The Ways to Develop Soil Textural Classification for Laser Diffraction Method
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The Ways to Develop Soil Textural Classification for Laser Diffraction Method A. V. Yudinaa, *, D. S. Fomina, I. A. Valdes-Korovkina, b, N. A. Churilina, M. S. Aleksandrovab, c, Yu. A. Golovlevab, N. V. Phillipovd, I. V. Kovdaa, A. A. Dymove, and E. Yu. Milanovskiya, b aDokuchaev
Soil Science Institute, per. Pyzhevskii 7, Moscow, 119017 Russia Lomonosov Moscow State University, Leninskie gory, Moscow, 119991 Russia c Izrael Institute of Global Climate and Ecology, Moscow, 107258 Russia d Institute for Biological Problems of the Cryolithozone, Siberian Branch of the Russian Academy of Sciences, Yakutsk, 677007 Russia e Institute of Biology, Komi Science Center, Ural Branch of the Russian Academy of Science, Syktyvkar, Komi Republic, 167982 Russia *e-mail: [email protected] b
Received December 4, 2019; revised January 30, 2020; accepted April 24, 2020
Abstract—The existing classifications of soil texture are based on the sedimentation data. The aim of this article is to consider the ways to develop soil textural classification on the basis of particle-size distribution (PSD) data obtained by the laser diffraction method. A detailed comparison of PSD data obtained by the classical pipette method and the method of laser diffractometry has been performed. We have shown the reproducibility of the laser diffraction method and the effect of the oxidation stage on the soil texture class. This study is based on eight genetic soil types (overall, 32 full-profile soil pits) forming a zonal soil sequence from Podzols (Subpolar Urals) to ferrallitic soil (southwest Oceania) and differing in their mineralogical compositions, textures, and elementary pedogenetic processes. The direct use of the Kachinskii and USDA classifications with the data of the laser diffraction method leads to mistakes in determining the soil texture class in 43 and 65% of cases, respectively. The increasing complexity of recalculation, introduction of new variables, and accounting for interlaboratory errors allow us to determine correctly the texture class according to the Kachinskii and USDA classifications in no more than 70 and 72% of soil samples, respectively. The most simple and effective approach to solve the classification problem for the laser diffraction method is to calibrate existing classifications directly on the basis of data on soil samples, for which the texture class was determined by the field method. Keywords: Kachinskii classification, USDA classification, soil texture, soil sample preparation, ultrasound dispersion DOI: 10.1134/S1064229320110149
INTRODUCTION Particle-size distribution (PSD) is the most common quantitative physical characteristic describing the dispersity of soils for their diagnosis and classification and for solving many applied problems. The most common approaches to describing soil PSD are the sedimentation and the laser diffraction (LD) methods. There are a number of soil textural classifications for the first group of methods, but the classifications based on LD have not been developed so far. This f
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