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Artigo de periodico
The combined effect of supercritical carbon dioxide and mild temperatures on pectin methylesterase inactivation in orange juice (2023)
Sultani, Thais Madoglio; Francisco, Ana Carolina Pereira; Dacanal, Gustavo César ; Oliveira, Alessandra Lopes de ; Petrus, Rodrigo Rodrigues
Source: Food Science and Technology International. Unidade: FZEA
Subjects: PECTINA, DIÓXIDO DE CARBONO, TECNOLOGIA DE ALIMENTOS, SUCOS DE FRUTAS, LARANJA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SULTANI, Thais Madoglio et al. The combined effect of supercritical carbon dioxide and mild temperatures on pectin methylesterase inactivation in orange juice. Food Science and Technology International, p. 1-12, 2023Tradução . . Disponível em: https://doi.org/10.1177/10820132231172363. Acesso em: 02 nov. 2024.
APA
Sultani, T. M., Francisco, A. C. P., Dacanal, G. C., Oliveira, A. L. de, & Petrus, R. R. (2023). The combined effect of supercritical carbon dioxide and mild temperatures on pectin methylesterase inactivation in orange juice. Food Science and Technology International, 1-12. doi:10.1177/10820132231172363
NLM
Sultani TM, Francisco ACP, Dacanal GC, Oliveira AL de, Petrus RR. The combined effect of supercritical carbon dioxide and mild temperatures on pectin methylesterase inactivation in orange juice [Internet]. Food Science and Technology International. 2023 ; 1-12.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1177/10820132231172363
Vancouver
Sultani TM, Francisco ACP, Dacanal GC, Oliveira AL de, Petrus RR. The combined effect of supercritical carbon dioxide and mild temperatures on pectin methylesterase inactivation in orange juice [Internet]. Food Science and Technology International. 2023 ; 1-12.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1177/10820132231172363
Dissertação (Mestrado)
Evaluation of sensory crispness of dry crispy foods by convolutional neural networks (2023)
Lopes, Rafael Zinni; Dacanal, Gustavo César (Orientador)
Unidade: FZEA
Subjects: ANÁLISE SENSORIAL DE ALIMENTOS, SECAGEM DE ALIMENTOS, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LOPES, Rafael Zinni. Evaluation of sensory crispness of dry crispy foods by convolutional neural networks. 2023. Dissertação (Mestrado) – Universidade de São Paulo, Pirassununga, 2023. Disponível em: https://www.teses.usp.br/teses/disponiveis/74/74133/tde-09022024-105654/. Acesso em: 02 nov. 2024.
APA
Lopes, R. Z. (2023). Evaluation of sensory crispness of dry crispy foods by convolutional neural networks (Dissertação (Mestrado). Universidade de São Paulo, Pirassununga. Recuperado de https://www.teses.usp.br/teses/disponiveis/74/74133/tde-09022024-105654/
NLM
Lopes RZ. Evaluation of sensory crispness of dry crispy foods by convolutional neural networks [Internet]. 2023 ;[citado 2024 nov. 02 ] Available from: https://www.teses.usp.br/teses/disponiveis/74/74133/tde-09022024-105654/
Vancouver
Lopes RZ. Evaluation of sensory crispness of dry crispy foods by convolutional neural networks [Internet]. 2023 ;[citado 2024 nov. 02 ] Available from: https://www.teses.usp.br/teses/disponiveis/74/74133/tde-09022024-105654/
Artigo de periodico
Classification of crispness of food materials by deep neural networks (2023)
Lopes, Rafael Zinni; Dacanal, Gustavo César
Source: Journal of Texture Studies. Unidade: FZEA
Subjects: REDES NEURAIS, INDÚSTRIA DE ALIMENTOS, COMPORTAMENTO DO CONSUMIDOR, CARNES E DERIVADOS, BATATA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
LOPES, Rafael Zinni e DACANAL, Gustavo César. Classification of crispness of food materials by deep neural networks. Journal of Texture Studies, v. 54, n. 6, p. 845-859, 2023Tradução . . Disponível em: https://doi.org/10.1111/jtxs.12792. Acesso em: 02 nov. 2024.
APA
Lopes, R. Z., & Dacanal, G. C. (2023). Classification of crispness of food materials by deep neural networks. Journal of Texture Studies, 54( 6), 845-859. doi:10.1111/jtxs.12792
NLM
Lopes RZ, Dacanal GC. Classification of crispness of food materials by deep neural networks [Internet]. Journal of Texture Studies. 2023 ; 54( 6): 845-859.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1111/jtxs.12792
Vancouver
Lopes RZ, Dacanal GC. Classification of crispness of food materials by deep neural networks [Internet]. Journal of Texture Studies. 2023 ; 54( 6): 845-859.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1111/jtxs.12792

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