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SENSOR SYSTEMS FOR MAPPING SOIL FERTILITY ATTRIBUTES: CHALLENGES, ADVANCES, AND PERSPECTIVES IN BRAZILIAN TROPICAL SOILS REA
Molin,José Paulo; Tavares,Tiago Rodrigues.
ABSTRACT Soil fertility attributes have different scales and forms of spatial and temporal variations in agricultural fields. Adequate spatiotemporal characterization of these attributes is fundamental to the successful development of strategies for variable rate application of fertilizers, enabling the classic benefits of precision agriculture (PA). Studies on Brazilian soil have shown that at least 1 sample ha-1 is required for the reliable mapping of key fertility attributes. However, this sampling density is difficult owing to the operational challenges of sample collection and the cost of laboratory analyses. Given this limitation, soil sensors have emerged as a practical and complementary technique for obtaining information on soil attributes, at...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Spatial variability; Spectroscopy; On-the-go sensing; Hybrid laboratory.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162019000800126
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Effects of storage on vis-NIR-SWIR reflectance spectra of Mombasa grass leaf samples Ciência Rural
Tavares,Tiago Rodrigues; Fiorio,Peterson Ricardo; Seixas,Hugo Tameirão; Garcia,Amparo Cisneiros; Barros,Pedro Paulo da Silva.
ABSTRACT: Vis-NIR-SWIR reflectance spectra of leaf samples, collected in the laboratory, allow the calibration of predictive models to quantify their physicochemical attributes in a practical manner and without producing chemical residues. This technique should enable the development of management strategies for intensification of pasture use. However, spectral analysis performed in the laboratory may be affected by the deterioration of plant material during transport from the field to the lab, so storage methods are necessary. This research aimed to evaluate the effects of different storage methods on the spectral response of Mombasa grass leaves. Three methods were evaluated: (i) artificially refrigerated environment, (ii) humid environment, and (iii)...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Diffuse reflectance spectroscopy; Hyperspectral sensors; Forage; Precision agriculture.
Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000300401
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