Date: Thu Jul 25, 2019
Time: 9:00 AM - 11:00 AM
Moderator: Sally Flis
New fertilizer technologies are able to better match up with crop nutrient demands to create higher yields. However, some of these new technologies are difficult to include into precision agriculture programs due to differences in release rates and limited data sets. This presentation will introduce existing fertilizer coating technologies and market needs. The influence of these technologies on fertilizer uptake will discussed. Finally, case studies will be used to demonstrate how fertilizer coatings can be implemented into a precision ag program.
Trace Genomics has developed the first analytics engine that learns as it maps the living soil. Founded in 2015 to serve the farming community, Trace Genomics helps growers maximize the value of every acre. The company is building the largest, most actionable body of soil intelligence, making thousands of growers experts on what’s underground. Working collaboratively across the agriculture ecosystem, Trace Genomics helps growers optimize costs, manage risk and protect their soil as a capital asset. Headquartered in Silicon Valley—and led by two female founders - Trace Genomics has raised $19 million in financing.
This presentation will explore the adoption of high-resolution soil mapping to compliment the various other data types that exist in precision agriculture, and how agronomists and their growers can practically implement them in-field.
During the first quarter century of precision agriculture, our focus as growers and advisors has been on using a small number of layers to improve infield decisions, as we move forward vast data pillars will be at our disposal. This talk will review these datasets and consider how do we analyze them, improve decisions and make them accessible on farm.
Improved management of soil resources begins with improved knowledge the soil’s condition and capability. Utilizing this knowledge requires a systematic approach for data collection, analysis, and management. In this presentation we will discuss one approach to soil data science: soil information systems. We will discuss the three components of soil information systems: data, inference, and intervention. Using the soil information systems approach, we can better understanding of the interactions between soil data collection, inference, and interpretation. Ultimately, an improved understanding of these interactions can lead to increased efficiency in soil data collection, improved knowledge gain from soil inference, and better knowledge-based agronomic interventions.