Peer-Reviewed Manuscripts
2025
- Freitas LA, Ferreira RE, Alves AAC, Dorea JR, Paz CCP, Rosa GJM (2025). Detection of anemic sheep using ocular conjunctiva images and deep learning algorithms. Livestock Science, 294:105669. https://doi.org/10.1016/j.livsci.2025.105669
2024
Bussiman F, Alves AAC, Richter J, Hidalgo J, Veroneze R, Oliveira T (2024). Supervised machine learning techniques for breeding value prediction in horses: An example using gait visual scores. Animals, 14(18). [https://doi.org/10.3390/ani14182723] (https://doi.org/10.3390/ani14182723)
Alves AAC, Fernandes AFA, Breen V, Hawken R, Rosa GJM (2024) Monitoring mortality and welfare-culling in group-housed broilers using machine learning algorithms trained with feeding behavior time-series data. Comput. Electron. Agric., 224:109124. https://doi.org/10.1016/j.compag.2024.109124
Silveira RMF, Silva César LF da, Sousa LCO de, Costa HHA, Vasconcelos ECG, McManus C, Sarti DA, Alves AAC, Landim AV (2024). Carcass traits and morphometry, typification of the Longissimus dorsi muscle and non‑carcass components of hair lambs: Can biscuit bran completely replace corn? A machine learning approach. Tropical Animal Health and Production, 56(4), 162. https://doi.org/10.1007/s11250-024-04007-w
Alves AAC, Fernandes AFA, Lopes FB, Breen V, Hawken R, Rosa GJM. (2024). Genetic analysis of feed efficiency and novel feeding behavior traits measured in group‑housed broilers using electronic feeders.Poultry Science, 103(7), 103737. https://doi.org/10.1016/j.psj.2024.103737
Mota LFM, Arikawa LM, Santos SWB, Fernandes Júnior GA, Alves AAC, Rosa GJM, Mercadante MEZ, Cyrillo JNSG, Carvalheiro R, Albuquerque LG. (2024). Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency‑related traits in Nellore cattle. Scientific Reports, 14, 6404. https://doi.org/10.1038/s41598-024-57234-4
Freitas LA, Savegnago RP, Alves AAC, Stafuzza NB, Pedrosa VB, Rocha RA, Rosa GJM, Paz CCP. (2024). Genome‑enabled prediction of indicator traits of resistance to gastrointestinal nematodes in sheep using parametric models and artificial neural networks. Research in Veterinary Science, 166:105099. https://doi.org/10.1016/j.rvsc.2023.105099
2023
Alves AAC, Fernandes AFA, Lopes FB, Breen V, Hawken R, Gianola D, Rosa GJM (2023) (Quasi) multitask support vector regression with heuristic hyperparameter optimization for whole-genome prediction of complex traits: a case study with carcass traits in broilers. G3 13(8):jkad109. https://doi.org/10.1093/g3journal/jkad109
Freitas LA, Savegnago RP, Alves AAC, Costa RLD, Munari DP, Stafuzza NB, Rosa GJM, Paz CCP (2023) Classification Performance of Machine Learning Methods for Identifying Resistance, Resilience, and Susceptibility to Gastrointestinal Nematode Infections in Sheep. Animals. 13(3):374. https://doi.org/10.3390/ani13030374
Pinto DL, Selli A, Tulpan D, Andrietta LT, Garbossa PLM, Voort GV, Munro Jasper, McMorris M, Alves AAC, Carvalheiro R, Poleti MD, Balieiro JCC, Ventura RV (2023) Image feature extraction via Local Binary Patterns for marbling score classification in beef cattle using tree-based algorithms. Livestock Science. 267:105152. doi:10.1016/j.livsci.2022.105152
2022
Alves AAC, Costa RM, Fonseca LS, Carvalheiro R, Ventura RV, Rosa GJM, Albuquerque LG (2022) A Random Forest-based genome-wide scan reveals fertility candidate genes and potential inter-chromosomal epistatic regions associated with age at first calving in Nellore cattle. Frontiers in Genetics.13:834724. doi:10.3389/fgene.2022.834724
Bresolin T, Passafaro TL, Braz CU, Alves AAC, Carvalheiro R, Chardulo LAL, Rosa GJM, Albuquerque LG (2022). Investigating potential causal relationships among carcass and meat quality traits using structural equation model in Nellore cattle. Meat Science. 187:108771.doi: 10.1016/j.meatsci.2022.108771
2021
Alves AAC, Andrietta LT, Lopes RZ, Bussiman FO, Silva FF, Carvalheiro R, Brito LF, Balieiro JCC, Albuquerque LG, Ventura RV (2021) Integrating Audio Signal Processing and Deep Learning Algorithms for Gait Pattern Classification in Brazilian Gaited Horses. Frontiers in Animal Science 2:681557. doi: 10.3389/fanim.2021.681557
Alves AAC, Espigolan R, Bresolin T, Costa RM, Fernandes Júnior GA, Ventura RV, Carvalheiro R, and Albuquerque LG (2021) Genome-enabled prediction of breeding values for reproductive traits in Nellore cattle using parametric models and machine learning methods. Animal Genetics 52(1):32-46. doi: 10.1111/age.13021
2020
Alves AAC, Costa RM, Bresolin T, Fernandes Júnior GA, Espigolan R, Ribeiro AMF, Carvalheiro R, and Albuquerque LG (2020) Genome-wide prediction for complex traits under the presence of dominance effects in simulated populations using GBLUP and machine learning methods. Journal of Animal Science 98:6. doi:10.1093/jas/skaa179
Cardoso D, Fernandes-Junior G, Scalez D, Alves AAC, Magalhães AFB, Bresolin T, Ventura RV, Li C, Oliveira M, Porto-Neto L, Carvalheiro R, Oliveira HN, Tonhati H, and Albuquerque LG (2020) Uncovering sub-structure and genomic profiles in across-countries subpopulations of Angus cattle. Scientific Reports 10:8770. doi:10.1038/s41598-020- 65565-1
2019
- Alves AAC, Pinzon AC, Costa RM, Silva MS, Vieira EHM, Mendonça IB, Viana VSS, and Lôbo RNB (2019) Multiple regression and machine learning-based methods for carcass traits and saleable meat cuts prediction using non-invasive in vivo measurements in commercial lambs. Small Ruminant Research 171:49-56. doi: 10.1016/j.smallrumres.2018.12.008