Use of digital images for evaluating soil compaction in the culture of beans Uso de imagens digitais para avaliação da compactação do solo na cultura do feijão

Bean yield in Brazil is considered low, around 820 kg ha-1, reaching values above 3000 kg ha-1, there are several environmental factors which may limit the performance of this culture, especially those related to the soil. The present work aimed to evaluate soil compactions in bean culture of different soil management systems, by means of digital images. This study took place at the Federal University of Viçosa, randomized block design with six replications was used and four treatments, (direct planting, conventional preparation, minimum plantation using grade crusher-leveler and minimum plantation using scarificator), were evaluated. The spectral responses using the vegetation indexes (NDVI, RS, GNDVI, VARI, WDRVI and SAVI) were evaluated, calculated from digital numbers of the images and the values were estimated from the reflectance. For obtainning the images, a platform containing two digital cameras, one sensitive in the region of visible (RGB) and another sensitive to the region of proximal infrared were used, this platform was attached to a helium-inflatable balloon. The vegetation indexes obtained from the values of digital numbers of images were only able to defer treatments 70 days after plantation. However, indexes obtained from the reflectance, deferred treatments at 34 and 70 days after planting.<br>A produtividade do feijoeiro no Brasil é considera baixa entorno de 820 kg ha-1, podendo atingir valores acima de 3.000 kg ha-1, vários fatores ambientais podem limitar o bom desempenho da cultura, principalmente os relacionados ao solo. Sendo assim objetivou-se com a realização deste trabalho avaliar a compactação do solo na cultura do feijoeiro em diferentes sistemas de manejo do solo, por meio de imagens digitais. Este trabalho foi realizado na Universidade Federal de Viçosa, utilizou-se o delineamento em blocos ao acaso com seis repetições, sendo quatros tratamentos avaliados (plantio direto, preparo convencional, cultivo mínimo utilizando grade niveladora-destorroadora e cultivo mínimo utilizando escarificador). Foram avaliados a resposta espectral utilizando índices de vegetação (NDVI, RS, GNDVI, VARI, WDRVI e SAVI), calculados a partir dos valores dos números digitais das imagens e dos valores estimados da reflectância. Para aquisição das imagens foi utilizado uma plataforma contendo duas câmeras digitais, uma sensível na região do visível (RGB) e a outra sensível na região do infravermelho próximo, esta plataforma foi acoplada a um balão inflado com gás hélio. Os índices de vegetação obtidos a partir dos valores dos números digitais das imagens só foram capazes de diferirem os tratamentos aos 70 dias após o plantio. Os índices obtidos pelos valores estimados da reflectância diferiram os tratamentos aos 34 e 70 dias após o plantio

Spatial distribution of soil hydraulic parameters estimated by pedotransfer functions for the Jialing River Catchment, Southwestern China

Soil hydraulic parameters θ s, α, n, K s, L and θ r of the van Genuchten-Mualem model were estimated using three pedotransfer functions (PTFs) based on soil properties for surface soils of the largest main tributary catchment (the Jialing River) of the upper Yangtze River in China. The soil database was from the second national soil survey of China with a spatial 30 X 30 arc-second resolution. According to the statistical analysis of the differences between the continuous-PTFs-estimated values of soil hydraulic parameters for the study catchment and the reference values for a specific texture class provided in the development database of a specific PTF, best estimations were obtained using the Wösten PTF. The Rawls & Brakenssiek PTF was good estimation for parameter θ r that was assumed as zero by Wösten PTF. The established higher θ r (0.08%) and lower K s (20 cm/d) and θ s (0.43%) in the mid-downstream area relative to the other areas of the catchment could lead to larger amounts of surface runoff and consequently provide higher energy to erode soil. Thus, these factors provide a supporting explanation for previously reported severe soil erosion occurring in this area. Spatial heterogeneity analysis for estimated hydraulic parameters in terms of semivariogram showed that the spatial correlation distance was in the range of 50-80 km and that the spatial variability (sill) was not large except for parameters K s and L. The semi-variance with the exponential model at the zero distance (nugget) was 30%-50% of the sill. This study provided a practical PTF approach for estimating soil hydraulic properties from soil survey data at a large watershed scale. The estimation results could provide better insight into the mechanism of surface runoff and soil erosion, which is important to better understand and manage erosion in the catchment