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Lucas Alcantara


Position/Title: Ph.D. Candidate
email: alcantal@uoguelph.ca
Phone: (519) 824-4120 ext. 53786
Office: ANNU 016B

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Short Biography

Lucas obtained his Bachelor’s in Biotechnology (2015) and a Master’s in Biosciences (2017) from the Federal University of Bahia, Brazil. As part of numerous research projects during his undergraduate studies, he acquired experience in genetic polymorphisms, molecular biology, fermentative processes, bioprospection of microorganisms, and in the production and purification of industrial enzymes. He was an exchange student at the University of Toronto (2013), where he improved his skills in molecular biology and enzymology while studying the biological degradation of pine tree bark by different fungi species for bioethanol production. As a master’s student, he decided to understand the role of different bacteria from the rumen in the degradation of plant cell-wall through bioinformatics analysis and to target species with the potential to produce enzymes of industrial interest. His passion for research and new challenges brought him to the Centre for Genetic Improvement of Livestock (CGIL) at the University of Guelph in 2018 to pursue a Ph.D. in Animal Breeding and Genetics, where he seeks to understand the impact of cutting-edge technologies on breeding strategies for optimum sustainable genetic progress in Canadian dairy cattle, under the advisement of Dr. Flavio Schenkel and Dr. Christine Baes

Current Research Projects

  • Estimation of genetic parameters for all genetically evaluated traits in Canadian Holsteins. This project focuses on estimation of genetic parameters and genetic trends, using bivariate linear animal models under a Bayesian approach, for 67 traits genetically evaluated on heifers and first lactation Canadian Holstein cows. At the end of this study, genetic parameters that have not been previously estimated for Canadian cows and updates on those previously estimated will be reported. These estimates will be useful for building new indexes or updating existing selection indexes, and also to predict correlated responses due to the inclusion of novel traits in the breeding programs. This work is being done under the advisement of Dr. Flavio Schenkel and Dr. Christine Baes, in collaboration with Dr. Gerson Oliveira, Kerry Houlahan, and Colin Lynch.
  • Conformation traits of Holstein cows and their association with the Pro$ selection index. There are currently more than 20 conformation traits being genetically evaluated for Canada Holsteins. Understanding the contribution of each of these traits to a monetary index, such as the national selection index Pro$, would help producers make culling and mating decisions to achieve more profitable herds. This study uses multiple linear regression and principal component analysis to assess the association between conformation traits and Pro$. A video of the oral presentation at the 2020 American Dairy Science Association Meeting with some of the results from this research is publicly available here. This work is being done under the advisement of Dr. Flavio Schenkel and Dr. Christine Baes, in collaboration with Dr. Gerson Oliveira.
  • Intelligent algorithms for the prediction of dairy bull fertility. Bovine fertility is a multifactorial process that relies on the quality of semen, female fertility, proper management of herds, and accurate timing of artificial insemination. Much attention has been given to the later factors, and, even though clear impact on reproduction has been seen and attributed to poor semen fertility, not much progress has been achieved in this regard. Due to the complexity of the variables involved in predicting bull fertility, machine learning (ML) and deep learning (DL) algorithms appear as promising methods for predicting bull fertility. Therefore, this study uses ML and DL algorithms to accurately predict bull fertility from semen quality data along with cow fertility and insemination records from Canadian Holsteins. This work is being done under the advisement of Dr. Flavio Schenkel and Dr. Christine Baes, in collaboration with Dr. Dan Tulpan.

Featured Web-Applications Developed

  1. https://cgil.shinyapps.io/genetic_parameters - Interactive tool to facilitate visualization of genetic parameters of all currently genetically evaluated traits of Canadian Holsteins (correlation matrix, network plot, genetic trends, trait definitions, etc) [temporarily unavailable, pending publication]
  2. https://alcantara.shinyapps.io/covid - Daily updates of COVID-19 notifications in Brazil with simple interactive graphs [Available in Portuguese only]

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