Agriculture, Food, and the Environment

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Agriculture, Food and Environment

Food Systems Modeling and Analysis

Agriculture and food industries are a subject of growing interest in terms of their resource requirements, ecological impacts, and sustainability.  This course will provide a foundation in some of the methods of modeling and analysis used to study food systems. We will address several types of approaches, generally building in complexity, starting with net balances of production and consumption and continuing through modeling food production capacity, foodshed analyses, life cycle assessment, and system dynamics and integrated modeling.

Agricultural Science and Policy II

Second part of a two-semester sequence required of AFE students. This course covers the major biological, chemical and physical components of agricultural systems. Each is discussed from the viewpoints of both the underlying natural processes and principles, and their significance for major agricultural, food safety, and environmental policy issues in the US today. In this second semester, the topics are best management practices, livestock systems, food systems, climate change and bio-energy.

Anthropology of Food and Nutrition

This course provides an advanced introduction to anthropological theory and methods designed for food and nutrition science and policy graduate students. Section 1 covers anthropology's four-field modes of inquiry, cross-cutting theoretical approaches and thematic interest groups, their respective institutions and intellectual concerns. Section 2 demonstrates applications of these concepts and methods to cutting-edge food and nutrition issues.

Nutrition Data Analysis

This course will cover knowledge of advanced Stata statistical computing, data base construction, error detection and correction, creation of composite variables, descriptive statistics, univariate analyses, regression analysis of continuous, binary and categorical outcomes, ANOVA & ANCOVA, analysis of clustered data including cluster randomized trials, panel data analysis & introduction to multilevel modeling, factor analysis; and the construction of scales and factor scores.

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