Ultrasound technology supplements zinc in soybean seeds and increases the photosynthetic efficiency of seedlings von Gomes, Érica Souza, Fonseca de Oliveira, Gustavo Roberto, Rodrigues, Arthur Almeida, Corrêa, Camila Graziela, de Almeida, Eduardo, de Carvalho, Hudson Wallace Pereira, Arthur, Valter, Amaral da Silva, Edvaldo Aparecido, Novikov, Arthur I., Mastrangelo, Clíssia Barboza

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Fungal identification in peanuts seeds through multispectral images: Technological advances to enhance sanitary quality von Sudki, Julia Marconato, Fonseca de Oliveira, Gustavo Roberto, de Medeiros, André Dantas, Mastrangelo, Thiago, Arthur, Valter, Amaral da Silva, Edvaldo Aparecido, Mastrangelo, Clíssia Barboza

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An Approach Using Emerging Optical Technologies and Artificial Intelligence Brings New Markers to Evaluate Peanut Seed Quality von Fonseca de Oliveira, Gustavo Roberto, Mastrangelo, Clíssia Barboza, Hirai, Welinton Yoshio, Batista, Thiago Barbosa, Sudki, Julia Marconato, Petronilio, Ana Carolina Picinini, Crusciol, Carlos Alexandre Costa, Amaral da Silva, Edvaldo Aparecido

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A Reliable Method to Recognize Soybean Seed Maturation Stages Based on Autofluorescence-Spectral Imaging Combined With Machine Learning Algorithms von Batista, Thiago Barbosa, Mastrangelo, Clíssia Barboza, de Medeiros, André Dantas, Petronilio, Ana Carolina Picinini, Fonseca de Oliveira, Gustavo Roberto, dos Santos, Isabela Lopes, Crusciol, Carlos Alexandre Costa, Amaral da Silva, Edvaldo Aparecido

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The Root Collar Diameter Growth Reveals a Strong Relationship with the Height Growth of Juvenile Scots Pine Trees from Seeds Differentiated by Spectrometric Feature von Novikova, Tatyana P., Tylek, Paweł, Mastrangelo, Clíssia Barboza, Drapalyuk, Michael V., Kharin, Sergei V., Novikov, Arthur I.

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Deep-Learning Approach for Fusarium Head Blight Detection in Wheat Seeds Using Low-Cost Imaging Technology von Bernardes, Rodrigo Cupertino, De Medeiros, André, da Silva, Laercio, Cantoni, Leo, Martins, Gustavo Ferreira, Mastrangelo, Thiago, Novikov, Arthur, Mastrangelo, Clíssia Barboza

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Spectroscopy Technologies to Screen Peanut Seeds with Superior Vigor Through “Chemical Fingerprinting” von Fonseca de Oliveira, Gustavo Roberto, Hirai, Welinton Yoshio, Ferreira, Dennis Silva, Silva, Karolyne Priscila Oliveira Mota da, Silva, Giovani Chaves, Moraes, Tiago Bueno, Mastrangelo, Clissia Barboza, Pereira, Fabiola Manhas Verbi, Pereira-Filho, Edenir Rodrigues, Amaral da Silva, Edvaldo Aparecido

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How Can the Engineering Parameters of the NIR Grader Affect the Efficiency of Seed Grading? von Novikova, Tatyana P., Mastrangelo, Clíssia Barboza, Tylek, Paweł, Evdokimova, Svetlana A., Novikov, Arthur I.

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Deep-Learning Approach for IFusarium/I Head Blight Detection in Wheat Seeds Using Low-Cost Imaging Technology von Bernardes, Rodrigo Cupe, De Medeiros, André, da Silva, Laercio, Cantoni, Leo, Ma, Mastrangelo, Thiago, Novikov, Arthur, Mastrangelo, Clíssia Barboza

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Hormetic effects of low-dose gamma rays in soybean seeds and seedlings: A detection technique using optical sensors von Oliveira, Nielsen Moreira, Medeiros, André Dantas de, Nogueira, Marina de Lima, Arthur, Valter, Mastrangelo, Thiago de Araújo, Barboza da Silva, Clíssia

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Convolutional Neural Networks Using Enhanced Radiographs for Real-Time Detection of Sitophilus zeamais in Maize Grain von Barboza da Silva, Clíssia, Silva, Alysson Alexander Naves, Barroso, Geovanny, Yamamoto, Pedro Takao, Arthur, Valter, Toledo, Claudio Fabiano Motta, Mastrangelo, Thiago de Araújo

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Multispectral imaging for quality control of laboratory‐reared Anastrepha fraterculus (Diptera: Tephritidae) pupae von Mastrangelo, Thiago, Silva, Fabiano França, Mascarin, Gabriel Moura, Silva, Clíssia Barboza

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