From seed to canopy: high-throughput phenotyping and machine learning in soybean breeding (2024)
Unidade: ESALQSubjects: APRENDIZADO COMPUTACIONAL, MELHORAMENTO GENÉTICO VEGETAL, REDES NEURAIS, SEMENTES, SOJA
ABNT
MIRANDA, Melissa Cristina de Carvalho. From seed to canopy: high-throughput phenotyping and machine learning in soybean breeding. 2024. Tese (Doutorado) – Universidade de São Paulo, Piracicaba, 2024. Disponível em: https://www.teses.usp.br/teses/disponiveis/11/11137/tde-02072024-112314/. Acesso em: 03 set. 2024.APA
Miranda, M. C. de C. (2024). From seed to canopy: high-throughput phenotyping and machine learning in soybean breeding (Tese (Doutorado). Universidade de São Paulo, Piracicaba. Recuperado de https://www.teses.usp.br/teses/disponiveis/11/11137/tde-02072024-112314/NLM
Miranda MC de C. From seed to canopy: high-throughput phenotyping and machine learning in soybean breeding [Internet]. 2024 ;[citado 2024 set. 03 ] Available from: https://www.teses.usp.br/teses/disponiveis/11/11137/tde-02072024-112314/Vancouver
Miranda MC de C. From seed to canopy: high-throughput phenotyping and machine learning in soybean breeding [Internet]. 2024 ;[citado 2024 set. 03 ] Available from: https://www.teses.usp.br/teses/disponiveis/11/11137/tde-02072024-112314/