Graduate Course Listings

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Graduate Courses in Agricultural and Biological Engineering


ABE 5038: Fundamentals and Applications of Biosensors

Introduction to biosensors, design and performance analysis. Fundamental application of biosensor theory will be demonstrated, including recognition, transduction, signal acquisition, and post processing/data analysis.

Prerequisite: At least senior status in engineering and background in biology including biomolecules.

Instructor: Dr. Eric McLamore

3 Spring

ABE 5152: Advanced Fluid Power Circuits and Control

Engineering analysis, design, and experimentation of electro-hydraulic circuits and systems. Design of hydraulic circuits, fluid power system components, hydraulic actuator analysis, servo and proportional valve performance, and electro-hydraulic control theory and applications.

Prerequisite: Senior level undergraduate standing with EGM3400, EGN3353C completed. Graduate Students are encouraged but not required to take EML5311 concurrently.

3 Spring (Even Years)

ABE 5442: Bioprocess Engineering

Engineering principles, processes, and techniques for using biological agents for production of chemicals, food, biofuels, and pharmaceuticals, and waste treatment.

Instructor: Dr. Pratap Pullammanappilli

3 Fall

ABE 5643C: Biological Systems Modeling

Introduction to concepts and methods of process-based modeling of biological systems; physiological, populational, and agricultural applications.

Prereq: MAC 2312. This course assumes no modeling experience or computer programming. Familiarity with differential equations can aid in most sections of the course.

Instructors: Dr. Greg Kiker, Dr. Rafael Muñoz-Carpena and Dr. Ray Huffaker

3 Fall

ABE 5646: Agricultural and Biological Systems Simulation

Basic concepts of systems analysis, modeling, and computer simulation of dynamic biological and agricultural systems. Methods for working with models, including sensitivity analysis, parameter estimation, and model evaluation. Applications of models in agricultural and biological systems.

Prerequisite: MAC 2312, STA 3032 or STA 4322

Instructor: Dr. Senthold Asseng

3 Spring

ABE 5648: Modeling Coupled Natural-Human Systems

In this course, we will explore some approaches to modeling coupled natural-human systems (CNHs). By definition, modeling such systems requires concepts drawn from both natural and social sciences, a selected few of which will be studied in this course.

Prereq: MAC2312 or equivalent (Basic calculus and college-level probability courses)

Instructor: Dr. Rachata Muneepeerakul

3 Fall

ABE 5707C: Agricultural Waste Management

Engineering analysis and design of systems for the collection, storage, treatment, transport, and utilization of livestock and other agricultural organic wastes and wastewaters. Field trips to operating systems and laboratory evaluation of materials and processes.

Prerequisite: 4 or higher classification.

Instructor: Dr. Pratap Pullammanappilli and Dr. Senthold Asseng

3 Spring

ABE 5815C: Food and Bioprocess Engineering Design

Engineering design of unit process operations employed in agro/food, pharmaceutical, and biological industries including sterilization/pasteurization, radiation, freezing, drying, evaporation, fermentation, distillation.

Instructor: Dr. Pratap Pullammanappilli

4 Fall

ABE 5936: Writing Grant Proposals for Scholarships and Fellowships

Provides incoming graduate students in the ABE Department an introduction to acquire scholarships, fellowships, internships, and graduate assistantships from federal funding agencies. Students will be introduced to funding sources and opportunities, provided guidelines for proposal writing, and prepare a mock proposal for instructor and peer review.

Prerequisite: ENC3246 or equivalent technical writing course, and graduate status in the Agricultural and Biological Engineering Department.

Instructor: Dr. Eric McLamore

2 Fall

ABE 6005: Applied Control for Automation and Robotics

Introduction to industrial controls, programmable logic controllers, and manipulator application programming in agricultural and biological engineering. Kinematics, dynamics, and control strategies for serial link manipulators in agricultural applications.

Prereq: EML 5311, equivalent, or consent

Instructor: Dr. Tom Burks

3 Spring (Odd Years)

ABE 6031: Instrumentation in Agricultural Engineering Research

Principles and application of measuring instruments and devices for obtaining experimental data in agricultural engineering research.

Instructor: Dr. Tom Burks

3 Fall

ABE 6035: Advanced Remote Sensing: Science and Sensors

Develops understanding of remote sensing theory and systems using information obtained from visible/near infrared, thermal infrared, and microwave regions of the EM spectrum.

Prerequisite: MAP 2302

Instructor: Dr. Jasmeet Judge

3 Spring

ABE 6037C: Remote Sensing in Hydrology

Develops practical understanding of remote sensing applications to hydrology using observations in different regions of the EM spectrum. Seminar style with emphasis on literature review and presentation.

Prerequisite: ABE 6035

Instructor: Dr. Jasmeet Judge

3 Fall (Even Years)

ABE 6252: Advanced Soil and Water Management Engineering

Physical and mathematical analysis of problems in infiltration, drainage, and groundwater hydraulics.

Instructor: Dr. Richard Scholtz

3 Spring (Even Years)

ABE 6254: Simulation of Agricultural Watershed Systems

Characterization and simulation of agricultural watershed systems including land and channel phase hydrologic processes and pollutant transport processes. Investigation of the structure and capabilities of current agricultural watershed computer models.

Prerequisite: CWR 4111 and working knowledge of FORTRAN

Instructors: Dr. Rafael Muñoz-Carpena and Dr. Greg Kiker

3 Fall (Odd Years)

ABE 6265: Vadose Zone Water and Solute Transport Modeling

Unsaturated zone modeling of water flow and solute transport processes. Comparative analysis of alternative mechanistic modeling approaches of different complexity.

Prerequisite: Recommended basic use of high level computer language or numerical computing environment (i.e., Matlab, Mathematica, etc.) that allows the student to test algorithms and read existing modeling source code

Instructor: Dr. Rafael Muñoz-Carpena

3 Summer A (Even Years)

ABE 6266: Nanotechnology in Water Research

Applications of environmental nanotechnology to water quality control. Fate and transport of nanomaterials in hydrologic pathways.

Prerequisite: Basic knowledge of hydrology, environmental engineering, and water chemistry

Instructor: Dr. Bin Gao

3 Fall

ABE 6615: Advanced Heat and Mass Transfer in Biological Systems

Analytical and numerical technique solutions to problems of heat and mass transfer in biological systems. Emphasis on nonhomogeneous, irregularly shaped products with respiration and transpiration.

Prerequisite: CGS 2425, ABE 3612C

Instructor: Dr. William Pelletier

3 Spring (Even Years)

ABE 6645C: Computer Simulation of Crop Growth and Management Responses

Teaches the background of computer models for the dynamic simulation of crop growth, development, and yield, and soil and plant water, nutrient, and carbon dynamics, and the application of models to real-world problems. The course is based on a systems analysis approach using DSSAT as a platform.

Recommended that students have a basic understanding of crop and soil science

Instructors: Dr. Gerrit Hoogenboom

3 Summer C

ABE 6840: Data Diagnostics: Detecting and Characterizing Deterministic Structure in Time Series Data

Application of nonlinear time series analysis to detect, characterize, and model deterministic structure in real-world time series data. Topics include signal processing, phase space reconstruction, surrogate data testing, causal network analysis, and phenomenological modeling.

Instructor: Dr. Ray Huffaker


ABE 6905: Individual Work in Agricultural and Biological Engineering


1-4 (Max 6)  

ABE 6910: Supervised Research

  1-5 (Max 5)  

ABE 6931: Seminar

Preparation and presentation of reports on specialized aspects of research in agricultural engineering and agricultural operations management.

Instructor: Dr. Richard Scholtz

1 (Max 2) Fall, Spring

ABE 6933: Applied Case Study Data Analysis

  3 Spring

ABE6933: Foundations of Probability and Math Statistics

This course is a fast-paced introduction to calculus-based probability and statistics aimed at graduate students in engineering and quantitative life sciences. It covers the essentials of STA5325 and STA5328 in a single semester making use of calculus and basic scientific computing to gain understanding about fundamental results and methods of probability and statistics.

Knowledge of calculus of multiple variables. Experience reading and writing simple computer programs in a scripting language (ideally, in R); basic knowledge of scientific computing (e.g., ABE 5643C for ABE students). Undergraduate statistics or a recent first graduate statistical methods class (such as ALS5932 or STA6166) is preferred.

Instructor: Dr. Nikolay Bliznyuk

3 Spring

ABE 6933: Logistics of Agricultural Food Chains

This course covers logistic strategy and concepts for agricultural food chains, and the techniques and tools needed to improve supply chain efficiency and solve logistics problems.

Prereq: Basic skill of Math and Statistics, knowledge of farming operations

Instructor: Dr. Fedro Zazueta

3 Spring

ABE 6933: Seminar on Stochastic Modeling in Ecology and Hydrology

This course takes a problem-based approach to introduce stochastic modeling in context of ecology and hydrology. The students will be asked to study selected papers in detail, through reading and in-class discussion, such that they understand how to set up the problems and derive some results and mathematical expressions reported therein.

Prereq: Graduate standing. Basic calculus and college-level probability course.

Instructor: Dr. Rachata Muneepeerakul

3 Fall

ABE6933: Statistical Machine Learning

This course focuses on methodology and application of tools of statistical (machine) learning. In contrast with courses with similar names offered by Computer Science (CS) and Industrial Engineering (IE), it emphasizes statistical approaches to machine learning. The course prioritizes application and the intuition behind statistical methods rather than formal derivations and justification of the procedures.

Prereq: Recent first graduate statistical methods class (such as ALS5932 or STA6166). Experience reading and writing simple computer programs in a scripting language (ideally, in R). Basic undergraduate quantitative training (calculus and basic matrix/linear algebra). Stats/biostats grad students with stronger math and stats background are welcome.

Instructor: Dr. Nikolay Bliznyuk

3 Fall

ABE6933: Fundamentals & Applications of Solar Energy

  3 Spring

ABE 6933: Spatial Statistics

This course is an introduction to spatial statistics, with a focus on methods that are relevant for public health applications, as well as earth and environmental sciences. It is primarily intended for two audiences: (i) statisticians who want to get exposed to methods and applications and (ii) researchers from other elds with some training in statistics that routinely work with spatial data and would like to learn appropriate statistical models and methods.

Sufficient background: First-year required masters-level coursework in statistics at UF.

Minimal sufficient background: a solid graduate course in regression (such as STA6207) with exposure to matrix notation; a solid course in inference at the level of STA5328; basic scientific and statistical computing skills; motivation (particularly, to pick up R)

Ideal background: in addition to the minimum background above, proficiency with matrix algebra and basic numerical linear algebra (STA6329); statistical computing using R; exposure to linear mixed models, generalized linear models and generalized linear mixed models; masters level sequence in probability and inference STA 6326-6327; interest (and/or need) to apply methods learned in this course in your research work.

Instructor: Dr. Nikolay Bliznyuk

3 Fall

ABE 6933: Advanced Biosystems Modeling

This course serves as an advanced graduate class for continued modeling of biological processes and systems. It is the second and required course of the Biological Modeling Certificate offered by ABE.

The course extends and deepens the curriculum of ABE5643C in that it covers more advanced modeling topics such as: (1) hands-on experience and confidence in formulating, solving (analytically and numerically with R programming), (2) interpreting the output of dynamic biological models; (3) object-oriented design and programming, cellular automata and agent-based model development, (4) High Performance Computing, and (5) Global Sensitivity and Uncertainty Analysis towards subjects of specific interest.

Instructors: Dr. Greg Kiker, Dr. Rafael Muñoz-Carpena and Dr. Ray Huffaker

3 Spring

ABE 6940: Supervised Teaching

  1-5 (Max 5) Fall, Spring

ABE 6971: Research for Master's Thesis

  1-15 Fall, Spring, Summer

ABE 6974: Non-Thesis Project


ABE 6986: Applied Mathematics in Agriculture and Life Sciences

Mathematical methods, including regression analysis, graphical techniques, and analytical and numerical solution of ordinary and partial differential equations, relevant to engineering in agriculture and the related sciences.

Instructor: Dr. Richard Scholtz

3 Spring

AGG 5607: Communicating in Academia - Guide for Graduate Students

This course is designed to teach graduate students about academic writing, specifically focused on research proposals, theses, dissertations, manuscripts, grant proposals, and CVs. The course was developed to teach students about aspects of academic writing that are not normally part of graduate curriculum but are necessary to succeed.

Instructor: Dr. Heather Enloe and Dr. Rachata Muneepeerakul

3 Spring

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Graduate Courses in Agricultural Operations Management


AOM 5334C: Agricultural Chemical Application Technology

Equipment and methods used to apply pesticides in agriculture. Emphasis on techniques to avoid misapplication and pesticide drift.

Instructor: Dr. Wonsuk "Daniel" Lee

3 Fall

AOM 5435: Advanced Precision Agriculture

Principles and applications of technologies supporting precision farming and natural resource data management planning. Global positioning systems (GPS), geographic information systems (GIS), variable rate technologies (VRT), data layering of independent variables, automated guidance, Internet information access, computer software management.

Prereq: Graduate student standing or permission of instructor

Instructor: Dr. Wonsuk "Daniel" Lee

3 Fall (Even Years)

AOM 6735: Irrigation Principles and Management

Designed to teach graduate students about irrigation and gain skills to evaluate an irrigation system, identify parts of a system, and develop
an irrigation schedule based on system characteristics. This course is designed for nonengineers although quantitative ability will be required for calculations and analysis. Prerequisites Students must be proficient in Microsoft Excel and Word. Students should be able to use equation functions and graphing functions in Excel. It is recommended that students have basic understanding of hydrology, unit conversions, and algebra.

Pre-requisites and Co-requisites: Students must be proficient in Microsoft Excel and Word. Students should be able to use equation functions and graphing functions in Excel. It is recommended that students have basic understanding of hydrology, unit conversions, and algebra.

Instructor: Dr. Haimanote Bayabil

3 Fall

AOM 6905: Individual Work in Agricultural Operations Management

  1-6 (Max 6) Fall

AOM 6932: Principles and Issues in Environmental Hydrology

This is a basic course in Environmental Hydrology intended for Agricultural and Natural Resource Managers. The first half of the course covers scientific principles of the hydrologic cycle while, the second half investigates case studies of current water quality and water management issues.

Prereq: This course will use simple and intermediate algebraic equations and trigonometry. Sophomore level chemistry and physics as well as mathematics through pre-calculus are recommended. Significant experience with Microsoft Excel or similar spreadsheets is required in select assignments.

Instructor: Dr. Greg Kiker

3 Fall (Online)

AOM 6932: Agri-Food Systems Innovation

This course is open to undergraduates and graduates alike and requires students to explore the role of innovation in food systems from a reverse chain perspective. Students will gain knowledge of the food system framework from a multi-level (i.e., global, national, and regional/local) perspective, identify current, innovative business and technological practices, as well as present and think critically about future trends in food.

Instructor: J. Adam Watson

3 Spring

AOM 6932: Advanced Intro to Biofuel

Instructor: Dr. Pratap Pullammanappallil   Summer A

AOM 6932: Sustainable Agricultural Intensification

Instructors: Mark Musumba and Dr. Cheryl Palm 2 Spring

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Graduate Courses in Packaging


PKG 5006: Advanced Principles of Packaging

Modern lab instruments and procedures employed for packaging used to solve problems from packaging industry.

Prerequisite: Chemistry, physics, or biology

Instructor: Dr. William Pelletier

3 Fall

PKG 6100: Advanced Computer Tools for Packaging

Label design, bar code technology, spreadsheets, visual basic programming, 3D package design, and distribution efficiency analysis.

Instructor: Dr. Bruce Welt

3 Spring

PKG 6905: Individual Work in Packaging

  1-6 (Max 6)  

PKG 6932: Advanced Food Packaging

Instructor: Dr. Bruce Welt  3 Fall

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