The Australian soil texture boomerang: a comparison of the Australian and USDA/FAO soil particle-size classification systems

Soil Research ◽  
2001 ◽  
Vol 39 (6) ◽  
pp. 1443 ◽  
Author(s):  
Budiman Minasny ◽  
Alex. B. McBratney

The different classification of particle-size fractions used in Australia compared with other countries presents a problem for the immediate adoption of the exotic pedotransfer functions. Australia adopted the international system which defined silt as particles with diameters in the range 2–20 m, while the USDA/FAO define it as 2–50 m. We present empirical equations to convert between the two systems. The USDA/FAO textural classes were also plotted in the International system’s coordinate. The USDA/FAO classes in the International system had a ‘boomerang’ shape and only occupy 60% of the triangle. Particle-size data showed that the data are evenly distributed in the USDA/FAO triangle, while most data are concentrated in the boomerang in the International system. We therefore suggest that it would seem wise for most countries to consider adopting the particle-size limits and texture classes of the USDA/FAO system.

2017 ◽  
Vol 68 (5) ◽  
pp. 769-782 ◽  
Author(s):  
A. Makó ◽  
G. Tóth ◽  
M. Weynants ◽  
K. Rajkai ◽  
T. Hermann ◽  
...  

Soil Research ◽  
2012 ◽  
Vol 50 (6) ◽  
pp. 443 ◽  
Author(s):  
José Padarian ◽  
Budiman Minasny ◽  
Alex McBratney

The difference between the International (adopted by Australia) and the USDA/FAO particle-size classification systems is the limit between silt and sand fractions (20 μm for the International and 50 µm for the USDA/FAO). In order to work with pedotransfer functions generated under the USDA/FAO system with Australian soil survey data, a conversion should be attempted. The aim of this work is to improve prior models using larger datasets and a genetic programming technique, in the form of a symbolic regression. The 2–50 µm fraction was predicted using a USDA dataset which included both particle-size classification systems. The presented model reduced the root mean square error (%) by 14.96 and 23.62% (IGBP-DIS dataset and Australian dataset, respectively), compared with the previous model.


2014 ◽  
Vol 50 (6) ◽  
pp. 5298-5308 ◽  
Author(s):  
Monica Riva ◽  
Xavier Sanchez-Vila ◽  
Alberto Guadagnini

Author(s):  
N. R. J. Fieller ◽  
E. C. Flenley ◽  
W. Olbricht

Soil Research ◽  
2007 ◽  
Vol 45 (6) ◽  
pp. 428 ◽  
Author(s):  
Budiman Minasny ◽  
Alex B. McBratney ◽  
Damien J. Field ◽  
Grant Tranter ◽  
Neil J. McKenzie ◽  
...  

This paper aims to establish the means and ranges of clay, silt, and sand contents from field texture classes, and to investigate the differences in the field texture classes and texture determined from particle-size analysis. The results of this paper have 2 practical applications: (1) to estimate the particle size distribution and its uncertainty from field texture as input to pedotransfer functions, and (2) to examine the criteria of texture contrast soils in the Australian Soil Classification system. Estimates of clay, silt, and sand content for each field texture class are given and this allows the field texture classes to be plotted in the texture triangle. There are considerable differences between field texture classes and particle-size classes. Based on the uncertainties in determining the clay content from field texture, we establish the probability of the occurrence of a texture contrast soil according to the Australian Soil Classification system, given the texture of the B2 horizon and its overlying A horizon. I enjoy doing the soil-texture feel test with my fingers or kneading a clay soil, which is a short step from ceramics or sculpture. Hans Jenny (1984)


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