the application accuracy and economics of variable-rate fertilizer applications in cotton will be shared.
Ladder: Large Agricultural Database That Drives Extension And Research
Presented by: Zach Reynolds, Mississippi State University
Big data capture and analytics may be foundational to addressing a multitude of research and Extension areas in the Mid-South. Analysis of large-scale, agricultural data can be used to determine the effects of agronomic practices, management philosophies, and environment on crop productivity and profitability. Therefore, the LADDER program will collect, process, and securely store geospatially specific agronomic and environmental data for the purpose of addressing some of the Mid-South’s primary research and Extension concerns.
On Farm Precision Experimentation And Its Connection With Crop Management
Presented by: Dr. Luciano Shiratsuchi, Associate Professor, LSU AgCenter
Presented by: Mead Hardwick, Louisiana Farmer, Hardwick Planting Company
Practitioners of Precision Agriculture technologies often conduct large plots, long strips experiment on their farms due to the easy yield monitoring capabilities of harvesters to compare treatments. Larger experiments are more reliable than small plot in research station, since they are less prone to human error. The objective of this talk is to present how farmers that own and are equipped with yield monitors and variable rate applicators can get most of the data collected if they design a spatial design to evaluate treatments. We will show some preliminary results of an entire farm seed rate study using variable rate technologies to set up on farm precision experimentation without interference in the operational farm routine.
The Potential Of Precision Agriculture Technologies To Support Implementation Of Site-Specific Management Of Cotton Production In Alabama
Presented by: Dr. Brenda Ortiz, Professor & Extension Specialist, Auburn University
Presented by: Michael Mullek, Alabama Farmer, Mullek Farm
The use of precision agriculture (PA) technologies tomonitor crop, soils,and weather conditions and precisely place inputs such as seeds, fertilizer,and water according to within-field variability is allowing farmers to meet 21stcenturychallenges. In Alabama, PAextension specialists are working closely with stakeholders on evaluation and demonstration of PA technologies. In 2022 at a 64 acres field from the Mullek farms, we demonstrated several PA technologies. A 12-row John Deere planter retrofitted with Precision Planting® technologies was used to evaluate the impact of three downforce treatment (95, 120, and 150 pounds) on three cotton seeding rates. These treatments arranged on a split-split plot design received two nitrogen placement treatments. A Sentera drone was used to collect multispectral images to monitor crop growth. Preliminary results showed as the downforce increased, seeding depth increased, and plant height decreased. The impact of downforce on plant height changed within the field, zone, and with seeding rate. We were able to show the potential of drone images to capturing changes in plant height, crop biomass, and crop yield. These results showed the potential that PA technologies have on addressing within-field variability and adjusting management to that variability.