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Francesca Abbona



Mario Giacobini

Curriculum vitae

Curriculum Vitae

Phd thesis


The aim of the thesis is a comprehensive investigation of the possible improvements in modelling beef farm performance, in order to subsequently integrate it with information systems.

Using the Piemontese breed as a case study, the assessment of beef farm performance was investigated, as well as the attributes influencing the corresponding parameters. Critical points were identified in the measurement of breeding production efficiency, which revolves around cows’ fertility and production, i.e., the calf quota generated yearly. With a particular focus on the weaning period, approximately two months after birth, it emerged that losses related to calf management are consistent, as viable calves go through a very delicate phase, conditioned by multiple factors. The need for a methodology towards the construction of a more appropriate model was outlined. In order to adequately address the issue, two main points needed to be handled. First, the necessity to cope with the management of Big Data and, second, the need for the identification of patterns among the variables, without introducing a priori knowledge or bias into the model.

The approach that responds suitably to this complex issue is the popular Machine Learning, hence proposed and investigated as a flexible tool that, rather than making a priori assumptions, allows the system to learn directly from data. This approach uses indeed the data to continuously build and refine a model for making predictions. An introduction to the problem is given in detail, as well as a sufficiently thorough description of the scenario within which the research study is carried out. Similarly, an exhaustive description of Machine Learning principles is given, starting from the basic concepts behind its use, to then move on to the illustration of all the approaches applied in this research, their strengths, and their conceptual differences.

The research involved an initial pool of 725 representative farms, among which different subsets were extracted thereafter. Information about the farms was elicited from the National Herd-Book, managed by ANABORAPI, and pre-processed in order to apply different techniques. Additionally, information was collected through an on-field questionnaire, regarding also production systems, farm size, animal density, environmental conditions, and diet. Among the different sets of farms, distinct Machine Learning methods were applied. As the main purpose of this research was the identification of a technique able to exploit at the same time feature extraction and simple, intelligible models, the choice of applying Genetic Programming seemed straightforward. It resulted appropriate for the development of the analysis, as it allowed also to exploit all the information contained in the dataset: for each breeding, it was possible to make a comparison using all the data recorded over several years, refining the prediction. Comparative studies with other usually enrolled prediction methods were investigated with promising results in the context of modelling the breeding performance of Piemontese cattle farms.

Research activities

2019, May 02nd-August 05th: NOVA IMS,  Universidade NOVA de Lisboa - Supervision of Prof. Leonardo Vanneschi.

2020, Jan 06th-April 15th: NOVA IMS,  Universidade NOVA de Lisboa - Supervision of Prof. Leonardo Vanneschi.



Abbona F, Vanneschi L, Giacobini M. Towards a Vectorial Approach to Predict Beef Farm Performance. Applied Sciences. 2022; 12(3):1137.

F. Abbona, L. Vanneschi, M. Bona, M. Giacobini, Towards modelling beef cattle management with Genetic Programming, Livestock Science, Volume 241, 2020,104205, ISSN 1871-1413,

Abbona F., Vanneschi L., Bona M., Giacobini M., A GP approach for Precision Farming, 2020 IEEE Congress on Evolutionary Computation (CEC) Proceedings, Glasgow, Scotland (2020).


2020, July 21th, A GP approach for Precision Farming, IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE (WCCI) 2020, Virtual Conference originally planned in Glasgow, Scotland.

2017, October 26th, "Analysis of spatial organization of pastures as a contact network, implications for potential disease spread and biosecurity in livestock", Grugliasco-Torino, Department of Veterinary Science, Journal Club.


2020, July 19th-24th, IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE (WCCI) 2020, Virtual Conference originally planned in Glasgow, Scotland.

2020, April 15th-17th, EvoStar 2020, Virtual Conference originally planned in Seville, Spain. 

2018, May 24th-25th, Statistic and Data Science: new developments for business and industrial applications, Università degli Studi di Torino-Collegio Carlo Alberto, Torino. 

2018, May 3rd-4thSeminari Padovani di Analisi Numerica SPAN 2018, Department of Mathematics Tullio Levi-Civita, Università degli Studi di Padova, Padova.

2018, February 23rd Filiera suinicola: approccio one-health, Università degli Studi di Torino, Cuneo.

2018, February 22nd, Approcci diagnostici ed emergenze sanitarie delle specie avicole e del coniglio da carne e d'affezione, Department of Veterinary Science, Grugliasco, Torino.

2018, February 7th-9th, Ninth Workshop Dynamical Systems Applied to Biology and Natural Sciences DSABNS 2018, Department of Mathematics Giuseppe Peano, Università degli Studi di Torino, Torino.


2019, February 22nd, "OCCAM workshop", Torino, Department of Veterinary Science(held by Dr Sergio Rabellino)

2018, May 15th-18th: "Bibliography and bibliometrics like pros", Doctoral School of University of Turin, Torino.

2018, May 7th-8th: "Scientific Writing", Department of Veterinary Science, Grugliasco (Lecturer: Prof. Carlo Nebbia)

2018, April 13th, Torino, Collegio Carlo Alberto, "An application of Dirichlet Process Mixing for Bayesian Nonparametric Spatial Modeling" (Speaker: Dott. Luigi Riso)

2018, February 14th, Grugliasco-Torino, Department of Veterinary Science, "Why non-rodent domestic and wild animal models are needed for studying brain plasticity", (Speaker: Prof. Luca Bonfanti)

2018, 8th February: "Evaluation of Research and Third Mission", Department of Veterinary Science, Grugliasco (Lecturer: Prof. Luca Bonfanti).

2018, February 6th: "Communication and presentation of scientific data", Department of Veterinary Science, Grugliasco (Lecturer: Prof. Luca Bonfanti).

2018, February 6th: "Image acquisition, manipulation and final figure preparation", Department of Veterinary Science, Grugliasco (Lecturer: Prof. Paolo Accornero).

2018, February 1st, Grugliasco-Torino, Department of Veterinary Science, "Gut health in animal production" (Speaker: Prof. Maria Teresa Capucchio)

2018, January 30th, February 1st: "Norms on Animal Testing and Management of Animal Facilities", Department of Veterinary Science, Grugliasco (Lecturer: Dr Flavia Girolami).


2018, September 20th, "Optimization for prevention of spreading of threats in networks", Torino, Department of Veterinary Science (held by Prof. Krzysztof Michalak)

2018, September 21st, "Cattle Multiplex: The Role of Pastures in Epidemic Diffusion", Torino, Department of Veterinary Science (held by Dr Davide Colombi)

2017, October 21st, Grugliasco-Torino, Department of Veterinary Science, "Luminex technology" (Speaker: Dr Rudd Jorna)

2017, October 18th, Torino, Department of Economics, "Introduction to Machine Learning and Genetic Programming" (Speaker: Prof. Leonardo Vanneschi - Universidade NOVA de Lisboa) 

2017, October 17th, Grugliasco-Torino, Department of Veterinary Science, Journal Club "Machine learning for Biomedical Data" (held by Dr Irene Azzali) 




All of my research products
Last update: 17/02/2022 10:16

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