%0 Conference Proceedings
%4 sid.inpe.br/marte2/2017/10.27.13.40.22
%2 sid.inpe.br/marte2/2017/10.27.13.40.23
%@isbn 978-85-17-00088-1
%F 59700
%T Análise Espectral Orbital da Sigatoka Amarela da Bananeira e Sua Relação com a Nutrição Mineral do Solo e das Plantas
%D 2017
%A Rodrigues, Julia Dal Poggetto,
%A Alves, Marcelo de Carvalho,
%A Freitas, Aurivan Soares de,
%A Pozza, Edson Ampélio,
%@electronicmailaddress juliapoggetto@posgrad.ufla.br
%E Gherardi, Douglas Francisco Marcolino,
%E Aragão, Luiz Eduardo Oliveira e Cruz de,
%B Simpósio Brasileiro de Sensoriamento Remoto, 18 (SBSR)
%C Santos
%8 28-31 maio 2017
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%P 4048-4055
%S Anais
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%X The banana (Musa spp.) is a food that is included in the diet of various social strata, produced by small, medium and large producers. When the banana tree is in a vulnerable state it is susceptible to attack by diseases such as Yellow Sigatoka, which may cause reduction of the number of banana bunches and fruit size. This disease is among the most destructive and occurs throughout Brazil. Remote sensing has a potential monitoring and agricultural planning, serving to detection and monitoring of plants attacked by pathogens. This study aimed to characterize the Yellow Sigatoka on a banana plantation using vegetation indices and correlates them with nutrition data of the plant and soil. The selected pixels covered areas with high, medium and low incidence of Yellow Sigatoka and the spectral behavior was measured. Vegetation indices related to physiological parameters, such as the Normalized Difference Vegetation Index, Normalized Difference Water Index, Modified Normalized Difference Water Index, Green Normalized Difference Vegetation Index and Red Edge Position were calculated and correlated with plant and soil nutrition data. There was an increase in reflectance in the region of 1.4 to 1.9 µm indicating loss of water by the leaf. Mn, Ca, Mg, Zn and organic matter presented a correlation with the vegetation indexes calculated. The GNDVI was the index that presented the highest correlation with the data in situ.
%9 Agricultura e silvicultura
%@language pt
%3 59700.pdf