INTRODUCTION

The pores of the soil are represented by cavities with different sizes and shapes, determined by the arrangement of solid particles which constitute a volumetric fraction of the soil filled withair, water and nutrients solution (Hillel, 1972). The soil porosity influences in aeration, water conduction and retention, resistance to penetration and branching of the roots in the soil and, consequently use of availablewater and nutrients (Tavares Filho, J. & Tessie, Stubff et al, 2014). Several techniques can be used to obtain soil porosity index. In the search for new techniques aimed at complementing and adding new data on Ferralsols,high resolution computer microtomography (microCT) appears as a non-destructive and fast analytical technique. MicroCT has been outstanding in the international scenarios and it is more and more present in soil analyses. Analyzinga soil sample by microCT allows obtaining knowledge, in microscale, on shape, size, distribution, volume, area and pore connectivity and having a 3D visualization of the soil sample and its structure.

The microCT provides high resolution images with a set of volume data of an inspected sample that does not need to be modified and no preparation method has been submitted. Its physical principle is basedon the attenuation of the X-rays when they interact with the object and are modulated according to the physical characteristics. To obtain microCT images, it is necessary to acquire many projections at constant angular stepsand the reconstruction is performed with an appropriate algorithm based on the filtered overhead, (Machado et al., 2015)

Soil attributes can be visualized, quantified and simulated using three-dimensional (3D) image processing of the pore space, using dynamic models obtained from computed tomography, using different sourcesof radiation, and as examples of studies (Pires et al., 2010), and the effects of soil erosion on soil erosion. The density of particles (Crestana, 1992) porosity (Luo; Lin; Li, 2010; Munkholm; Heck; Deen, 2012); (Sleutelet al., 2008), distribution of the root system in a porous medium (Garbout et al., 2012; Kaestner, Schneebeli, Graf, 2006;

The objective of this work is to use microCT to compare the porosity distribution and pore connectivity density between a soil without vegetation cover and a soil with grass cover, both Ferralsols. Fourundisturbed samples of each soil were collected.

MATERIALS AND METHODOLOGY

The work developed on a slope within the limits of the Stream of Thorn Microbasin, which has a total area of 9.14km2 being located in the Farming Paiol, where agricultural activities related to the geneticimprovement of cattle and dairy cattle are developed. The area is located in the municipality of Silva Jardim, State of Rio de Janeiro, and access is given by BR 101. (Fig.1).

The undisturbed samples for the tests were collected on the half slope of a dissected hill within the limits established by erosion plots (A), totaling eight replicates packed in plastic film for transportationand handling without loss (B). The samples were distributed in the following way: four in soil with grass cover (1) and four in soil without vegetation cover (2), using acrylic tubes measuring 50mm in height and 32mm in diameter(C). (Fig. 2)

The samples were scanned in a high energy system - Skyscan / Bruker, model1173. The Figure 3 show the microCT experimental setup. The system operates with voltage and current of 130 kV and 61 μA,respectively. A flat panel detector (2240 x 2240 pixels) was used to register the transmission of the X-ray beam. All the acquisition parameters are presented in table 1. After acquisition, the image is captured and reconstructedusing the FDK reconstruction algorithm, (Feldk Davis; Kress, 1984).

After reconstruction 3D models were built highlighting the porous space versus soil matrix. Then, total porosity and density of connectivity among the pores were measured. For these quantitative analyzes,the first step is to determine the region of interest (ROI) and / or volume of interest (VOI), represented respectively in two and three dimensions. ROI relate to a cross section where the 2D analysis will be carried out,while VOI relate to the sum of all the cross sections that represent a 3D volume. However, there is no law of thumb used to determine the segmentation (threshold value), (Gonzalez and Woods, 2002).

In the present study, we chose to use a adaptive method segmentation. In this method for each voxel, the threshold is calculated as the mean of all pixel/voxel grayscales within a selected radius. Inthis way, the binary image is obtained, with the objects (soil matrix) in white and the background (pore) in black. Thus, it was possible to quantify the total porosity and density of connectivity. The schematic of this segmentationis shown in Figure 4.

RESULTS AND DISCUSSIONS

To acquire the data, the values of the parameters were adjusted to acquire the information within a pattern that responded in the most accurate way, searching for the openings with the smallest possiblesize, in order to identify more clearly the class of Micropores. In this sense the soil pore diameters analyzed were classified according to Brewer (1964) that define micropores that have a diameter smaller than 0.03mm andmacropores larger than this value.

Covered soil (CS) presented the following percentages of total porosity: 21.1; 24.6; 27.3 and 36.7%; As the soil without cover (SWC) had porosities of 13.6; 20.5; 21.8 and 30.8%. The pore densities inthe covered soil were 46.7; 76.7; 155.4 and 508.63 mm3, while in the uncovered terrain were 19.9; 45.8; 76.7 and 511.3 mm3. The values of soil porosity presented higher values in the soil covered with grass in relation tothe same pairs of soil samples without vegetation cover. This trend was also observed in the values of density of connections between the pores.

The values corresponding to macroporosity were 7.37; 13.78; 9.01 and 12.54% on CS soil and 7.66; 7.48; 13.18; 12.52% not only SWC. Both coverages obtained an average very close to this index, varyingonly 0.46%. Already the values of microporosity for the soil CS was 13.75; 10.91; 18.37 and 24.17%, in SWC soil the indices were in the houses of 5.94; 13.08; 8.71 and 18.36. In this cyst it is noticed that there is evidencefor CS soil, showing an average 5% higher than SWC soil. This can be explained because the permanence of the vegetal cover increases organic matter in the soil, it keeps the root system active and assists in the stabilityof its aggregates generating an increase of the microporisdade according to Viana et al (2011).

In order to obtain a standard of comparison, the soil water retention curve test was carried out in soil samples from the same aforementioned environments (CS and SWC), which presents several practical,technical and scientific applications, such as: The determination of the soil field capacity, the permanent wilting point and the total availability of water in the soil, indispensable variables for an adequate irrigationmanagement, soil water balance and macro and micro porosity (Table 2).

One of the ways to determine the water retention curve in the soil is to use the Richards pressure chamber, which simulates a determined tension in the soil sample and later, by weight difference (wetsoil after being subjected to pressure - Soil dried in an oven at 105 ºC for 48 hours), the water content related to the applied voltage is determined. For all eight samples submitted to the assay an eight-strain sequencewas applied on the following increasing scale: 0.01; 0.033; 0.06; 0.33; 1.00; 5.00 and 15.00 bar.

What is evident when carrying out a relationship with both methods is that the Retention Curve is larger than the Computed Microtomography because this method can identify a greater percentage of microporosityreaching the house of 23.17% more in the soil CS and 28.05% in soil SWC. This is due to the fact that the maximum resolution of the MCT reaches the equivalent of 0.03mm, however there are a series of pores with smaller sizesthat are not identified by the tomographic sensors. Regarding macroporosity data, the Retention Curve showed an average of 12.11% for CS soil and 5.40% for SWC soil. In this same index for MCT, 10.21% for CC soils and 11.52for SWC were presented. This demonstrates a greater capacity of the microtomography in the identification of pores larger than 0.03mm, mainly to environments that have already been worn in compacts for a period of five years.

To evaluate the total porosity and soil structure after reconstruction of the images from the Microtomography data, the following templates will be used (Fig. 5). This will allow the visual localizationof the information described in a more dynamic and fast way. This porosity profile is constructed from the slice evaluation by slice of the whole sample body measuring 5.0cm.

The porosity profile of sample 1 (Fig. 6.1), which corresponds to the system with coverage (CS), concentrates around 24% of the porosity at the base and gradually decreases this value with the proximityof the surface. In the first few centimeters there is a significant increase in relation to the average of the whole body of the sample, going from 8.0% to 16% in a few centimeters of difference. If we correlate these valueswith the coronal profile image (Fig. 7.1) of the same sample we can see the presence of some significant voids in the 2nd and 3rd quadrant that corroborate with the presented values.

In the sample 2CS (Fig. 6.2) the porosity at the base is 25%, presented a considerable increase, rising to 37.5% in a space of 1cm and then decreasing gradually to 2.5 cm in height, later the values presentAn increase of the total porosity until reaching the top of the sample with 44%. These high values at the beginning of the base and at the top of the top are visually confirmed by observing that the coronal profile (Fig. 7.2)shows a large crack in the 1st quadrant and a contrast between matrix and well-disaggregated pores.

The sample 3CS (Fig. 6.3) has a very similar behavior with the previous sample, the porosity in the base is high because of a defragmentation presented by the sample in the 4th quadrant (Fig. 7.3) whichalso occurs in the third elevating quadrant The porosity in the final centimeters of the top, reaching 40%.

The last soil sample with 4CS coverage (Fig. 6.4), has a high porosity at the base (35%) and a lower percentage at the top (34%). However, in the centimeters that precede the top, it presents a 20% elevationof the house because of circular spaces that can be understood as paths of the microfauna of the soil or old roots that were incorporated to the organic matter. This occurs in the 1st and 2nd quadrant (Fig. 7.4).

However, in the soil samples without vegetation cover (SWC) the behavior was slightly different. In the sample 1SWC (Fig. 6.5) the porosity in the base is in the 10% and has its highest values at thetop, reaching 36%, which is evidenced by the concentration of mineral matrix in the 3rd and 4th quadrants (Fig. 7.5).

In the sample 2SWC (Fig. 6.6) the base already presents high porosity starting from 39%, reaching 56% at the top. The presence of ducts explains this increase according to height, especially in the 1stquadrant (Figure 7.6). The sample 7SWC (Figure 6.7) presents a porosity of 38% at the base and reaching 40% at the top, it is observed that at the ends of all the quadrants there is an evident disintegration of particles,since the matrix region is with faults of Occurrence (Fig. 7.7).

In the last sample 4SWC (Fig. 6.8) a fluctuation of the values occurs, since cracks denoting porosity are observed throughout the sample length (Fig. 7.8). In the 1st and 2nd quadrants, the values risein a very generalized way because there is an opening in the soil that could have been constructed by roots or by the contraction of the soil after the procedures of preparation of the samples, mainly the drying.

CONCLUSIONS

The results show that the presence of the vegetal cover is a relevant factor in the increase of the porosity of the superficial layers of the soil, because the root system develops ducts that are connectedwith the progress of its development. In this sense, identified a concentration of 18.60 g/dm3 of organic carbon in the A horizon of this soil, which may aid in the stability of aggregates and condition the occurrence of pores.On the other hand, the lack of vegetation cover considerably reduces the pore indices of the superficial layers of the soil, which can be explained by the fact that the sealing process of the exposed soil occurs when the materialdisaggregated by erosion caused by the impact of the raindrops (Splash) obliterates the pores, corroborating with this hypothesis identified, for the same area, very high apparent density values for horizon A, at the houseof 1.45 g/dm3. Thus, the MicroCT technique demonstrated an efficient and non-destructive tool for the analysis and characterization of the pore structure of soils protected from and degraded by erosion, underlining clear differencesbetween them, as expected.

ACKNOWLEDGMENTS

The authors would like to thank EMBRAPA for the partnership, as well as, CAPES and FAPERJ for the financial supports. The author thanks UNESA for the Research and Productivity Exchange.

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