Welcome


Currently, I’m a Professor in the Animal Science Department at the School of Agriculture of the Polytechnic Institute of Braganza (ESA-IPB), where I teach Animal Breeding and Biotechnology Applied to Genetic Improvement. I’m also an active researcher at the Socio-Ecological Systems Group of the Mountain Research Center (CIMO), based at IPB.

Interests

  • Animal Breeding
  • Food Safety Modelling
  • Statistical Modelling
  • Data Science

Education

  • PhD in Animal Science, 2004

    Universidade de Trás-os-Montes e Alto Douro

  • MSc. Animal Production, 1998

    Universidade de Trás-os-Montes e Alto Douro

  • Bach. Zoothecnical Engineering, 1993

    Universidade de Trás-os-Montes e Alto Douro

Skills

R Programming

R Markdown + shiny

Predictive modelling

Dynamic models

Meta-analysis

Goat milk and cheese

Carcass quality

Carcass composition

Recent Posts

Topical Collection

Modern food science is supported by reliable research outcomes depicted or confirmed by data modelling and probability science. Although different types of models can be developed in food science, their objectives mostly revolve around explaining or representing physical, chemical, or biological phenomena in foods or food processes and/or estimating meaningful parameters that are necessary for simulation, prediction, control applications, or optimization/intervention strategies.

AgroStat2021: 16th Edition of the AgroStat Conference

O AgroStat 2021 reunirá investigadores, reconhecidos internacionalmente, e representantes da indústria agro-alimentar para discutir a análise estatística de dados aplicada às ciências agro-alimentares, incluindo: Análise sensorial, Quimiometria, Desenho Experimental, Controlo de Processos, Microbiologia Preditiva e Análise de Risco, Meta-análise, Big Data e software. Está aberta a Submissão de resumos

Projects

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ArtiSaneFood

Innovative Bio-interventions and Risk Modelling Approaches for Ensuring Microbial Safety and Quality of Mediterranean Artisanal Fermented Foods

EcoLamb

Holistic Production to reduce the Ecological Footprint of Meat

Recent & Upcoming Talks

Recent Publications

Quickly discover relevant content by filtering publications.

Risk factors for sporadic listeriosis: A systematic review and meta-analysis

Listeriosis is a major public health concern associated with high hospitalization and mortality rates. The objective of this work was …

A comparison of dynamic tertiary and competition models for describing the fate of Listeria monocytogenes in Minas fresh cheese during refrigerated storage

This study compares dynamic tertiary and competition models for L. monocytogenes growth as a function of intrinsic properties of a …

Classification of beef carcasses from Portugal using animal characteristics and pH/temperature decline descriptors

Previous research showed that meat of optimal tenderness is produced when rigor mortis temperature falls between 12-35 °C. This study …

Tutorials

Avaliação da Condição Corporal de Ovinos

Introdução As ovelhas dispõem de um reservatório de nutrientes nos seus tecidos corporais (músculo, gordura e osso), que podem mobilizar em períodos de deficiência alimentar ou em períodos de elevadas exigências.

Terminologia Zootécnica

Bovinos - Cattle Bovinos - Cattle Bovinos Touro - Macho inteiro (não castrado) Boi - Macho castrado Novilha - Fêmea antes do primeiro parto, geralmente com idade inferior a 18-24 meses Vaca - Fêmea adulta que já pariu Vitelo - animal jovem macho ou fêmea Parto - ato ou efeito de parir Cattle Bull - uncastrated male Steer - castrated male Heifer - female that has not had a calf (with less than 18-24 months of age) Cow - adult female that has had a calf Calf - young aniaml either male or female Calving - the act of parturition in cattle Suínos - Swine Suínos - Swine

Avaliação da Condição Corporal de Caprinos

Introdução Em determinadas fases do ciclo de produção, idependentemente do nível alimentar, é inevitável a mobilização das reservas corporais pelas fêmeas em balanço energético negativo em virtude do seu estado fisiológico (Morand-Fehr et al.

Fitting a reparameterised Gompertz growth model using R

Using the data set “gomp1.csv”, find the parameters of the reparameterised Gompertz model. \[\begin{equation} y= y_0 + (y_{max} -y_0)*exp(-exp(k*(lag-x)/(y_{max}-y_0) + 1) ) \end{equation}\] Import the data set. dat <- read.

Fitting a first-order or loglinear growth model using R

The data set “FirstOrder.csv” contains observations of microbial concentrations (log N) measured at different times (t) at a given environmental condition. Lets fit a first-order growth kinetics model \(log N = log N_0 + k \times t\) to the experimental data.

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