Uso de índices de reflectância das folhas para avaliar o nível de nitrogênio em grama-bermuda

A reflectância da folha em determinados comprimentos de onda pode ser uma alternativa para estimar a concentração de nitrogênio (N) na planta, devido à relação entre o teor de clorofila e de N no tecido foliar. Este trabalho teve por objetivo avaliar índices da cor verde em grama-bermuda para predizer o nível de N na planta. O experimento foi conduzido em área comercial de produção de grama-bermuda, localizada na cidade de Capela do Alto/SP. O delineamento experimental utilizado foi de blocos ao acaso, com cinco tratamentos (0, 150, 300, 450 e 600kg de N ha-1) e quatro repetições. Foi avaliada a reflectância das folhas pelo uso de medidor de cor de grama, clorofilômetro, e por meio de análise da imagem digital. O matiz (H) e índice de cor verde escuro (ICVE), calculados com base nos índices de reflectância da imagem digital, o ICVE, obtido com medidor de cor de grama, e a intensidade de coloração verde (ICV), obtida com o clorofilômetro, apresentaram forte correlação positiva com a concentração de N e a taxa de cobertura do solo (TCS) da grama-bermuda, podendo ser utilizados como índices auxiliares na recomendação de adubação nitrogenada para a cultura. Os valores obtidos que podem servir como primeiros índices para avaliação do estado nutricional em N na grama-bermuda Celebration são: H de 88 a 109o e ICVE de 0,54 a 0,66 (imagem digital); H de 67 a 76o e ICVE de 0,41 a 0,44 (medidor de cor da grama TCM 500); e ICV de 374 a 471 (clorofilômetro CM 1000).

Effects of aluminum-copper alloy filtration on photon spectra, air kerma rate and image contrast

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Signal classification of submerged aquatic vegetation based on the hemispherical-conical reflectance factor spectrum shape in the yellow and red regions

The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Image quality evaluation of chest for computed radiography

The daily-to-day of medical practice is marked by a constant search for an accurate diagnosis and therapeutic assessment. For this purpose the doctor serves up a wide variety of imaging techniques, however, the methods using ionizing radiation still the most widely used because it is considered cheaper and above all very efficient when used with control and quality. The optimization of the risk-benefit ratio is considered a major breakthrough in relation to conventional radiology, though this is not the reality of computing and digital radiology, where Brazil has not established standards and protocols for this purpose. This work aims to optimize computational chest radiographs (anterior-posterior projection-AP). To achieve this objective were used a homogeneous phantoms that simulate the characteristics of absorption and scattering of radiation close to the chest of a patient standard. Another factor studied was the subjective evaluation of image quality, carried out by visual grading assessment (VGA) by specialists in radiology, using an anthropomorphic phantom to identify the best image for a particular pathology (fracture or pneumonia). Quantifying the corresponding images indicated by the radiologist was performed from the quantification of physical parameters (Detective Quantum Efficiency - DQE, Modulation Transfer Function - MTF and Noise Power Spectrum - NPS) using the software MatLab®. © 2013 Springer-Verlag.