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Artigo de periodico
Tree-level carbon stock estimations across diverse species using multi-source remote sensing integration (2025)
Li, Qing; Yin, Jia; Zhang, Xiaoxin; Hao, Dalei; Ferreira, Matheus Pinheiro ; Yan, Wenhui; Tian, Ye; Zhang, Da; Tan, Shen; Nie, Sheng; An, Tianyu; Li, Xiaoyao; Huang, Jianxi; Su, Wei; Zeng, Yelu
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: AERONAVES NÃO TRIPULADAS, ÁRVORES FLORESTAIS, CARBONO, DOSSEL (BOTÂNICA), IMAGEAMENTO DE SATÉLITE, SENSORIAMENTO REMOTO
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ABNT
LI, Qing et al. Tree-level carbon stock estimations across diverse species using multi-source remote sensing integration. Computers and Electronics in Agriculture, v. 231, p. 1-16, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2025.109904. Acesso em: 07 out. 2025.
APA
Li, Q., Yin, J., Zhang, X., Hao, D., Ferreira, M. P., Yan, W., et al. (2025). Tree-level carbon stock estimations across diverse species using multi-source remote sensing integration. Computers and Electronics in Agriculture, 231, 1-16. doi:10.1016/j.compag.2025.109904
NLM
Li Q, Yin J, Zhang X, Hao D, Ferreira MP, Yan W, Tian Y, Zhang D, Tan S, Nie S, An T, Li X, Huang J, Su W, Zeng Y. Tree-level carbon stock estimations across diverse species using multi-source remote sensing integration [Internet]. Computers and Electronics in Agriculture. 2025 ; 231 1-16.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2025.109904
Vancouver
Li Q, Yin J, Zhang X, Hao D, Ferreira MP, Yan W, Tian Y, Zhang D, Tan S, Nie S, An T, Li X, Huang J, Su W, Zeng Y. Tree-level carbon stock estimations across diverse species using multi-source remote sensing integration [Internet]. Computers and Electronics in Agriculture. 2025 ; 231 1-16.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2025.109904
Artigo de periodico
Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions (2025)
Curti, Paula de Freitas ; Souza, André Moreira ; Kobayashi, Livia Lissa ; Castanheira, Aline Mello ; Pinto, Diógenes Lodi ; Ruiz, Alexandre Merlos ; Andrietta, Lucas Tassoni ; Balieiro, Júlio Cesar de Carvalho ; Rennó, Francisco Palma ; Sousa, Elaine Parros Machado de ; Ventura, Ricardo Vieira
Fonte: Computers and Electronics in Agriculture. Unidades: FMVZ, ICMC
Assuntos: VISÃO COMPUTACIONAL, APRENDIZAGEM PROFUNDA, PECUÁRIA LEITEIRA, GADO HOLANDÊS, ZOOTECNIA DE PRECISÃO
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CURTI, Paula de Freitas et al. Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions. Computers and Electronics in Agriculture, v. 239, p. 1-9, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2025.110987. Acesso em: 07 out. 2025.
APA
Curti, P. de F., Souza, A. M., Kobayashi, L. L., Castanheira, A. M., Pinto, D. L., Ruiz, A. M., et al. (2025). Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions. Computers and Electronics in Agriculture, 239, 1-9. doi:10.1016/j.compag.2025.110987
NLM
Curti P de F, Souza AM, Kobayashi LL, Castanheira AM, Pinto DL, Ruiz AM, Andrietta LT, Balieiro JC de C, Rennó FP, Sousa EPM de, Ventura RV. Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions [Internet]. Computers and Electronics in Agriculture. 2025 ; 239 1-9.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2025.110987
Vancouver
Curti P de F, Souza AM, Kobayashi LL, Castanheira AM, Pinto DL, Ruiz AM, Andrietta LT, Balieiro JC de C, Rennó FP, Sousa EPM de, Ventura RV. Respiratory rate regression in Holstein dairy cattle with deep neural networks: an evaluation on different body regions [Internet]. Computers and Electronics in Agriculture. 2025 ; 239 1-9.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2025.110987
Artigo de periodico
Performance evaluation of Sentinel-2 imagery, agronomic and climatic data for sugarcane yield estimation (2025)
Amaro, Rafaella Pironato ; Todoroff, Pierre; Christina, Mathias; Duft, Daniel Garbellini; Luciano, Ana Cláudia dos Santos
Fonte: Computers and Electronics in Agriculture. Unidades: FFLCH, ESALQ
Assuntos: AGROCLIMATOLOGIA, ALGORITMOS, APRENDIZADO COMPUTACIONAL, CANA-DE-AÇÚCAR, IMAGEAMENTO DE SATÉLITE
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ABNT
AMARO, Rafaella Pironato et al. Performance evaluation of Sentinel-2 imagery, agronomic and climatic data for sugarcane yield estimation. Computers and Electronics in Agriculture, v. 237, p. 1-14, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2025.110522. Acesso em: 07 out. 2025.
APA
Amaro, R. P., Todoroff, P., Christina, M., Duft, D. G., & Luciano, A. C. dos S. (2025). Performance evaluation of Sentinel-2 imagery, agronomic and climatic data for sugarcane yield estimation. Computers and Electronics in Agriculture, 237, 1-14. doi:10.1016/j.compag.2025.110522
NLM
Amaro RP, Todoroff P, Christina M, Duft DG, Luciano AC dos S. Performance evaluation of Sentinel-2 imagery, agronomic and climatic data for sugarcane yield estimation [Internet]. Computers and Electronics in Agriculture. 2025 ; 237 1-14.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2025.110522
Vancouver
Amaro RP, Todoroff P, Christina M, Duft DG, Luciano AC dos S. Performance evaluation of Sentinel-2 imagery, agronomic and climatic data for sugarcane yield estimation [Internet]. Computers and Electronics in Agriculture. 2025 ; 237 1-14.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2025.110522
Artigo de periodico
Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion (2025)
Zielinski, Kallil Miguel Caparroz ; Scabini, Leonardo Felipe dos Santos ; Ribas, Lucas Correia ; Silva, Núbia Rosa da ; Beeckman, Hans; Verwaeren, Jan; Bruno, Odemir Martinez ; Baets, Bernard De
Fonte: Computers and Electronics in Agriculture. Unidade: IFSC
Assuntos: APRENDIZADO COMPUTACIONAL, FÍSICA COMPUTACIONAL, REDES NEURAIS, PLANTAS, RECONHECIMENTO DE IMAGEM
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ZIELINSKI, Kallil Miguel Caparroz et al. Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion. Computers and Electronics in Agriculture, v. 231, p. 109867-1-109867-12, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.109867. Acesso em: 07 out. 2025.
APA
Zielinski, K. M. C., Scabini, L. F. dos S., Ribas, L. C., Silva, N. R. da, Beeckman, H., Verwaeren, J., et al. (2025). Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion. Computers and Electronics in Agriculture, 231, 109867-1-109867-12. doi:10.1016/j.compag.2024.109867
NLM
Zielinski KMC, Scabini LF dos S, Ribas LC, Silva NR da, Beeckman H, Verwaeren J, Bruno OM, Baets BD. Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion [Internet]. Computers and Electronics in Agriculture. 2025 ; 231 109867-1-109867-12.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109867
Vancouver
Zielinski KMC, Scabini LF dos S, Ribas LC, Silva NR da, Beeckman H, Verwaeren J, Bruno OM, Baets BD. Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion [Internet]. Computers and Electronics in Agriculture. 2025 ; 231 109867-1-109867-12.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109867
Artigo de periodico
New dielectric-based smart sensor with multi-probe arrays for in-vivo monitoring of trunk water content distribution of a tree in a poplar stand (2024)
Cheng, Xianglin; Wu, Xiaotong; Zhu, Yufan; Zhao, Yang; Xi, Benye; Yan, Xiaofei; Oliveira, Ricardo Ferraz de ; Cheng, Qiang
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ÁLAMO, DIELÉTRICOS, DISTRIBUIÇÃO DE ÁGUA, MONITORAMENTO, SENSOR, XILEMA
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CHENG, Xianglin et al. New dielectric-based smart sensor with multi-probe arrays for in-vivo monitoring of trunk water content distribution of a tree in a poplar stand. Computers and Electronics in Agriculture, v. 227, p. 1-11, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.109585. Acesso em: 07 out. 2025.
APA
Cheng, X., Wu, X., Zhu, Y., Zhao, Y., Xi, B., Yan, X., et al. (2024). New dielectric-based smart sensor with multi-probe arrays for in-vivo monitoring of trunk water content distribution of a tree in a poplar stand. Computers and Electronics in Agriculture, 227, 1-11. doi:10.1016/j.compag.2024.109585
NLM
Cheng X, Wu X, Zhu Y, Zhao Y, Xi B, Yan X, Oliveira RF de, Cheng Q. New dielectric-based smart sensor with multi-probe arrays for in-vivo monitoring of trunk water content distribution of a tree in a poplar stand [Internet]. Computers and Electronics in Agriculture. 2024 ; 227 1-11.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109585
Vancouver
Cheng X, Wu X, Zhu Y, Zhao Y, Xi B, Yan X, Oliveira RF de, Cheng Q. New dielectric-based smart sensor with multi-probe arrays for in-vivo monitoring of trunk water content distribution of a tree in a poplar stand [Internet]. Computers and Electronics in Agriculture. 2024 ; 227 1-11.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109585
Artigo de periodico
Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502] (2024)
Silveira, Robson Mateus Freitas ; Façanha, Débora Andréa Evangelista; McManus, Concepta; Bermejo Asensio, Luis Alberto; Silva, Iran José Oliveira da
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ADAPTAÇÃO ANIMAL, ALGORITMOS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, PRODUÇÃO ANIMAL, REGULAÇÃO DA TEMPERATURA CORPORAL ANIMAL, SENSOR
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ABNT
SILVEIRA, Robson Mateus Freitas et al. Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502]. Computers and Electronics in Agriculture, v. 218, p. 1, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.108673. Acesso em: 07 out. 2025.
APA
Silveira, R. M. F., Façanha, D. A. E., McManus, C., Bermejo Asensio, L. A., & Silva, I. J. O. da. (2024). Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502]. Computers and Electronics in Agriculture, 218, 1. doi:10.1016/j.compag.2024.108673
NLM
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502] [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.108673
Vancouver
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Corrigendum to: "Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals" [Comput. Electron. Agric. 216 (2024) 108502] [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.108673
Artigo de periodico
Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning (2024)
Amorim, Magno do Nascimento; Turco, Silvia Helena Nogueira; Costa, Daniel dos Santos; Ferreira, Iara Jeanice Souza; Silva, Wedson Pereira da; Sabino, Antonio Leopoldo Cardoso ; Oliveira da Silva-Miranda, Késia
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ALIMENTAÇÃO ANIMAL, AMOSTRAGEM, APRENDIZADO COMPUTACIONAL, DISPOSITIVOS ELETRÔNICOS, INGESTÃO, INTELIGÊNCIA ARTIFICIAL, OVINOS
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ABNT
AMORIM, Magno do Nascimento et al. Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning. Computers and Electronics in Agriculture, v. 218, p. 1-8, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.108657. Acesso em: 07 out. 2025.
APA
Amorim, M. do N., Turco, S. H. N., Costa, D. dos S., Ferreira, I. J. S., Silva, W. P. da, Sabino, A. L. C., & Oliveira da Silva-Miranda, K. (2024). Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning. Computers and Electronics in Agriculture, 218, 1-8. doi:10.1016/j.compag.2024.108657
NLM
Amorim M do N, Turco SHN, Costa D dos S, Ferreira IJS, Silva WP da, Sabino ALC, Oliveira da Silva-Miranda K. Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1-8.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.108657
Vancouver
Amorim M do N, Turco SHN, Costa D dos S, Ferreira IJS, Silva WP da, Sabino ALC, Oliveira da Silva-Miranda K. Discrimination of ingestive behavior in sheep using an electronic device based on a triaxial accelerometer and machine learning [Internet]. Computers and Electronics in Agriculture. 2024 ; 218 1-8.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.108657
Artigo de periodico
Ultrasound technology supplements zinc in soybean seeds and increases the photosynthetic efficiency of seedlings (2024)
Gomes, Érica Souza; Oliveira, Gustavo Roberto Fonseca de ; Rodrigues, Arthur Almeida ; Corrêa, Camila Graziela; Almeida, Eduardo de ; Carvalho, Hudson Wallace Pereira de ; Arthur, Valter ; Silva, Edvaldo Aparecido Amaral da ; Novikov, Arthur I ; Mastrangelo, Clíssia Barboza
Fonte: Computers and Electronics in Agriculture. Unidades: CENA, ESALQ
Assuntos: SOJA, SEMENTES, MUDAS, ULTRASSOM
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ABNT
GOMES, Érica Souza et al. Ultrasound technology supplements zinc in soybean seeds and increases the photosynthetic efficiency of seedlings. Computers and Electronics in Agriculture, v. 227, p. 1-8, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.109619. Acesso em: 07 out. 2025.
APA
Gomes, É. S., Oliveira, G. R. F. de, Rodrigues, A. A., Corrêa, C. G., Almeida, E. de, Carvalho, H. W. P. de, et al. (2024). Ultrasound technology supplements zinc in soybean seeds and increases the photosynthetic efficiency of seedlings. Computers and Electronics in Agriculture, 227, 1-8. doi:10.1016/j.compag.2024.109619
NLM
Gomes ÉS, Oliveira GRF de, Rodrigues AA, Corrêa CG, Almeida E de, Carvalho HWP de, Arthur V, Silva EAA da, Novikov AI, Mastrangelo CB. Ultrasound technology supplements zinc in soybean seeds and increases the photosynthetic efficiency of seedlings [Internet]. Computers and Electronics in Agriculture. 2024 ; 227 1-8.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109619
Vancouver
Gomes ÉS, Oliveira GRF de, Rodrigues AA, Corrêa CG, Almeida E de, Carvalho HWP de, Arthur V, Silva EAA da, Novikov AI, Mastrangelo CB. Ultrasound technology supplements zinc in soybean seeds and increases the photosynthetic efficiency of seedlings [Internet]. Computers and Electronics in Agriculture. 2024 ; 227 1-8.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109619
Artigo de periodico
Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals (2024)
Silveira, Robson Mateus Freitas ; Façanha, Débora Andréa Evangelista; McManus, Concepta; Bermejo Asensio, Luis Alberto; Silva, Iran José Oliveira da
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ADAPTAÇÃO ANIMAL, ALGORITMOS, APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, PRODUÇÃO ANIMAL, REGULAÇÃO DA TEMPERATURA CORPORAL ANIMAL, SENSOR
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVEIRA, Robson Mateus Freitas et al. Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals. Computers and Electronics in Agriculture, v. 216, p. 1-11, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2023.108502. Acesso em: 07 out. 2025.
APA
Silveira, R. M. F., Façanha, D. A. E., McManus, C., Bermejo Asensio, L. A., & Silva, I. J. O. da. (2024). Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals. Computers and Electronics in Agriculture, 216, 1-11. doi:10.1016/j.compag.2023.108502
NLM
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals [Internet]. Computers and Electronics in Agriculture. 2024 ; 216 1-11.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.108502
Vancouver
Silveira RMF, Façanha DAE, McManus C, Bermejo Asensio LA, Silva IJO da. Intelligent methodologies: An integrated multi-modeling approach to predict adaptive mechanisms in farm animals [Internet]. Computers and Electronics in Agriculture. 2024 ; 216 1-11.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.108502
Artigo de periodico
Multi-attribute, graph-based approach for duplicate cattle removal and counting in large pasture areas from multiple aerial images (2024)
Soares, Victor Hugo Andrade ; Ponti, Moacir Antonelli ; Campello, Ricardo José Gabrielli Barreto
Fonte: Computers and Electronics in Agriculture. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, AERONAVES NÃO TRIPULADAS, PECUÁRIA, AGRICULTURA DE PRECISÃO
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ABNT
SOARES, Victor Hugo Andrade e PONTI, Moacir Antonelli e CAMPELLO, Ricardo José Gabrielli Barreto. Multi-attribute, graph-based approach for duplicate cattle removal and counting in large pasture areas from multiple aerial images. Computers and Electronics in Agriculture, v. 220, p. 1-18, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.108828. Acesso em: 07 out. 2025.
APA
Soares, V. H. A., Ponti, M. A., & Campello, R. J. G. B. (2024). Multi-attribute, graph-based approach for duplicate cattle removal and counting in large pasture areas from multiple aerial images. Computers and Electronics in Agriculture, 220, 1-18. doi:10.1016/j.compag.2024.108828
NLM
Soares VHA, Ponti MA, Campello RJGB. Multi-attribute, graph-based approach for duplicate cattle removal and counting in large pasture areas from multiple aerial images [Internet]. Computers and Electronics in Agriculture. 2024 ; 220 1-18.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.108828
Vancouver
Soares VHA, Ponti MA, Campello RJGB. Multi-attribute, graph-based approach for duplicate cattle removal and counting in large pasture areas from multiple aerial images [Internet]. Computers and Electronics in Agriculture. 2024 ; 220 1-18.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.108828
Artigo de periodico
Development and validation of a mobile application for thermal risk management in pigs – GRT Suínos (2024)
Gregolin, Fabiano ; Miranda, Késia Oliveira da Silva
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ADMINISTRAÇÃO DE RISCO, APLICATIVOS MÓVEIS, CONFORTO TÉRMICO, SUÍNOS
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ABNT
GREGOLIN, Fabiano e MIRANDA, Késia Oliveira da Silva. Development and validation of a mobile application for thermal risk management in pigs – GRT Suínos. Computers and Electronics in Agriculture, v. 222, p. 1-10, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2024.109054. Acesso em: 07 out. 2025.
APA
Gregolin, F., & Miranda, K. O. da S. (2024). Development and validation of a mobile application for thermal risk management in pigs – GRT Suínos. Computers and Electronics in Agriculture, 222, 1-10. doi:10.1016/j.compag.2024.109054
NLM
Gregolin F, Miranda KO da S. Development and validation of a mobile application for thermal risk management in pigs – GRT Suínos [Internet]. Computers and Electronics in Agriculture. 2024 ; 222 1-10.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109054
Vancouver
Gregolin F, Miranda KO da S. Development and validation of a mobile application for thermal risk management in pigs – GRT Suínos [Internet]. Computers and Electronics in Agriculture. 2024 ; 222 1-10.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2024.109054
Artigo de periodico
Assessing the influence of crop model structure on the performance of data assimilation for sugarcane (2023)
Fattori Junior, Izael Martins ; Marin, Fábio Ricardo
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: ALGORITMOS, CANA-DE-AÇÚCAR, IMAGEAMENTO DE SATÉLITE, ÍNDICE DE ÁREA FOLIAR, SENSORIAMENTO REMOTO, SIMULAÇÃO
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ABNT
FATTORI JUNIOR, Izael Martins e MARIN, Fábio Ricardo. Assessing the influence of crop model structure on the performance of data assimilation for sugarcane. Computers and Electronics in Agriculture, v. 209, p. 1-11, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2023.107848. Acesso em: 07 out. 2025.
APA
Fattori Junior, I. M., & Marin, F. R. (2023). Assessing the influence of crop model structure on the performance of data assimilation for sugarcane. Computers and Electronics in Agriculture, 209, 1-11. doi:10.1016/j.compag.2023.107848
NLM
Fattori Junior IM, Marin FR. Assessing the influence of crop model structure on the performance of data assimilation for sugarcane [Internet]. Computers and Electronics in Agriculture. 2023 ; 209 1-11.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.107848
Vancouver
Fattori Junior IM, Marin FR. Assessing the influence of crop model structure on the performance of data assimilation for sugarcane [Internet]. Computers and Electronics in Agriculture. 2023 ; 209 1-11.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.107848
Artigo de periodico
A Rolling Horizon scheme for rescheduling in agricultural harvest (2023)
Santos, Fernando Montenegro dos; Pérez Galarce, Francisco; Monardes Concha, Carlos; Candia Vejar, Alfredo; Nagano, Marcelo Seido ; Gómez Lagos, Javier
Fonte: Computers and Electronics in Agriculture. Unidade: EESC
Assuntos: COLHEITA, COLHEDORAS, ENGENHARIA DE PRODUÇÃO
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ABNT
SANTOS, Fernando Montenegro dos et al. A Rolling Horizon scheme for rescheduling in agricultural harvest. Computers and Electronics in Agriculture, v. 215, p. 1-15, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2023.108392. Acesso em: 07 out. 2025.
APA
Santos, F. M. dos, Pérez Galarce, F., Monardes Concha, C., Candia Vejar, A., Nagano, M. S., & Gómez Lagos, J. (2023). A Rolling Horizon scheme for rescheduling in agricultural harvest. Computers and Electronics in Agriculture, 215, 1-15. doi:10.1016/j.compag.2023.108392
NLM
Santos FM dos, Pérez Galarce F, Monardes Concha C, Candia Vejar A, Nagano MS, Gómez Lagos J. A Rolling Horizon scheme for rescheduling in agricultural harvest [Internet]. Computers and Electronics in Agriculture. 2023 ; 215 1-15.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.108392
Vancouver
Santos FM dos, Pérez Galarce F, Monardes Concha C, Candia Vejar A, Nagano MS, Gómez Lagos J. A Rolling Horizon scheme for rescheduling in agricultural harvest [Internet]. Computers and Electronics in Agriculture. 2023 ; 215 1-15.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.108392
Artigo de periodico
Deep4Fusion: a Deep FORage Fusion framework for high-throughput phenotyping for green and dry matter yield traits (2023)
Rodrigues, Lucas de Souza; Caixeta Filho, Edmar; Sakiyama, Kenzo ; Santos, Mateus Figueiredo; Jank, Liana ; Carromeu, Camilo ; Silveira, Eloise; Matsubara, Edson Takashi ; Marcato Júnior, José ; Gonçalves, Wesley Nunes
Fonte: Computers and Electronics in Agriculture. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, VISÃO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
RODRIGUES, Lucas de Souza et al. Deep4Fusion: a Deep FORage Fusion framework for high-throughput phenotyping for green and dry matter yield traits. Computers and Electronics in Agriculture, v. 211, p. 1-14, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2023.107957. Acesso em: 07 out. 2025.
APA
Rodrigues, L. de S., Caixeta Filho, E., Sakiyama, K., Santos, M. F., Jank, L., Carromeu, C., et al. (2023). Deep4Fusion: a Deep FORage Fusion framework for high-throughput phenotyping for green and dry matter yield traits. Computers and Electronics in Agriculture, 211, 1-14. doi:10.1016/j.compag.2023.107957
NLM
Rodrigues L de S, Caixeta Filho E, Sakiyama K, Santos MF, Jank L, Carromeu C, Silveira E, Matsubara ET, Marcato Júnior J, Gonçalves WN. Deep4Fusion: a Deep FORage Fusion framework for high-throughput phenotyping for green and dry matter yield traits [Internet]. Computers and Electronics in Agriculture. 2023 ; 211 1-14.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.107957
Vancouver
Rodrigues L de S, Caixeta Filho E, Sakiyama K, Santos MF, Jank L, Carromeu C, Silveira E, Matsubara ET, Marcato Júnior J, Gonçalves WN. Deep4Fusion: a Deep FORage Fusion framework for high-throughput phenotyping for green and dry matter yield traits [Internet]. Computers and Electronics in Agriculture. 2023 ; 211 1-14.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2023.107957
Artigo de periodico
Digital mapping of coffee ripeness using UAV-based multispectral imagery (2023)
Nogueira Martins, Rodrigo; Pinto, Francisco de Assis de Carvalho; Queiroz, Daniel Marçal de; Valente, Domingos Sárvio Magalhães; Rosas, Jorge Tadeu Fim ; Portes, Marcelo Fagundes; Cerqueira, Elder Sânzio Aguiar
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: AERONAVES NÃO TRIPULADAS, ANÁLISE ESPECTRAL, CAFÉ, MATURAÇÃO VEGETAL, SENSORIAMENTO REMOTO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NOGUEIRA MARTINS, Rodrigo et al. Digital mapping of coffee ripeness using UAV-based multispectral imagery. Computers and Electronics in Agriculture, v. 204, p. 1-13, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2022.107499. Acesso em: 07 out. 2025.
APA
Nogueira Martins, R., Pinto, F. de A. de C., Queiroz, D. M. de, Valente, D. S. M., Rosas, J. T. F., Portes, M. F., & Cerqueira, E. S. A. (2023). Digital mapping of coffee ripeness using UAV-based multispectral imagery. Computers and Electronics in Agriculture, 204, 1-13. doi:10.1016/j.compag.2022.107499
NLM
Nogueira Martins R, Pinto F de A de C, Queiroz DM de, Valente DSM, Rosas JTF, Portes MF, Cerqueira ESA. Digital mapping of coffee ripeness using UAV-based multispectral imagery [Internet]. Computers and Electronics in Agriculture. 2023 ; 204 1-13.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.107499
Vancouver
Nogueira Martins R, Pinto F de A de C, Queiroz DM de, Valente DSM, Rosas JTF, Portes MF, Cerqueira ESA. Digital mapping of coffee ripeness using UAV-based multispectral imagery [Internet]. Computers and Electronics in Agriculture. 2023 ; 204 1-13.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.107499
Artigo de periodico
Parameterizing field capacity as the upper limit of available water in bucket-type hydrological models (2022)
Turek, Maria Eliza ; De Jong Van Lier, Quirijn ; Armindo, Robson André
Fonte: Computers and Electronics in Agriculture. Unidade: CENA
Assuntos: ANÁLISE EM FLUXO CONTÍNUO, ÁGUA DO SOLO, CRESCIMENTO VEGETAL, PRODUÇÃO AGRÍCOLA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
TUREK, Maria Eliza e DE JONG VAN LIER, Quirijn e ARMINDO, Robson André. Parameterizing field capacity as the upper limit of available water in bucket-type hydrological models. Computers and Electronics in Agriculture, v. 194, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2022.106801. Acesso em: 07 out. 2025.
APA
Turek, M. E., De Jong Van Lier, Q., & Armindo, R. A. (2022). Parameterizing field capacity as the upper limit of available water in bucket-type hydrological models. Computers and Electronics in Agriculture, 194. doi:10.1016/j.compag.2022.106801
NLM
Turek ME, De Jong Van Lier Q, Armindo RA. Parameterizing field capacity as the upper limit of available water in bucket-type hydrological models [Internet]. Computers and Electronics in Agriculture. 2022 ; 194[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.106801
Vancouver
Turek ME, De Jong Van Lier Q, Armindo RA. Parameterizing field capacity as the upper limit of available water in bucket-type hydrological models [Internet]. Computers and Electronics in Agriculture. 2022 ; 194[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.106801
Artigo de periodico
Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee (2022)
Gomes, Winston Pinheiro Claro ; Gonçalves, Luís; Silva, Clíssia Barboza da ; Melchert, Wanessa Roberta
Fonte: Computers and Electronics in Agriculture. Unidades: ESALQ, CENA
Assuntos: ANÁLISE DE ALIMENTOS, APRENDIZADO COMPUTACIONAL, CAFÉ, ESPECTROSCOPIA, QUÍMICA DE ALIMENTOS, QUIMIOMETRIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GOMES, Winston Pinheiro Claro et al. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee. Computers and Electronics in Agriculture, v. 198, p. 1-9, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2022.107097. Acesso em: 07 out. 2025.
APA
Gomes, W. P. C., Gonçalves, L., Silva, C. B. da, & Melchert, W. R. (2022). Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee. Computers and Electronics in Agriculture, 198, 1-9. doi:10.1016/j.compag.2022.107097
NLM
Gomes WPC, Gonçalves L, Silva CB da, Melchert WR. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee [Internet]. Computers and Electronics in Agriculture. 2022 ; 198 1-9.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.107097
Vancouver
Gomes WPC, Gonçalves L, Silva CB da, Melchert WR. Application of multispectral imaging combined with machine learning models to discriminate special and traditional green coffee [Internet]. Computers and Electronics in Agriculture. 2022 ; 198 1-9.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.107097
Artigo de periodico
On supervised learning to model and predict cattle weight in precision livestock breeding (2022)
Biase, Adriele Giaretta ; Albertini, Tiago Zanett ; Mello, Rodrigo Fernandes de
Fonte: Computers and Electronics in Agriculture. Unidade: ICMC
Assuntos: REDES NEURAIS, PROCESSOS ESTOCÁSTICOS, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), SISTEMAS DINÂMICOS, PECUÁRIA DE CORTE
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIASE, Adriele Giaretta e ALBERTINI, Tiago Zanett e MELLO, Rodrigo Fernandes de. On supervised learning to model and predict cattle weight in precision livestock breeding. Computers and Electronics in Agriculture, v. 195, p. 1-19, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2022.106706. Acesso em: 07 out. 2025.
APA
Biase, A. G., Albertini, T. Z., & Mello, R. F. de. (2022). On supervised learning to model and predict cattle weight in precision livestock breeding. Computers and Electronics in Agriculture, 195, 1-19. doi:10.1016/j.compag.2022.106706
NLM
Biase AG, Albertini TZ, Mello RF de. On supervised learning to model and predict cattle weight in precision livestock breeding [Internet]. Computers and Electronics in Agriculture. 2022 ; 195 1-19.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.106706
Vancouver
Biase AG, Albertini TZ, Mello RF de. On supervised learning to model and predict cattle weight in precision livestock breeding [Internet]. Computers and Electronics in Agriculture. 2022 ; 195 1-19.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2022.106706
Artigo de periodico
Cattle reference growth curves based on centile estimation: a GAMLSS approach (2022)
Nakamura, Luiz R; Ramires, Thiago G; Righetto, Ana J; Pescim, Rodrigo R; Roquim, Fernanda V; Savian, Taciana Villela ; Stasinopoulos, Dimitrios M
Fonte: Computers and Electronics in Agriculture. Unidade: ESALQ
Assuntos: BOVINOCULTURA DE CORTE, CURVAS DE CRESCIMENTO, GADO HEREFORD, MODELOS MATEMÁTICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NAKAMURA, Luiz R et al. Cattle reference growth curves based on centile estimation: a GAMLSS approach. Computers and Electronics in Agriculture, v. 192, p. 1-6, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2021.106572. Acesso em: 07 out. 2025.
APA
Nakamura, L. R., Ramires, T. G., Righetto, A. J., Pescim, R. R., Roquim, F. V., Savian, T. V., & Stasinopoulos, D. M. (2022). Cattle reference growth curves based on centile estimation: a GAMLSS approach. Computers and Electronics in Agriculture, 192, 1-6. doi:10.1016/j.compag.2021.106572
NLM
Nakamura LR, Ramires TG, Righetto AJ, Pescim RR, Roquim FV, Savian TV, Stasinopoulos DM. Cattle reference growth curves based on centile estimation: a GAMLSS approach [Internet]. Computers and Electronics in Agriculture. 2022 ; 192 1-6.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2021.106572
Vancouver
Nakamura LR, Ramires TG, Righetto AJ, Pescim RR, Roquim FV, Savian TV, Stasinopoulos DM. Cattle reference growth curves based on centile estimation: a GAMLSS approach [Internet]. Computers and Electronics in Agriculture. 2022 ; 192 1-6.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2021.106572
Artigo de periodico
DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage (2021)
Machado, Bruno Brandoli ; Spadon, Gabriel ; Esau, Travis ; Hennessy, Patrick ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Amer-Yahia, Sihem ; Rodrigues Junior, José Fernando
Fonte: Computers and Electronics in Agriculture. Unidade: ICMC
Assuntos: COMPUTAÇÃO MÓVEL, PROCESSAMENTO DE IMAGENS, AGRICULTURA DE PRECISÃO, PESTICIDAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MACHADO, Bruno Brandoli et al. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage. Computers and Electronics in Agriculture, v. 180, n. Ja 2021, p. 1-9, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2020.105906. Acesso em: 07 out. 2025.
APA
Machado, B. B., Spadon, G., Esau, T., Hennessy, P., Carvalho, A. C. P. de L. F. de, Amer-Yahia, S., & Rodrigues Junior, J. F. (2021). DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage. Computers and Electronics in Agriculture, 180( Ja 2021), 1-9. doi:10.1016/j.compag.2020.105906
NLM
Machado BB, Spadon G, Esau T, Hennessy P, Carvalho ACP de LF de, Amer-Yahia S, Rodrigues Junior JF. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage [Internet]. Computers and Electronics in Agriculture. 2021 ; 180( Ja 2021): 1-9.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2020.105906
Vancouver
Machado BB, Spadon G, Esau T, Hennessy P, Carvalho ACP de LF de, Amer-Yahia S, Rodrigues Junior JF. DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage [Internet]. Computers and Electronics in Agriculture. 2021 ; 180( Ja 2021): 1-9.[citado 2025 out. 07 ] Available from: https://doi.org/10.1016/j.compag.2020.105906

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