Potential of Spectroradiometry to Classify Soil Clay Content

ABSTRACT Diffuse reflectance spectroscopy (DRS) is a fast and cheap alternative for soil clay, but needs further investigation to assess the scope of application. The purpose of the study was to develop a linear regression model to predict clay content from DRS data, to classify the soils into three textural classes, similar to those defined by a regulation of the Brazilian Ministry of Agriculture, Livestock and Food Supply. The DRS data of 412 soil samples, from the 0.0-0.5 m layer, from different locations in the state of Rio Grande do Sul, Brazil, were measured at wavelengths of 350 to 2,500 nm in the laboratory. The fitting of the linear regression model developed to predict soil clay content from the DRS data was based on a R2 value of 0.74 and 0.75, with a RMSE of 7.82 and 8.51 % for the calibration and validation sets, respectively. Soil texture classification had an overall accuracy of 79.0 % (calibration) and 80.9 % (validation). The heterogeneity of soil samples affected the performance of the prediction models. Future studies should consider a previous classification of soil samples in different groups by soil type, parent material and/or sampling region.

Spectroradiometry of soil and comparison with orbital sensors

The aim of this study was to characterize and compare the spectral behavior of different soil classes obtained by orbital and terrestrial sensors. For this, an area of 184 ha in Rafard (SP) Brazil was staked on a regular grid of 100x100 m and soil samples were collected and georeferenced. After that, soil spectral curves were obtained with IRIS sensor and the sample points were overlaid at Landsat and ASTER images for spectral data collection. The soil samples were classified and mean soil curves for all sensors were generated by soil classes. The soil classes were differentiated by texture, organic matter and total iron for all sensors studied, the orbital sensors despite the lower spectral resolution, maintained the characteristics of the soil and the curves of reflectance intensity.

Detecção de Heterodera glycines em plantio de soja mediante espectrorradiometria no visível e infravermelho próximo

O ataque do nematóide de cisto da soja, Heterodera glycines, limita o potencial de expansão e maior produtividade de áreas plantadas com soja (Glycine Max). O conhecimento da distribuição espacial desse patógeno na lavoura é fundamental, para elaboração de estratégias de manejo. A área em estudo estava localizada em lavoura de soja, variedade BRS133, localizada no Município de Florínea, SP, com solos naturalmente infestados por H. glycines. Foram obtidas medidas de espectrorradiometria de campo, 112 dias após o plantio, nas regiões do visível e do infravermelho próximo do espectro eletromagnético, a fim de se conhecer o padrão da resposta espectral de plantas atacadas pelo fitonematóide. Paralelamente, foram retiradas amostras de solo e encaminhadas ao Laboratório de Nematologia, Departamento de Fitossanidade da Universidade Estadual Paulista Júlio de Mesquita Filho, Campus de Jaboticabal, onde foram processadas para determinação da densidade populacional do nematóide. As medidas do espectrorradiômetro foram transformadas em índice vegetativo, com diferença normalizada (NDVI), que foi relacionado com a densidade populacional do nematóide, peso da matéria fresca e número de vagens por planta. Observou-se que diferentes densidades de população estão diretamente relacionados com a resposta espectral das plantas expressa, através dos valores do NDVI.

Influência da bacia hidrográfica e características espaço-temporais de variáveis limnológicas sobre reservatórios no Rio Jacuí - RS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Assessing biophysical variable parameters of bean crop with hyperspectral measurements

Recently high spectral resolution sensors have been developed, which allow new and more advanced applications in agriculture. Motivated by the increasing importance of hyperspectral remote sensing data, the need for research is important to define optimal wavebands to estimate biophysical parameters of crop. The use of narrow band vegetation indices (VI) derived from hyperspectral measurements acquired by a field spectrometer was evaluated to estimate bean (Phaseolus vulgaris L.) grain yield, plant height and leaf area index (LAI). Field canopy reflectance measurements were acquired at six bean growth stages over 48 plots with four water levels (179.5; 256.5; 357.5 and 406.2 mm) and tree nitrogen rates (0; 80 and 160 kg ha-1) and four replicates. The following VI was analyzed: OSNBR (optimum simple narrow-band reflectivity); NB_NDVI (narrow-band normalized difference vegetation index) and NDVI (normalized difference index). The vegetation indices investigated (OSNBR, NB_NDVI and NDVI) were efficient to estimate LAI, plant height and grain yield. During all crop development, the best correlations between biophysical variables and spectral variables were observed on V4 (the third trifoliolate leaves were unfolded in 50 % of plants) and R6 (plants developed first flowers in 50 % of plants) stages, according to the variable analyzed.