Curso “Processing and Interpreting Food Microbiology Data – developing and ftting mathematical models”
O curso será ministrado pelo Prof. József Baranyi, do Institute of Food Research da Grã-Bretanha e ocorrerá nos dias 23, 24 e 25 de Novembro pela manhã no Auditório 1 do EQA/CTC.
O curso será aberto à toda comunidade acadêmica e para inscrição, enviar: Nome Completo, Vínculo com a UFSC e número de matrícula (discentes) para ppgeal@contato.ufsc.br com o título da mensagem: “Curso – Processing and Interpreting Food Microbiology Data”
Discentes de pós-graduação poderão receber crédito em disciplina. Será emitido certificado de participação.
Breve currículo do Prof. Baranyi:
Prof József Baranyi, a mathematician, was the head of the Computational Microbiology Research Group at the Institute of Food Research, Norwich, UK. He is a Fellow of the of International Academy of Food Science and Technology, and a recipient of the Distinguished Service Award of the American Society for Microbiology. Author or co-author of ca 80 refereed research papers, with >4000 citations; invited speaker, scientific committee member in numerous international conferences; has coordinated several projects funded by UK government, EU and industry. Co-founder of the ComBase Consortium, 2003 (www.combase.cc). Held > 100 workshops all around the world on ComBase and the use of mathematical models and biostatistics in microbiology. He was the statistical advisor of Journal of Applied Microbiology for 15 years and a member of the Editorial Board of Applied and Environmental Microbiology for 16 years. Currently he is member of the Editorial Board of the International Journal of Food Microbiology. His mathematical model on bacterial growth, named after him, is one of the most frequently quoted models in predictive microbiology.
Programa do curso:
Day 1. Mathematical modelling in food microbiology
08:00h – 09:00h 1.1. Basic concepts of mathematical modelling
– Variables and parameters
– Scaling and reparameterizaton of models to interpret parameters
– Role of linearization and approximation in practical applications.
09:00h – 10:00h. 1.2. Deterministic models and their regression in predictive microbiology
– Growth and survival models and their parameters
– Fitting curves and response surfaces to data
– The Least Squares Method
10:00h – 10:30h Break
10:30h – 12:00h. 1.3. Dynamic models, differential equations and their simulation
– Dynamic versions of growth and survival models and their parameters.
– Dynamic / Static; Discrete/Continuous; Deterministic / Stochastic; Empirical/Mechanistic modelling
Day 2. Basics of data processing and statistics.
08:00h – 09:00h 2.1. Understanding the variability of data
– Measurements and measurement errors
– Mean, Median, and Mode; discrete and continuous case
– Measures of spread
09:00h – 10:00h. 2.2. Probabilistic modelling
– Frequency, Histograms and Distributions
– Empirical and theoretical parameters of a distribution
– Conditional probabilities
10:00h – 10:30h Break
10:30h -12:00h. 2.3. Random variables
– Generating samples for random variables for simulation
– Distributions of transformed random variables
Day 3. Quantitative Risk Assessment and Decision Analysis
08:00h – 09:00h 3.1. Analysis of data for decisions on optimizing microbial risk
– Discrete and continuous case
09:00h – 09:30h 3.2. Decision and outcome; quantification of dissimilarities by cost functions
– Sensitivity and robustness
10:00h – 10:30h Break
11:00h – 12:00h. Cost-benefit analysis.
– Objective functions. Optimization.
Horário Atendimento Secretaria