Soil texture spatial variability of different parent material in pereira barreto, São Paulo state

The variation of soil textural characteristics is a function of the relief and parent materials. The objective of this work was to study soil texture spatial variability from different parent material in Pereira Barreto, SP. An area of 530.67 hectares was mapped through the use of Global Positioning System receivers and obtaining of Digital Elevation Models. A set of 201 soil samples was collected from every seven hectares, at three depths: 0 - 0.25 m; 0.25 - 0.50 m; and 0.80 - 1.00 m. The amounts of sand, silt and clay were obtained by the pipette method and analyzed by both descriptive statistics and geostatistics. Soil textures varied as a function of parent materials and topography.

Potassium Leaching as Affected by Soil Texture and Residual Fertilization in Tropical Soils

Potassium (K) leaching is affected by soil texture and available K, among other factors. In this experiment, effects of soil texture and K availability on K distribution were studied in the presence of roots, with no excess water. Soils from two 6-year field experiments on a sandy clay loam and a clay soil fertilized yearly with 0, 60, 120, and 180 kg ha-1 of K2O were accommodated in pots that received 90 kg ha-1 of K2O. Soybean was grown up to its full bloom (R2). Under field conditions, K leaching below the arable layer increased with K rates, but the effect was less noticeable in the clay soil. Potassium leaching in a sandy clay loam soil was related to soil K contents from prior fertilizations. With no excess water, in the presence of soybean roots, K distribution in the profile was significant in the lighter textured soil but was not apparent on the heavier textured soil.

Correction of soil acidity in the subsurface of an oxisol with sandy loam texture under no-tillage

No Rio Grande do Sul (RS), muitas áreas sob plantio direto apresentam elevada saturação por Al e baixa saturação por bases na camada de 0,10-0,20 m (subsuperfície), e isso pode diminuir a produção de grãos de culturas anuais. O objetivo do presente trabalho foi avaliar se a ocorrência de alta saturação por Al e baixa saturação por bases em subsuperfície (0,10-0,20 m), no plantio direto, pode representar um ambiente restritivo para a produção de culturas, bem como avaliar os modos de incorporação de calcário na correção da acidez do solo em subsuperfície. Para isso, foi realizado um experimento com os cultivos de soja (2005/ 2006), milho (2006/2007), trigo (2007) e soja (2007/2008), em um Latossolo Vermelho distrófico típico (Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), 2006) de textura franco arenosa, há quatro anos sob plantio direto, no município de Tupanciretã (RS). Os seis tratamentos foram: sem revolvimento com ou sem calcário; lavração com ou sem calcário; e escarificação com ou sem calcário. Aos 24 meses após a aplicação dos tratamentos e nas camadas de 0-0,05, 0,05-0,10, 0,10-0,15, 0,15-0,20 e 0,20-0,30 m, foram avaliados os valores de pH-H2O, saturação por Al e por bases. Avaliou-se a produtividade de soja (2005/2006), milho (2006/2007), trigo (2007) e soja (2007/2008). A acidez do solo em subsuperfície não alterou a produtividade das culturas quando as propriedades de acidez na camada de 0-0,10 m estavam em níveis em que não se recomenda a aplicação de calcário, segundo a CQFSRS/SC (2004). A incorporação de calcário com aração foi o modo mais eficiente de corrigir a acidez em profundidade.

Fractal analysis of leaf-texture properties as a tool for taxonomic and identification purposes: a case study with species from Neotropical Melastomataceae (Miconieae tribe)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fuzzy Logic and Geostatistical Techniques for Spatialization of Soil Texture in Region with Rough Terrains

From the geotechnical standpoint, it is interesting to analyse the soil texture in regions with rough terrain due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this paper is to present a methodology that provides the soil texture spatialization by using Fuzzy logic and Geostatistic. The results were correlated with maps drawn specifically for the study area. The knowledge of the spatialization of soil properties, such as the texture, can be an important tool for land use planning in order to reduce the potential soil losses during rain seasons. (c) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

Corn texture and particle size in broiler diets

The objective of this study was to evaluate the effect of corn texture and the particle size on broiler performance, carcass yield, nutrient digestibility, and digestive organ morphometrics. In Experiment I, 720 male Cobb chicks were distributed in a completely randomized experimental design with a 2 x 3 factorial arrangement, consisting two corn textures (dented and hard) and three corn particle sizes, was applied, with four replicates of 30 birds each. Corn particle size was classified according to geometric mean diameter (GMD) as fine - 0.46 mm; medium - 0.73 mm, and coarse - 0.87 mm. In Experiment II, 120 broiler chicks were used to evaluate corn digestibility during the periods of 16 to 22 days and 35 to 41 days of age, using the method of total excreta collection. In Experiment I, corn particle size influenced body weight, average weight gain, feed intake and feed conversion ratio of 21-day-old birds. Corn texture and particle size did not affect the performance of 42-day-old broilers or carcass traits. In Experiment II, there was no influence of corn texture and particle size on digestive organ weights. Dented corn increased nitrogen excretion in the first trial, and hard corn improved dry matter digestibility in the second metabolic trial. Corn with fine particle size promotes better performance of broilers at 21 days of age. Hard corn results in higher dry matter digestibility and lower nitrogen excretion, and consequently higher production factor in 42-day-old broilers.

The effects of extrusion conditions and the addition of volatile compounds and flavour enhancers to corn grits on the retention of the volatile compounds and texture of the extrudates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Automatic estimation of crowd density using texture

This paper considers the role of automatic estimation of crowd density and its importance for the automatic monitoring of areas where crowds are expected to be present. A new technique is proposed which is able to estimate densities ranging from very low to very high concentration of people, which is a difficult problem because in a crowd only parts of people's body appear. The new technique is based on the differences of texture patterns of the images of crowds. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures. The image pixels are classified in different texture classes and statistics of such classes are used to estimate the number of people. The texture classification and the estimation of people density are carried out by means of self organising neural networks. Results obtained respectively to the estimation of the number of people in a specific area of Liverpool Street Railway Station in London (UK) are presented. (C) 1998 Elsevier B.V. Ltd. All rights reserved.

On the efficacy of texture analysis for crowd monitoring

The goal of this work is to assess the efficacy of texture measures for estimating levels of crowd densities ill images. This estimation is crucial for the problem of crowd monitoring. and control. The assessment is carried out oil a set of nearly 300 real images captured from Liverpool Street Train Station. London, UK using texture measures extracted from the images through the following four different methods: gray level dependence matrices, straight lille segments. Fourier analysis. and fractal dimensions. The estimations of dowel densities are given in terms of the classification of the input images ill five classes of densities (very low, low. moderate. high and very high). Three types of classifiers are used: neural (implemented according to the Kohonen model). Bayesian. and an approach based on fitting functions. The results obtained by these three classifiers. using the four texture measures. allowed the conclusion that, for the problem of crowd density estimation. texture analysis is very effective.

Texture and Microstructure of Gelatin/Corn Starch-Based Gummy Confections

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Oriented texture classification based on self-organizing neural network and Hough transform

This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.