Addresses the institutional setting, business climate, and structure of the food and agricultural markets. Encompasses both the domestic and international dimensions of the food chain, including consumer demand, global sourcing, and worldwide production potential. Focuses on managerial economics, as applied to such topics as food system market structure, the nature and dimensions of domestic and global competition, the components of cost and revenue, and the food system value chain. 

Exposes students to the nature of linkages among agriculture, international markets, and the macro-economy, which are key to the fortunes of U.S. farmers and agribusiness. Exam theories and methods that allow students to establish or quantify these linkages and evaluate the consequences of alternative policies, demonstrating the usefulness of economic analysis as a tool. Also explores current policy issues facing the food and agribusiness industries, which might include farm legislation; environmental regulations; and food safety and nutrition labeling rules, among other policy topics.

Explores the application of contemporary concepts and quantitative techniques for decision making in the face of uncertainty. Focus is on application of statistical tools to decisions facing the food and agricultural business manager.

Explores key areas of risk management of the food and agricultural firm, including price, production, strategic, regulatory, technology, market/competitor, political, financial, and exchange rate risk. Contemporary tools, such as score carding, decision trees, and real options are introduced for quantifying and managing uncertain decisions. 

This course explores integration of the functional areas of business at the corporate level. Heavy emphasis is on analysis of the business environment, setting strategic direction, assessing core competencies, choosing a market position and developing competitive advantage, and organizational implementation and control in the context of the food and agricultural markets. The course makes heavy use of case studies of firms in the food and agricultural marketplace.

Develops a structured approach to problem solving, including problem definition, development of alternatives, identifying consequences, assessing trade-offs, and making informed choices. Research methods and project management concepts will be addressed. A major business analysis project will be framed during the course, to be completed as part of the capstone course in business analysis.

Capstone experience where students will work on individual projects focused on a comprehensive detailed analysis of an issue facing their employer or an issue of general interest to the student. It is expected that this project will draw on tools and concepts developed throughout the MS program and be delivered to an appropriate audience of decision-makers upon completion.

The ability to communicate effectively is necessary for agricultural professionals, organizations and the agricultural industry. Communication is also key to engaging audiences on scientific issues that become controversial. In this eight-week online course, students will be exposed to science communication and issues engagement principles. The course is designed primarily for those with little or no formal communication training. Topics include evidence-based best practices for communicating science; news media and social media influences on controversial science; how to monitor controversial issues; and major theoretical perspectives and strategies for engaging the public on food and agricultural science.

This course will educate students in the use, manipulation and analysis of environmental data by introducing them to scripting languages (e.g., C shell, Python), data types (e.g., ASCII, binary, NetCDF), databases (e.g., XML, DBF) and data visualization software (e.g., GMT, ArcMap) as well as techniques for checking data quality, working with missing data and handling large diverse sources of time series and spatial data.

Students will manipulate, check and insert data from a variety of sources, use that data as input to distributed hydrologic model, analyze model output and learn methods for properly documenting their data use (creation of metadata) and long-term archival storage of those data. Skills learned should be applicable to most computer operating systems, but the majority of work for this class will be done within the Unix/Linux environment.

Students taking this course should have experience with one or more programming languages, including but not limited to C, Fortran, Perl, Python, Java, BASIC or two writing scripts or macros within programs such as MATLAB, S-PLUS, R or SAS.

This course introduces students to the principles of remote sensing and teaches methods for analysis and interpretation of remotely sensed data. The emphasis of the first half of the course is on passive optical technology and methodology for analysis of remotely sensed data.

The second half of the course introduces other sensing technologies and their application to the remote observation of soil, vegetation and water resources (together referred to as land resources) by airborne (manned and unmanned) and space-based sensors.

Students will be introduced to the latest developments in instrumentation and information technology in remote sensing and will learn how to utilize remotely sensed data to support research and decision making in agriculture, science and engineering.

This course provides an introduction to fundamentals of geographic information systems (GIS) for spatially analyzing problems related to environmental, agricultural and engineering domains. You will learn key concepts of GIS, including data sources, projections, spatial analysis methods, data and metadata creation and conceptualization framework for solving spatial problems.

GIS is a powerful tool and most students find it to be interesting and enjoyable. The course will use Esri ArcGIS Pro software. At the end of the course we expect you to be an informed GIS user, as well as being reasonably competent using ArcGIS Pro.

Introduction to the principles of landscape ecology and biogeography with a laboratory devoted to the analysis of spatial data using geographic information systems (GIS) and other database tools.

Landscape ecology focuses on the important relationships of landscape structure (pattern, heterogeneity) and ecological processes (movement of animals, hydrologic dynamics) and how this information is used for natural resource management. Biogeography examines ecological patterns and processes at larger scales (generally at subcontinental to global) for the purposes of managing plants and animals of global importance.

In the last 15 years, tremendous efforts have been made to create spatial databases that help support research and management of natural resources at various scales. The lab will focus on the use and application of these databases that are common in natural resource management settings.