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

Authors

  • Miguel Cooper University of São Paulo; ESALQ; Dept. of Soil Science
  • Raquel Stucchi Boschi University of São Paulo; ESALQ; Dept. of Soil Science
  • Vitor Boschi da Silva University of São Paulo; ICMC
  • Laura Fernanda Simões da Silva University of São Paulo; ESALQ; Dept. of Soil Science

DOI:

https://doi.org/10.1590/0103-9016-2015-0053

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.

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Published

2016-08-01

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How to Cite

Software for micromorphometric characterization of soil pores obtained from 2-D image analysis . (2016). Scientia Agricola, 73(4), 388-393. https://doi.org/10.1590/0103-9016-2015-0053