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ABE 5009: Control Methods in SmartAg Systems
Design, analysis, simulation and programming modern control methods for applications in production agriculture, biological and food engineering, land and water resources. Students will learn theoretical concepts, application programming, and simulation techniques using classical and modern control approaches, fuzzy logic, neural networks and other intelligent learning algorithms.
Credits: 3
Semester Offered: Spring
Instructor: Dr. Tom Burks
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ABE 5038: Recent Developments and Applications in Biosensors
Provides a broad introduction to the field of biosensors, as well as an in-depth and quantitative view of biosensor design and performance analysis. Fundamental application of biosensor theory will be demonstrated, including biorecognition, transduction, signal acquisition, and post-processing/data analysis.
Credits: 3
Semester Offered: Spring
Instructor: Dr. Jose Reyes
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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.
Credits: 3
Semester Offered: Spring (Even Years)
Instructor: Dr. Tom Burks
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ABE 5310: Controlled Environment Production Systems Design
An introduction to the engineering design of controlled environment agriculture systems, including glazing materials selection, fan sizing for mechanical ventilation, lighting distribution, cooling system design with fan-and-pad evaporative cooling, and heating system design with hot water floor heating.
Pre-Requisites/Co-Requisites:
MAC1147 Precalculus Algebra and Trigonometry and 3 credits of physics
Credits: 3
Semester Offered: Spring
Instructor: Dr. Ying Zhang
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ABE 5442: Bioprocess Engineering
Engineering principles, processes, and techniques for using biological agents for the production of chemicals, food, biofuels, and pharmaceuticals, and waste treatment.
Credits: 3
Semester Offered: Fall
Instructor: Dr. Pratap Pullammanappallil
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ABE 5643C: Biological Systems Modeling
Introduction to concepts and methods of process-based modeling of biological systems; physiological, populational, and agricultural applications.
Credits: 3
Semester Offered: Fall
Instructors: Dr. Greg Kiker and Dr. Rafael Muñoz-Carpena
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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
Credits: 3
Semester Offered: Spring
Instructor: Dr. Yiannis Ampatzidis, Dr. Tom Burks, Dr. Sandra Guzman, Dr. Adam Watson, Dr. Ziwen Yu, Dr. Ying Zhang, Dr. Dana Choi
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ABE 5648: Coupled Natural-Human Systems
Approaches to modeling coupled natural-human systems are explored, drawing from both natural and social sciences. Topics include regime shift from dynamical systems and basic concepts from game theory and social-ecological system literature. These are combined in models that operationalize a conceptual framework. Properties and implications of these models—e.g., resilience and robustness of the coupled systems—will be derived and discussed.
Prerequisite: Basic calculus and college-level probability courses
Credits: 3
Semester Offered: Fall
Instructor: Dr. Rachata Muneepeerakul
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ABE 5663: Applied Microbial Biotechnology
The course will focus on quantification of microbial growth, metabolite production, and microbially mediated degradation and transformation processes emphasizing the application of these tools to design industrial relevant bio processes for biofuels, bioproducts, pollution control and bioremediation.
Prerequisite: Life Sciences, Biological, Chemical or Environmental Engineering coursework
Credits: 3
Semester Offered: Spring
Instructor: Dr. Pratap Pullammanappallil
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ABE 5707C: Agricultural Waste Management
The course will introduce biological processes employed for treatment of agricultural, municipal, and agro-processing residues and wastes. It will include biological, physical and chemical principles related to characterization and analysis of pollutants, biological and physico-chemical transformation of pollutants, and engineering principles for design and operation of treatment systems. Specifically, the course will focus on analysis and design of lagoons, anaerobic digesters and composting systems. Field trips to operating systems will reinforce the concepts taught during lecture.
Prerequisite: 4 or higher classification courses in Biological, Chemical or Environmental Engineering
Credits: 3
Semester Offered: Spring (Odd Years)
Instructor: Dr. Pratap Pullammanappallil
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ABE 5815C: Food and Bioprocess Engineering Design Design and analysis of fermentation, thermal, freezing, evaporation, dehydration; and mechanical, chemical and phase separation processes as governed by principles of conservation of mass and energy, reaction kinetics and rheology of food and biological materials.
Credits: 4
Semester Offered: Fall
Instructor: Dr. Ziynet Boz
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ABE 5936: Writing Grant Proposals for Scholarships and Fellowships
Provides incoming graduate students in the ABE Department an introduction to acquiring 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.
Credits: 2
Semester Offered: Fall
Instructor: Dr. Henry Medeiros
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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
Credits: 3
Semester Offered: Spring (Odd Years)
Instructor: Dr. Tom Burks
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ABE 6017: Seminar on Stochastic Modeling in Ecology and Hydrology
This course takes a problem-based approach to introduce stochastic modeling in the 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.
Credits: 3
Semester Offered: Fall
Instructor: Dr. Rachata Muneepeerakul
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ABE 6031: Instrumentation in Agricultural Engineering Research
Principles and application of measuring instruments and devices for obtaining experimental data in agricultural engineering research.
Credits: 3
Semester Offered: Fall
Instructor: Dr. Tom Burks
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ABE 6035: Advanced Remote Sensing: Science and Sensors
Develop an understanding of remote sensing theory, systems and applications using information obtained from the visible/near infrared, thermal infrared and microwave regions of the EM spectrum.
Prerequisite: MAP 2302 or the equivalent
Credits: 3
Semester Offered: Spring
Instructor: Dr. Jasmeet Judge
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ABE 6037: Remote Sensing in Hydrology
Develops a practical understanding of remote sensing applications to hydrology using observations in different regions of the EM spectrum. The first part of the course covers the basic science and theory of remote sensing. The second part of the course is conducted in a seminar style with an emphasis on literature review, presentations, and discussions.
Prerequisite: MAP2302 or the equivalent (Please contact the instructor if you have questions regarding this)
Credits: 3
Semester Offered: Fall
Instructor: Dr. Jasmeet Judge
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ABE 6252: Advanced Soil and Water Management Engineering
Physical and mathematical analysis of problems in infiltration, drainage, and groundwater hydraulics.
Credits: 3
Semester Offered: Fall (Even Years)
Instructor: Dr. Richard Scholtz
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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
Credits: 3
Semester Offered: Fall (Odd Years)
Instructors: Dr. Rafael Muñoz-Carpena and Dr. Greg Kiker
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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
Credits: 3
Semester Offered: Summer A (Odd Years)
Instructor: Dr. Rafael Muñoz-Carpena
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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
Credits: 3
Semester Offered: Spring
Instructor: Dr. Dengjun Wang
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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.
Co-Requisites: COP 2271 and ABE3612C
Credits: 3
Semester Offered: Spring (Not offered Spring 2024)
Instructor: Dr. William Pelletier
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ABE 6644: Agricultural Decision Systems
Decision Support Systems are programs or tools to organize and synthesize information to support management decision making. They are commonly used to assist with managing agricultural systems, to help solve natural resource management issues, or to assist in policy advising. As such, they are sometimes closely related to or applied within agricultural extension and farmer education and can be both computerized and human powered. They are also commonly used by the private sector to provide information to producers and other stakeholders. With the advancement of remote sensing, Big Date, and the Internet of Things, decision support systems are providing new and challenging opportunities to provide timely and accurate information to a broad range of clients.
Credits: 3
Semester Offered: Spring (Odd Years)
Instructors: Dr. Gerrit Hoogenboom
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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
Credits: 3
Semester Offered: Summer C
Instructors: Dr. Gerrit Hoogenboom
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ABE 6649C: 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 Global Sensitivity and Uncertainty Analysis towards subjects of specific interest.
Prerequisite: This course requires ABE 5643C as a prerequisite or by an admission from one of the instructors.
Credits: 3
Semester Offered: Spring
Instructors: Dr. Greg Kiker and Dr. Rafael Muñoz-Carpena
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ABE 6654: Bio-Based Products
Provides the knowledge for the production of fuels, chemicals, and materials from renewable resources; includes the fundamental principles and practical applications of bio-based products: biorefinery and biobased products overview, fundamental concepts in understanding biorefinery and biobased products; materials, chemical platforms, and fuels from biomass.
Prerequisite: CHM 2045 or CHM 2095 and CHM 2046 or CHM 2096 or equivalent general chemistry courses, or instructor permission
Credits: 3
Semester Offered: Fall
Instructor: Dr. Pratap Pullammanappallil
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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 AI recurrent neural networks.
Credits: 3
Semester Offered: Fall - Not currently offered
Instructor: TBD
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ABE 6905: Individual Work in Agricultural and Biological Engineering
Credits: 1-4 (Max 6)
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ABE 6910: Supervised Research
Credits: 1-5 (Max 5)
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ABE 6931: Seminar
Preparation and presentation of reports on specialized aspects of research in agricultural engineering and agricultural operations management.
Credits: 1
Semesters Offered: Fall, Spring
Instructor: Dr. Richard Scholtz
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ABE 6933: Data Visualization & Dashboards in Agriculture
This course aims to provide students with an understanding of the key principles of data visualization. They will
learn to make insightful and persuasive visualizations using various tools and programming languages.
Credits: 3
Semesters Offered: Fall
Instructor: Dr. Willingthon Pavan
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ABE 6933: Comprehensive Data Management in Agriculture
This course is tailored for both undergraduate and graduate students, aiming to provide a thorough understanding of data management. It covers a broad range of topics from general data management practices and database systems to specialized topics like research data management, Database Management Systems, Microsoft Excel data handling, and data harmonization, following the FAIR principles (findable, accessible, interoperable, and reusable).
Credits: 3
Semesters Offered: Spring
Instructor: Dr. Willingthon Pavan
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ABE 6933: Engineering Applications of Computer Vision and Deep Learning
This course explores modern computer vision and deep learning techniques with an emphasis on their
engineering applications in agricultural and food systems. Students will learn the basic principles of camera models and stereo vision; motion and tracking: optical flow, Kalman filter, Bayes filter, particle filter; image classification, segmentation, and object detection; neural networks and backpropagation; convolutional neural networks (CNN); generative models, transformers; deep reinforcement learning.
Pre-Requisites/Co-Requisites:
Fundamental machine/statistical learning courses or equivalent approved by the instructor. Prior programming experiences in Python, Matlab, and Linux operating systems.
Credits: 3
Semester Offered: Fall
Instructor: Dr. Charlie Li
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ABE 6933: Applied Case Study Data Analysis
Credits: 3
Semester Offered: Spring |
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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.
Credits: 3
Semester Offered: TBA
Instructor: Dr. Nikolay Bliznyuk
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ABE 6933/4932: Advanced Applications of Life Cycle Assessment in Biological Engineering
Introduction and application of life cycle assessment (LCA) to evaluate the environmental impacts of various products, processes, or services related to the water-energy-food nexus. Additional topics include planetary boundaries, systems thinking, circular economy, mass and energy balances, life-cycle costing, social LCA and sensitivity and uncertainty analysis. This is an interdisciplinary course open to students from any major.
Prereq: Knowledge of calculus.
Credits: 3
Semester Offered: Spring
Instructor: Dr. Ana Martin-Ryals and Dr. Ziynet Boz
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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
Credits: 3
Semester Offered: Spring
Instructor: Dr. Fedro Zazueta
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ABE 6933/4932: Advanced Robotic Systems Design
This course provides graduate and undergraduate students foundational skills for the design, implementation, and
performance assessment of agricultural robotic systems.
Prereq: ABE 4171C or equivalent for undergraduate students or ABE 6005 or equivalent for graduate students. Both prerequisite courses can be taken concurrently with this course.
Credits: 2
Semesters Offered: Spring
Instructor: Dr. Henry Medeiros
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ABE6933: Fundamentals & Applications of Solar Energy
Credits: 3
Semester Offered: Spring
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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.
Credits: 3
Semester Offered: Fall
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ABE 6940: Supervised Teaching
Credits: 1-5 (Max 5)
Semesters Offered: Fall, Spring
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ABE 6971: Research for Master's Thesis
Credits: 1-15
Semesters Offered: Fall, Spring, Summer
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ABE 6974: Non-Thesis Project
Credits: 1-15
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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.
Pre-requisites/Co-requisites: MAP2302: Elementary Differential Equations or equivalent.
Credits: 3
Semester Offered: Spring
Instructor: Dr. Richard Scholtz
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