Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Karym Mayara de Oliveira"'
Autor:
Karym Mayara de Oliveira, João Vitor Ferreira Gonçalves, Renato Herrig Furlanetto, Caio Almeida de Oliveira, Weslei Augusto Mendonça, Daiane de Fatima da Silva Haubert, Luís Guilherme Teixeira Crusiol, Renan Falcioni, Roney Berti de Oliveira, Amanda Silveira Reis, Arney Eduardo do Amaral Ecker, Marcos Rafael Nanni
Publikováno v:
Remote Sensing, Vol 16, Iss 16, p 2869 (2024)
Modeling spectral reflectance data using machine learning algorithms presents a promising approach for estimating soil attributes. Nevertheless, a comprehensive investigation of the most effective models, parameters, wavelengths, and data acquisition
Externí odkaz:
https://doaj.org/article/1064bf2f0a0c4cc5a6ee8d1d76c8b7e9
Autor:
Gustavo Soares Wenneck, Reni Saath, Roberto Rezende, Daniele de Souza Terassi, Vinicius Villa e Vila, Karym Mayara de Oliveira, Adriana Lima Moro, Paulo Sérgio Lourenço de Freitas
Publikováno v:
Semina: Ciências Agrárias, Vol 44, Iss 6 (2024)
Water management has a direct impact on plant development, and under deficit conditions, it often results in reduced yields. Silicon (Si), however, has the potential to alleviate stress and enhance plant performance under unfavorable conditions. This
Externí odkaz:
https://doaj.org/article/730f1c5c13ad4e428e915a80e76abb87
Autor:
Karym Mayara de Oliveira, Renan Falcioni, João Vitor Ferreira Gonçalves, Caio Almeida de Oliveira, Weslei Augusto Mendonça, Luís Guilherme Teixeira Crusiol, Roney Berti de Oliveira, Renato Herrig Furlanetto, Amanda Silveira Reis, Marcos Rafael Nanni
Publikováno v:
Remote Sensing, Vol 15, Iss 19, p 4859 (2023)
In an effort to improve the efficiency of soil classification, traditional methods are being combined with analytical and computational techniques. This integration has strengthened the connection between conventional classification and the applicati
Externí odkaz:
https://doaj.org/article/bf3b2d86b0de4379a769f26dd1e50cec
Autor:
Renan Falcioni, João Vitor Ferreira Gonçalves, Karym Mayara de Oliveira, Caio Almeida de Oliveira, Amanda Silveira Reis, Luis Guilherme Teixeira Crusiol, Renato Herrig Furlanetto, Werner Camargos Antunes, Everson Cezar, Roney Berti de Oliveira, Marcelo Luiz Chicati, José Alexandre M. Demattê, Marcos Rafael Nanni
Publikováno v:
Plants, Vol 12, Iss 19, p 3424 (2023)
Reflectance hyperspectroscopy is recognised for its potential to elucidate biochemical changes, thereby enhancing the understanding of plant biochemistry. This study used the UV-VIS-NIR-SWIR spectral range to identify the different biochemical consti
Externí odkaz:
https://doaj.org/article/2932862c741d45af9050f310c3b74191
Autor:
Everson Cezar, Tatiane Amancio Alberton, Evandro Freire Lemos, Karym Mayara de Oliveira, Liang Sun, Luís Guilherme Teixeira Crusiol, Marlon Rodrigues, Amanda Silveira Reis, Marcos Rafael Nanni
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4397 (2023)
The quantification of soil organic matter (SOM) has increased over the years, especially in the Brazilian Cerrado region, one of the most important areas for grain production in the country. In this area, SOM content tends to be low, which directly i
Externí odkaz:
https://doaj.org/article/1f464eaf9da64de4ad1c76276c5a8781
Autor:
Renan Falcioni, João Vitor Ferreira Gonçalves, Karym Mayara de Oliveira, Caio Almeida de Oliveira, José A. M. Demattê, Werner Camargos Antunes, Marcos Rafael Nanni
Publikováno v:
Plants, Vol 12, Iss 6, p 1333 (2023)
In this study, we investigated the use of artificial intelligence algorithms (AIAs) in combination with VIS-NIR-SWIR hyperspectroscopy for the classification of eleven lettuce plant varieties. For this purpose, a spectroradiometer was utilized to col
Externí odkaz:
https://doaj.org/article/d0944e02c654483ab3bb3c9bebde1628
Autor:
Renan Falcioni, João Vitor Ferreira Gonçalves, Karym Mayara de Oliveira, Werner Camargos Antunes, Marcos Rafael Nanni
Publikováno v:
Remote Sensing, Vol 14, Iss 24, p 6330 (2022)
VIS-NIR-SWIR hyperspectroscopy is a significant technique used in remote sensing for classification of prediction-based chemometrics and machine learning. Chemometrics, together with biophysical and biochemical parameters, is a laborious technique; h
Externí odkaz:
https://doaj.org/article/9be7bb0f9e384c679c8aacaf77608911
Autor:
Lucimar Pereira Bonett, Karym Mayara de Oliveira, Gabriel Hitoshi Kabayashi, Bruna Garcia Gino, Hélida Mara Magalhães, Rayane Monique Sete da Cruz
Publikováno v:
Colloquium Agrariae, Vol 15, Iss 4, Pp 74-81 (2019)
Entre as hortaliças brasileiras mais cultivadas e consumidas se destacam as alfaces de folhas crespas, cultivadas durante todo o ano em todas as regiões do país. No presente trabalho avaliou-se a produção comercial de alface crespa solta, cultiv
Externí odkaz:
https://doaj.org/article/af8991a0c2b84bffbd2b2ceed622f976
Autor:
Glaucio Leboso Alemparte Abrantes dos Santos, Marcos Renan Besen, Renato Herrig Furlanetto, Luís Guilherme Teixeira Crusiol, Marlon Rodrigues, Amanda Silveira Reis, Karym Mayara de Oliveira, Carolina Fedrigo Coneglian, Roney Berti de Oliveira, Marcelo Augusto Batista, Marcos Rafael Nanni
Publikováno v:
Remote Sensing, Vol 14, Iss 9, p 1972 (2022)
Thousands of chemical analyses are carried out annually with the aim of recommending soil correction; however, these analyses are expensive, destructive, time-consuming, and can be harmful to the environment. As an alternative to conventional analysi
Externí odkaz:
https://doaj.org/article/031d09d973c74e738b22ad8686c4e597
Autor:
Marcos Rafael Nanni, José Alexandre Melo Demattê, Marlon Rodrigues, Glaucio Leboso Alemparte Abrantes dos Santos, Amanda Silveira Reis, Karym Mayara de Oliveira, Everson Cezar, Renato Herrig Furlanetto, Luís Guilherme Teixeira Crusiol, Liang Sun
Publikováno v:
Remote Sensing, Vol 13, Iss 9, p 1782 (2021)
We evaluated the use of airborne hyperspectral imaging and non-imaging sensors in the Vis—NIR—SWIR spectral region to assess particle size and soil organic matter in the surface layer of tropical soils (Oxisols, Ultisols, Entisols). The study are
Externí odkaz:
https://doaj.org/article/e4c2b9d71d2749f8bc0a97cb531fbb81