Soil structure changes in subsoiled solonetzic and chernozemic soils measured by image analysis

Geoderma ◽  
1992 ◽  
Vol 53 (3-4) ◽  
pp. 289-307 ◽  
Author(s):  
M.C.J. Grevers ◽  
E. de Jong
Keyword(s):  
Image Analysis ◽  
Soil Structure ◽  
Structure Changes

Micro-morphological analysis of the effect of sampling by the volumetric ring method on soil structure

2007 ◽  
Vol 3 (1) ◽  
pp. 1-19
Author(s):  
Luiz Pires ◽  
Miguel Cooper ◽  
Nivea Dias ◽  
Osny Bacchi ◽  
Klaus Reichardt
Keyword(s):  
Image Analysis ◽  
Bulk Density ◽  
Size Distribution ◽  
Soil Structure ◽  
Soil Bulk Density ◽  
Soil Samples ◽  
Pore Shape ◽  
Sampling Device ◽  
Structure Changes ◽  
Ring Method

This report investigates the effect of sampling by the volumetric ring method on pore size number and shape distributions. Soil porosity was analyzed using the micromorphological image analysis technique, which helped to explain soil structure changes near the border of samples collected in cylinders and provided detailed information about pore shape, number, and size distribution variations along the samples. Compaction due to sampling affects mainly large irregular and rounded pores of the soils utilized in this study. When evaluating inaccuracies in density measurements due to the compacted regions caused by the sampling device the average soil bulk density for each soil resulted in the ranges of 1.72 ± 0.05 g.cm −3 for Geric Ferralsol soil, 1.66 ± 0.03 g.cm −3 for Eutric Nitosol soil and 1.33 ± 0.05 g.cm −3 for Rhodic Ferralsol soil, respectively. When calculating the average soil bulk density over smaller regions, e.g. in the center of each sample (area of 17.14 mm 2 ) results reduced to 1.64 ± 0.05 g.cm −3 with Geric Ferralsol soil, 1.56 ± 0.03 g.cm −3 with Eutric Nitosol soil and 1.29 ± 0.10 g.cm −3 with Rhodic Ferralsol soil, respectively. These results clearly indicate the effect of sampling by the volumetric ring method. The use of image analysis was essential to explain compaction differences close to the border of the samples collected using cylinders (volumetric ring method) and provided detailed information about pore shape and size distribution variations within soil samples. The results are useful as indicators of the consequences of sampling on the quality of soil samples.

scholarly journals Pore system changes of damaged Brazilian oxisols and nitosols induced by wet-dry cycles as seen in 2-D micromorphologic image analysis

2009 ◽  
Vol 81 (1) ◽  
pp. 151-161 ◽  
Author(s):  
Luiz F. Pires ◽  
Klaus Reichardt ◽  
Miguel Cooper ◽  
Fabio A.M. Cássaro ◽  
Nivea M.P. Dias ◽  
...  
Keyword(s):  
Image Analysis ◽  
Size Distribution ◽  
Soil Structure ◽  
Tropical Soils ◽  
Transport Processes ◽  
Structure Characterization ◽  
Control Treatment ◽  
Simple Method ◽  
Wetting And Drying ◽  
Essential Information

Soil pore structure characterization using 2-D image analysis constitutes a simple method to obtain essential information related to soil porosity and pore size distribution (PSD). Such information is important to infer on soil quality, which is related to soil structure and transport processes inside the soil. Most of the time soils are submitted to wetting and drying cycles (W-D), which can cause important changes in soils with damaged structures. This report uses 2-D image analysis to evaluate possible modifications induced by W-D cycles on the structure of damaged soil samples. Samples of three tropical soils (Geric Ferralsol, GF; Eutric Nitosol, EN; and Rhodic Ferralsol, RF) were submitted to three treatments: 0WD, the control treatment in which samples were not submitted to any W-D cycle; 3WD and 9WD with samples submitted to 3 and 9 consecutive W-D cycles, respectively. It was observed that W-D cycles produced significant changes in large irregular pores of the GF and RF soils, and in rounded pores of the EN soil. Nevertheless, important changes in smaller pores (35, 75, and 150 µm) were also observed for all soils. As an overall consideration, it can be said that the use of image analysis helped to explain important changes in soil pore systems (shape, number, and size distribution) as consequence of W-D cycles.

scholarly journals Strong warming of subarctic forest soil deteriorated soil structure via carbon loss – Indications from organic matter fractionation

2019 ◽  
Author(s):  
Christopher Poeplau ◽  
Páll Sigurðsson ◽  
Bjarni D. Sigurðsson
Keyword(s):  
Organic Matter ◽  
Forest Soil ◽  
Soil Structure ◽  
Terrestrial Ecosystems ◽  
Soil Mass ◽  
Soil Warming ◽  
Ecosystem Responses ◽  
Structure Changes ◽  
Northern Latitudes ◽  
Fraction Distribution

Abstract. Net loss of soil organic carbon (SOC) from terrestrial ecosystems is a likely consequence of global warming and this may affect key soil functions. Strongest changes in temperature are expected to occur at high northern latitudes, with boreal forest and tundra as prevailing land-cover types. However, specific ecosystem responses to warming are understudied. We used a natural geothermal soil warming gradient in an Icelandic spruce forest (0–17.5 °C warming intensity) to assess changes in SOC content in 0–10 cm (topsoil) and 20–30 cm (subsoil) after 10 years of soil warming. Five different SOC fractions were isolated and the amount of stable aggregates (63–2000 µm) was assessed to link SOC to soil structure changes. Results were compared to an adjacent, previously investigated warmed grassland. Soil warming had depleted SOC in the forest soil by −2.7 g kg−1 °C−1 (−3.6 % °C−1) in the topsoil and −1.6 g kg−1 °C−1 (−4.5 % °C−1) in the subsoil. Distribution of SOC in different fractions was significantly altered, with particulate organic matter and SOC in sand and stable aggregates being relatively depleted and SOC attached to silt and clay being relatively enriched in warmed soils. The major reason for this shift was aggregate break-down: topsoil aggregate mass proportion was reduced from 60.7 ± 2.2 % in the unwarmed reference to 28.9 ± 4.6 % in the most warmed soil. Across both depths, loss of one unit SOC caused a depletion of 4.5 units aggregated soil, which strongly affected bulk density (R2 = 0.91 when correlated to SOC and R2 = 0.51 when correlated to soil mass in stable aggregates). The proportion of water extractable carbon increased with decreasing aggregation, indicating an indirect SOC protective effect of aggregates > 63 µm. Topsoil changes in total SOC and fraction distribution were more pronounced in the forest than in the adjacent warmed grassland soils, due to higher and more labile initial SOC. However, no ecosystem effect was observed in the response of subsoil SOC and fraction distribution. Whole profile differences across ecosystems might thus be small. Changes in soil structure upon warming should be studied more deeply and taken into consideration when interpreting or modelling biotic responses to warming.

scholarly journals Quantitative Evaluation of Soil Structure and Strain in Three Dimensions under Shear Using X-ray Computed Tomography Image Analysis

2021 ◽  
Vol 7 (11) ◽  
pp. 230
Author(s):  
Shintaro Nohara ◽  
Toshifumi Mukunoki
Keyword(s):  
Computed Tomography ◽  
Image Analysis ◽  
Shear Zone ◽  
Soil Structure ◽  
Three Dimensions ◽  
Image Correlation ◽  
Ct Scanner ◽  
Zone Formation ◽  
X Ray ◽  
X Ray Computed

The objective of this study is to quantitatively evaluate the soil structure behavior when under shear stress to understand the mechanism of shear zone formation using a micro-focus X-ray computed tomography (CT) scanner to visualize the internal samples without causing disturbance. A new image-analysis method was proposed to systematically evaluate the particle length and direction by fitting the particle as an ellipsoid. Subsequently, a direct shear experiment was conducted on soil materials, and shear band was scanned using a micro-focus X-ray CT scanner. After validating the proposed method, the soil structure was evaluated in the shear zone via image analysis on the CT images. Furthermore, the strain inside the specimen was evaluated using digital image correlation. The results showed that a partial change in the particle direction occurred when the volume expansion inside the shear zone exceeded the peak. In addition, the width of the shear zone was ~7.1 times the median grain size of the sand used; however, the region exhibiting a change in the direction of the particles was narrow and confined to the vicinity of the shear plane.

scholarly journals Support Vector Machine Untuk Klasifikasi Citra Jenis Daging Berdasarkan Tekstur Menggunakan Ekstraksi Ciri Gray Level Co-Occurrence Matrices (GLCM)

2016 ◽  
Vol 6 (1) ◽  
pp. 1 ◽  
Author(s):  
Neneng Neneng ◽  
Kusworo Adi ◽  
Rizal Isnanto
Keyword(s):  
Support Vector Machine ◽  
Image Analysis ◽  
Recognition Rate ◽  
Support Vector ◽  
Gray Level ◽  
Generalization Capability ◽  
Goat Meat ◽  
Horse Meat ◽  
Structure Changes ◽  
Shooting Distance

Texture is one of the most important features for image analysis, which provides informations such as the composition of texture on the surface structure, changes of the intensity, or brightness. Gray level co-occurence matrix (GLCM) is a method that can be used for statistical texture analysis. GLCM has proven to be the most powerful texture descriptors used in image analysis. This study uses the four-way GLCM 0o, 45o, 90o, and 135o. Support vector machine (SVM) is a machine learning that can be used for image classification. SVM has a high generalization capability without any requirement of additional knowledge, even with the high dimension of the input space. The data used in this study are the image of goat meat, buffalo meat, horse meat, and beef with shooting distance 20 cm, 30 cm and 40 cm. The result of this study shows that the best recognition rate of 87.5% was taken at a distance of 20 cm with neighboring pixels distance d = 2 in the direction GLCM 135o.

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