Software for micromorphometric characterization of soil pores obtained from 2-D image analysis

ABSTRACT Studies of soil porosity through image analysis are important to an understanding of how the soil functions. However, the lack of a simplified methodology for the quantification of the shape, number, and size of soil pores has limited the use of information extracted from images. The present work proposes a software program for the quantification and characterization of soil porosity from data derived from 2-D images. The user-friendly software was developed in C++ and allows for the classification of pores in terms of size, shape, and combinations of size and shape. Using raw data generated by image analysis systems, the software calculates the following parameters for the characterization of soil porosity: total area of pore (Tap), number of pores, pore shape, pore shape and pore area, and pore shape and equivalent pore diameter (EqDiam). In this paper, the input file with the raw soil porosity data was generated using the Noesis Visilog 5.4 image analysis system; however other image analysis programs can be used, in which case, the input file requires a standard format to permit processing by this software. The software also shows the descriptive statistics (mean, standard deviation, variance, and the coefficient of variation) of the parameters considering the total number of images evaluated. The results show that the software is a complementary tool to any analysis of soil porosity, allowing for a precise and quick analysis

Assemblage des constituants fins et grossiers du sol à l'échelle microscopique. Quantification par analyse d'image.

National audienc

Les jeunes et le monde du vin

Géoconfluences. Dossier Le vin entre sociétés, marchés et territoires. En ligne : http://geoconfluences.ens-lsh.fr/doc/typespace/vin/VinScient8.ht

Oscillations journalieres de la profondeur des nappes en l'absence de precipitations

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Quantification de la distribution relative des constituants fins et grossiers dans un sol par MEB, analyse X et analyse d'images

National audienc

Quantification de la distribution relative des constituants grossiers et fins par analyse d'image.

Symposium 30. Présentation orale. Texte complet + résuméNational audienc

Inability of near infrared reflectance spectroscopy (NIRS) to identify belowground earthworm casts in no-tillage soil

Several studies have emphasised the ability of Near Infrared Reflectance Spectroscopy (NIRS) to identify surface earthworm casts in the field. However, less is known about casts deposited within the soil, which usually represent the majority found in the field. This study tested the ability of NIRS to identify belowground casts in agricultural systems. Casts and surrounding soils were sampled at depths of 20–30 cm in a loamy soil under no tillage for 12 years. To distinguish different types of cast, sizes and orientations relative to the horizontal plane were measured. NIRS analyses and analyses of carbon and nitrogen content were also performed to compare casts to surrounding soils. Casts were classified into 4 size classes, with no preferential orientation. Cast carbon and nitrogen content were not influenced by their size and did not differ from surrounding soils. PCAs performed on the NIRS data did not allow casts to be differentiated from surrounding soils, regardless of size class. However, soil aggregates were clearly differentiated probably due to their spatial distribution in the soil. Although this study did not identify specific NIRS signatures for casts, it shows the utility of this method to investigate the origin of the soil consumed by earthworms. In our case, NIRS analyses suggest that the high bulk density of the soil (1.42 g cm−3) forced ingestion by endogeic earthworms, simply to move around, without preferential selection for organic matter. Consequently, their casts were deposited a few mm from where they had ingested soil with similar organic matter quality