Course Description
Concepts and analytical techniques used in precision agriculture to make management decisions, such as geostatistics to analyze georeferenced data, development of management zones, integration of sensors with real-time control systems, and big data analytics. Lab exercises will provide experiential learning of topics covered during lectures.
Additional Requirements for Graduate Students:
Graduate students will be required to read recent papers in
the area of precision agriculture assigned to them by the
instructor and turn in weekly assignments based on the papers.
Assignments will be designed to encourage critical thinking. To
enhance presentation and teaching skills, graduate students will
be required to make a presentation to the class on a recent
paper chosen by the instructor. Graduate students will also be
required to write a term paper on a current topic on precision
agriculture. The topic for the term paper will be chosen by the
student in consultation with the instructor. Students will need
to demonstrate the ability to critically read scientific papers
and to integrate scientific information from multiple sources.
Athena Title
Adv Topics in Precision Agri
Prerequisite
CRSS 3030
Undergraduate Pre or Corequisite
CRSS 4050/6050
Grading System
A - F (Traditional)
Course Objectives
1. Understand the principles of geostatistics and learn how to apply to georeferenced data sets relevant to precision agriculture. 2. Understand and use techniques available for delineating management zones. 3. Examine integration of sensors with real-time control systems and how these systems can be used to improve efficiency. 4. Consider the impact of big data and the connected farm. 5. Integrate the concepts from objectives 1-4 into a precision agriculture design project.
Topical Outline
1. Geostatistics a. What is it and how do we use it? b. Applications to data sets relevant to precision agriculture 2. Management zones a. Grid sampling vs. management zones b. Data sets for management zones c. Concepts and tools for delineating management zones d. Effect of environmental variables such as climate on management zones e. Nutrient, pH, and irrigation management zones f. Strategies for spatial management of weeds, insects, and diseases 3. Integration of sensors with real-time control systems a. Soil moisture and plant sensors integrated with variable rate irrigation b. Soil nutrient and plant sensors integrated with variable rate fertilizer applicators c. Other real-time sense and treat systems 4. Big data and the connected farm a. Sensing systems and data flow b. Data filtering and integration c. Big data analytics d. Data delivery and display e. Impact on overall farm efficiency f. Who are the end users of big data and how do we apply the results to the farm? 5. Precision agriculture design project a. Undergraduate students: Integrate concepts in topics 1-4 into a precision agriculture management plan for a conceptual farm. b. Graduate students: Integrate concepts in topics 1-4 into a precision agriculture management plan for a case study farm. c. Graduate students will be required to identify a case study farm, collect operational data from the farm, work with farm manager to develop the management plan, and deliver the plan to the end user.
Syllabus