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Soil morphostructural characterization and coffee root distribution under agroforestry system with Hevea Brasiliensis

Nunes, Amanda Letícia Pit; Cortez, Glassys Louise de Souza; Zaro, Geovanna Cristina; Zorzenoni, Thiago Ometto; Melo, Thadeu Rodrigues de; Figueiredo, Alex; Aquino, Gisele Silva de; Medina, Cristiane de Conti; Ralisch, Ricardo; Caramori, Paulo Henrique; Guimarães, Maria de Fátima (Escola Superior de Agricultura "Luiz de Queiroz", 2021)

Land use and tillage practices may change soil structure and undermine sustainable agriculture; however, such changes are hardly identified in the short term. In this sense, agroforestry systems have been used to reduce ...
Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms

Sousa, Ithalo Coelho de; Nascimento, Moysés; Silva, Gabi Nunes; Nascimento, Ana Carolina Campana; Cruz, Cosme Damião; Silva, Fabyano Fonseca e; Almeida, Dênia Pires de; Pestana, Kátia Nogueira; Azevedo, Camila Ferreira; Zambolim, Laércio; Caixeta, Eveline Teixeira (Escola Superior de Agricultura "Luiz de Queiroz", 2021)

Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic ...
Coffee crops adaptation to climate change in agroforestry systems with rubber trees in southern Brazil

Zaro, Geovanna Cristina; Caramori, Paulo Henrique; Wrege, Marcos Silveira; Caldana, Nathan Felipe da Silva; Virgens Filho, Jorim Sousa das; Morais, Heverly; Yada Junior, George Mitsuo; Caramori, Daniel Campos (Escola Superior de Agricultura "Luiz de Queiroz", 2022-04-13)

Adaptation to climate change is a strategy for crops to cope with the scenario of rising temperatures worldwide. In the case of Coffea arabica L., the use of agroforestry systems (AFS) with woody species is a promising ...
Detection of coffee fruits on tree branches using computer vision

Bazame, Helizani Couto; Molin, José Paulo; Althoff, Daniel; Martello, Maurício (Escola Superior de Agricultura "Luiz de Queiroz", 2022-09-12)

Coffee farmers do not have efficient tools to have sufficient and reliable information on the maturation stage of coffee fruits before harvest. In this study, we propose a computer vision system to detect and classify the ...