Search Results - "Mallmann, Caroline Lorenci"

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  1. 1

    Leaf-Level Field Spectroscopy to Discriminate Invasive Species (Psidium guajava L. and Hovenia dulcis Thunb.) from Native Tree Species in the Southern Brazilian Atlantic Forest by Mallmann, Caroline, Pereira Filho, Waterloo, Dreyer, Jaqueline, Tabaldi, Luciane, Durgante, Flavia

    Published in Remote sensing (Basel, Switzerland) (01-02-2023)
    “…Invasive species are known to have potential advantages over the native community and can be expressed in their leaf functional traits. Thus, leaf-level traits…”
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    Journal Article
  2. 2

    Estimated flooded rice grain yield and nitrogen content in leaves based on RPAS images and machine learning by Eugenio, Fernando Coelho, Grohs, Mara, Schuh, Mateus, Venancio, Luan Peroni, Schons, Cristine, Badin, Tiago Luis, Mallmann, Caroline Lorenci, Fernandes, Pablo, Pereira da Silva, Sally Deborah, Fantinel, Roberta Aparecida

    Published in Field crops research (01-03-2023)
    “…Remote sensing based on Remote Piloted Aircraft Systems (RPAS) has proved valuable for monitoring agronomic parameters in precision agriculture. This research…”
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    Journal Article
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    Estimation of soybean yield from machine learning techniques and multispectral RPAS imagery by Eugenio, Fernando Coelho, Grohs, Mara, Venancio, Luan Peroni, Schuh, Mateus, Bottega, Eduardo Leonel, Ruoso, Régis, Schons, Cristine, Mallmann, Caroline Lorenci, Badin, Tiago Luis, Fernandes, Pablo

    Published in Remote sensing applications (01-11-2020)
    “…Throughout the plant development, the physiological processes of growth, as well as the handling of water and fertilizers represent sources of variation in the…”
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    Journal Article
  6. 6

    Flooded rice variables from high-resolution multispectral images and machine learning algorithms by Eugenio, Fernando Coelho, Grohs, Mara, Schuh, Mateus Sabadi, Venancio, Luan Peroni, Schons, Cristine, Badin, Tiago Luis, Mallmann, Caroline Lorenci, Fernandes, Pablo, Pereira da Silva, Sally Deborah, Fantinel, Roberta Aparecida

    Published in Remote sensing applications (01-08-2023)
    “…Remote spectral detection via orbital, aerial or terrestrial platforms is considered a valuable tool for non-destructive real-time estimation of the Leaf Area…”
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    Journal Article
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