Application of multivariate statistical methods in the assessment of mountain organic soil transformation in the central Sudetes

Bogna Zawieja, and Bartłomiej Glina. "Application of multivariate statistical methods in the assessment of mountain organic soil transformation in the central Sudetes." Biometrical Letters 54.1 (2017): 43-59. <http://eudml.org/doc/288507>.

@article{BognaZawieja2017,
abstract = {In studies of organic soil degradation and transformation, alongside the conventional methods used in soil science, an increase in the importance of advanced statistical methods can be observed. In this study some multivariate statistical methods were applied in an investigation of organic soil transformation in the central Sudetes. Andrews curves, linear and kernel discriminant variable analysis and cluster analysis were used. The similarities among peatland soils and their layers were determined. It can be stated that the application of statistical methods in soil science research related to organic soil transformation is a valuable tool. The use of various statistical methods (such as Andrews curves, linear and kernel discriminant variables and cluster analysis) can with high probability confirm earlier laboratory or field observations. This is particularly justified in the case of organic soils derived from varied geobotanical peat materials, different types of peatlands and water supply types, which impact the primary properties of the soil.},
author = {Bogna Zawieja, Bartłomiej Glina},
journal = {Biometrical Letters},
keywords = {Andrews curves; degradation; kernel discriminant analysis; linear discriminant analysis; mountain peatlands},
language = {eng},
number = {1},
pages = {43-59},
title = {Application of multivariate statistical methods in the assessment of mountain organic soil transformation in the central Sudetes},
url = {http://eudml.org/doc/288507},
volume = {54},
year = {2017},
}

TY - JOUR
AU - Bogna Zawieja
AU - Bartłomiej Glina
TI - Application of multivariate statistical methods in the assessment of mountain organic soil transformation in the central Sudetes
JO - Biometrical Letters
PY - 2017
VL - 54
IS - 1
SP - 43
EP - 59
AB - In studies of organic soil degradation and transformation, alongside the conventional methods used in soil science, an increase in the importance of advanced statistical methods can be observed. In this study some multivariate statistical methods were applied in an investigation of organic soil transformation in the central Sudetes. Andrews curves, linear and kernel discriminant variable analysis and cluster analysis were used. The similarities among peatland soils and their layers were determined. It can be stated that the application of statistical methods in soil science research related to organic soil transformation is a valuable tool. The use of various statistical methods (such as Andrews curves, linear and kernel discriminant variables and cluster analysis) can with high probability confirm earlier laboratory or field observations. This is particularly justified in the case of organic soils derived from varied geobotanical peat materials, different types of peatlands and water supply types, which impact the primary properties of the soil.
LA - eng
KW - Andrews curves; degradation; kernel discriminant analysis; linear discriminant analysis; mountain peatlands
UR - http://eudml.org/doc/288507
ER -