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Software for micromorphometric characterization of soil pores obtained from 2-D image analysis
Cooper, Miguel; Boschi, Raquel Stucchi; Silva, Vitor Boschi da; Silva, Laura Fernanda Simões da.
Affiliation
  • Cooper, Miguel; University of São Paulo. Escola Superior de Agricultura Luiz de Queiroz. Dept. of Soil Science. Piracicaba. BR
  • Boschi, Raquel Stucchi; University of São Paulo. Escola Superior de Agricultura Luiz de Queiroz. Dept. of Soil Science. Piracicaba. BR
  • Silva, Vitor Boschi da; University of São Paulo. Instituto de Ciências Matemáticas e de Computação. São Carlos. BR
  • Silva, Laura Fernanda Simões da; University of São Paulo. Escola Superior de Agricultura Luiz de Queiroz. Dept. of Soil Science. Piracicaba. BR
Sci. agric ; 73(4): 388-393, 2016. ilus, tab
Article in En | VETINDEX | ID: biblio-1497572
Responsible library: BR68.1
Localization: BR68.1
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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Full text: 1 Database: VETINDEX Main subject: Image Processing, Computer-Assisted / Software / Soil Analysis / Soil Characteristics / Porosity Language: En Journal: Sci. agric / Sci. agric. Year: 2016 Document type: Article

Full text: 1 Database: VETINDEX Main subject: Image Processing, Computer-Assisted / Software / Soil Analysis / Soil Characteristics / Porosity Language: En Journal: Sci. agric / Sci. agric. Year: 2016 Document type: Article