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Volume 114
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Validation of soil particle size and shape distributions in particle image analysis using convergence analysis
Daisuke Sasakura a *, Sho Kimura b
a Malvern Panalytical, A Division of Spectris Co., Ltd., Daiichi Building 7-3, Hamamatsucho 1-Chome, Minato-ku, Tokyo, 105-0013, Japan
b Department of Regional Agricultural Engineering, Faculty of Agriculture, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan
10.1016/j.partic.2026.04.015
Volume 114, July 2026, Pages 256-269
Received 26 October 2025, Revised 17 April 2026, Accepted 26 April 2026, Available online 1 May 2026, Version of Record 9 May 2026.
E-mail: daisuke.sasakura@malvernpanalytical.com
Highlights

• Development of a new comprehensive particle morphology verification method.

• Performed automated particle image analysis (APIA) targeting on soil samples.

• APIA enables rapid, quantitative particle shape analysis across large datasets.

• The study proposes a convergence-based method to validate APIA particle counts.

• This simple, low-cost approach improves reliability in soil and material sciences.


Abstract

Evaluating soil particle morphology (i.e. shape and size) is vital in geology and geophysics, as the morphology controls properties such as shear strength, permeability, density, and friction. In coarse-grained soils, force chains affect the loading capacity and deformation, whereas particle orientation in silty soils influences their mechanical behaviour. Particle size and shape measurements typically combine laser diffraction (LD) and image analysis (IA). LD is fast but does not obtain shape data, whereas IA produces detailed results but is labour-intensive. Automated particle IA (APIA) can rapidly acquire diverse shape information; however, determining particle counts for statistical reliability and verifying their validity are challenging, as particle size and shape are multivariate. Although conventional simulation-based approaches can be used to evaluate these characteristics, such methods are often computationally intensive and may produce results the deviate from those of real samples. In this study, we propose a convergence parameter-based method to validate the particle counts obtained using APIA directly from physical measurements. This method is sample-independent, inexpensive, and uses intuitive calculations. The degree of convergence allows for comparisons across and within samples, thereby providing quantitative and qualitative verification without large-scale computation. This approach leverages the strengths of APIA to improve the reliability and performance of particle morphology characterisation in the broader fields of material and soil sciences.

Graphical abstract
Keywords
Particle size; Particle shape; Particle image analysis; Particle morphology
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