Precision Agriculture assumes that not all parts of a field are uniform and that by measuring and managing variability in the field, we can ensure we are not over-applying inputs such as fertilizer, pesticides, or water.
PA involves the use of many tools and technologies such as: global positioning systems (GPS), geographic information systems (GIS), remote sensing by satellite/drone/manned aircraft, proximal sensing by way of soil mapping technologies, LiDAR, yield monitors, variable rate application (VRA), weather stations and soil moisture monitoring systems, and more.
What Will I Learn?
By the end of this microcredential, learners will be prepared to use data to implement technologies for a farm operation to optimize crop inputs, limit negative environmental impacts, and increase efficiency.
Learners will:
- Explore the potential applications of available tools and technologies;
- Investigate the benefits, limitations, and costs of common technologies in smart farming;
- Differentiate between types of data (i.e., drone and satellite imagery) and the applications of each;
- Identify sources of existing data (both free and at cost);
- Recognize potential yield-limiting factors in Prince Edward Island;
To successfully complete the microcredential, learners will be required to:
- Use existing farm data to identify strengths, challenges, and opportunities;
- Develop goals to optimize crop inputs, limit negative environmental impacts, and increase efficiency;
- Select technologies to work toward chosen goals;
- Justify the choice of technologies for a farm operation to optimize crop inputs, limit negative environmental impacts, and increase efficiency.