Digital and Precision Agriculture (DPA)

Credits: 1. Contact Hours: Lecture 1.

Introduces students to college life, the digital and precision agriculture program, and careers within the profession. (Typically Offered: Fall)

(Cross-listed with ANS 1230X/ AGRON 1230X/ TSM 1230X).
Credits: 1. Contact Hours: Lecture 1.25.

Introduction to artificial intelligence applications in agriculture and life sciences through hands-on learning experiences. Covers fundamental AI concepts, terminology, and machine learning approaches using agricultural examples and no-code tools. Students explore AI applications in crop monitoring, livestock management, precision agriculture, soil analysis, and agricultural robotics. Emphasis on practical problem-solving, interdisciplinary collaboration, and ethical considerations in agricultural AI implementation. No programming experience required. (Typically Offered: Fall)

(Cross-listed with AGRON 2020/ TSM 2020).
Credits: 3. Contact Hours: Laboratory 2, Lecture 2.

Introduction to the principles, practices, and technologies used in digital and precision agricultural. An integrated approach to data interpretation for making cropping and land use decisions. Utilizing tools such as global positioning systems, geographic information systems, equipment monitors, variable rate technologies, spatial data storage, plant and soil sensors, drones, remote sensing, and satellites. (Typically Offered: Fall, Spring)

Credits: Required.

Professional work experience in agronomy. See advisor for program requirements. Offered on a satisfactory-fail basis only. (Typically Offered: Fall, Spring, Summer)

(Cross-listed with AGRON 4020/ TSM 4020).
Credits: 4. Contact Hours: Laboratory 4, Lecture 2.

Prereq: DPA 2020 and (AGRON 3920 or TSM 4330)
An integrated approach to data collection, visualization, and interpretation for designing and implementing cropping and land use decisions, using tools such as global positioning, geographic information systems, equipment monitors, variable rate technologies, spatial data storage, plant and soil sensors, drones, remote sensing, and satellites. Case studies will be emphasized. . (Typically Offered: Fall, Spring)