Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence?
Thoroughly analyzing the sperm and exploring the information obtained using artificial intelligence (AI) could be the key to improving fertility estimation. Artificial neural networks have already been applied to calculate zootechnical indices in animals and predict fertility in humans. This method...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-09-01
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| Series: | Frontiers in Veterinary Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fvets.2023.1254940/full |
| _version_ | 1797678673654972416 |
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| author | Suzane Peres Campanholi Sebastião Garcia Neto Gabriel Martins Pinheiro Marcelo Fábio Gouveia Nogueira José Celso Rocha João Diego de Agostini Losano Adriano Felipe Perez Siqueira Marcílio Nichi Mayra Elena Ortiz D'Avila Assumpção Andréa Cristina Basso Fabio Morato Monteiro Lindsay Unno Gimenes |
| author_facet | Suzane Peres Campanholi Sebastião Garcia Neto Gabriel Martins Pinheiro Marcelo Fábio Gouveia Nogueira José Celso Rocha João Diego de Agostini Losano Adriano Felipe Perez Siqueira Marcílio Nichi Mayra Elena Ortiz D'Avila Assumpção Andréa Cristina Basso Fabio Morato Monteiro Lindsay Unno Gimenes |
| author_sort | Suzane Peres Campanholi |
| collection | DOAJ |
| description | Thoroughly analyzing the sperm and exploring the information obtained using artificial intelligence (AI) could be the key to improving fertility estimation. Artificial neural networks have already been applied to calculate zootechnical indices in animals and predict fertility in humans. This method of estimating the results of reproductive biotechnologies, such as in vitro embryo production (IVEP) in cattle, could be valuable for livestock production. This study was developed to model IVEP estimates in Senepol animals based on various sperm attributes, through retrospective data from 290 IVEP routines performed using 38 commercial doses of semen from Senepol bulls. All sperm samples that had undergone the same procedure during sperm selection for in vitro fertilization were evaluated using a computer-assisted sperm analysis (CASA) system to define sperm subpopulations. Sperm morphology was also analyzed in a wet preparation, and the integrity of the plasma and acrosomal membranes, mitochondrial potential, oxidative status, and chromatin resistance were evaluated using flow cytometry. A previous study identified three sperm subpopulations in such samples and the information used in tandem with other sperm quality variables to perform an AI analysis. AI analysis generated models that estimated IVEP based on the season, donor, percentage of viable oocytes, and 18 other sperm predictor variables. The accuracy of the results obtained for the three best AI models for predicting the IVEP was 90.7, 75.3, and 79.6%, respectively. Therefore, applying this AI technique would enable the estimation of high or low embryo production for individual bulls based on the sperm analysis information. |
| first_indexed | 2024-03-11T23:03:20Z |
| format | Article |
| id | doaj.art-23b373d03aaf47bc9606ed8eada66491 |
| institution | Directory Open Access Journal |
| issn | 2297-1769 |
| language | English |
| last_indexed | 2024-03-11T23:03:20Z |
| publishDate | 2023-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Veterinary Science |
| spelling | doaj.art-23b373d03aaf47bc9606ed8eada664912023-09-21T14:02:02ZengFrontiers Media S.A.Frontiers in Veterinary Science2297-17692023-09-011010.3389/fvets.2023.12549401254940Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence?Suzane Peres Campanholi0Sebastião Garcia Neto1Gabriel Martins Pinheiro2Marcelo Fábio Gouveia Nogueira3José Celso Rocha4João Diego de Agostini Losano5Adriano Felipe Perez Siqueira6Marcílio Nichi7Mayra Elena Ortiz D'Avila Assumpção8Andréa Cristina Basso9Fabio Morato Monteiro10Lindsay Unno Gimenes11Departamento de Patologia, Reprodução e Saúde Única, Faculdade de Ciências Agrárias e Veterinárias (FCAV), Universidade Estadual Paulista, Jaboticabal, BrazilSenepol 3G, Barretos, BrazilDepartamento de Ciências Biológicas, Faculdade de Ciências e Letras (FCLA), Universidade Estadual Paulista (UNESP), Assis, BrazilDepartamento de Ciências Biológicas, Faculdade de Ciências e Letras (FCLA), Universidade Estadual Paulista (UNESP), Assis, BrazilDepartamento de Ciências Biológicas, Faculdade de Ciências e Letras (FCLA), Universidade Estadual Paulista (UNESP), Assis, BrazilDepartamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia (FMVZ), Universidade de São Paulo (USP), São Paulo, BrazilDepartamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia (FMVZ), Universidade de São Paulo (USP), São Paulo, BrazilDepartamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia (FMVZ), Universidade de São Paulo (USP), São Paulo, BrazilDepartamento de Reprodução Animal, Faculdade de Medicina Veterinária e Zootecnia (FMVZ), Universidade de São Paulo (USP), São Paulo, BrazilIn Vitro Brasil SA, Mogi Mirim, BrazilCentro Avançado de Pesquisa de Bovinos de Corte, Agência Paulista de Tecnologia dos Agronegócios/Instituto de Zootecnia (APTA/IZ), Sertãozinho, BrazilDepartamento de Patologia, Reprodução e Saúde Única, Faculdade de Ciências Agrárias e Veterinárias (FCAV), Universidade Estadual Paulista, Jaboticabal, BrazilThoroughly analyzing the sperm and exploring the information obtained using artificial intelligence (AI) could be the key to improving fertility estimation. Artificial neural networks have already been applied to calculate zootechnical indices in animals and predict fertility in humans. This method of estimating the results of reproductive biotechnologies, such as in vitro embryo production (IVEP) in cattle, could be valuable for livestock production. This study was developed to model IVEP estimates in Senepol animals based on various sperm attributes, through retrospective data from 290 IVEP routines performed using 38 commercial doses of semen from Senepol bulls. All sperm samples that had undergone the same procedure during sperm selection for in vitro fertilization were evaluated using a computer-assisted sperm analysis (CASA) system to define sperm subpopulations. Sperm morphology was also analyzed in a wet preparation, and the integrity of the plasma and acrosomal membranes, mitochondrial potential, oxidative status, and chromatin resistance were evaluated using flow cytometry. A previous study identified three sperm subpopulations in such samples and the information used in tandem with other sperm quality variables to perform an AI analysis. AI analysis generated models that estimated IVEP based on the season, donor, percentage of viable oocytes, and 18 other sperm predictor variables. The accuracy of the results obtained for the three best AI models for predicting the IVEP was 90.7, 75.3, and 79.6%, respectively. Therefore, applying this AI technique would enable the estimation of high or low embryo production for individual bulls based on the sperm analysis information.https://www.frontiersin.org/articles/10.3389/fvets.2023.1254940/fullbovinesperm kineticsartificial intelligencefertilityIVEP |
| spellingShingle | Suzane Peres Campanholi Sebastião Garcia Neto Gabriel Martins Pinheiro Marcelo Fábio Gouveia Nogueira José Celso Rocha João Diego de Agostini Losano Adriano Felipe Perez Siqueira Marcílio Nichi Mayra Elena Ortiz D'Avila Assumpção Andréa Cristina Basso Fabio Morato Monteiro Lindsay Unno Gimenes Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? Frontiers in Veterinary Science bovine sperm kinetics artificial intelligence fertility IVEP |
| title | Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? |
| title_full | Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? |
| title_fullStr | Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? |
| title_full_unstemmed | Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? |
| title_short | Can in vitro embryo production be estimated from semen variables in Senepol breed by using artificial intelligence? |
| title_sort | can in vitro embryo production be estimated from semen variables in senepol breed by using artificial intelligence |
| topic | bovine sperm kinetics artificial intelligence fertility IVEP |
| url | https://www.frontiersin.org/articles/10.3389/fvets.2023.1254940/full |
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