Articles
Computerized particle analyzer: the next generation of particle analysis
Article number
1266_14
Pages
97 – 102
Language
English
Abstract
The characteristics of any substrate material can be attributed to its composition of particle characteristics.
Sieve analysis is one of the most basic tests for fractioning particle sizes and the predominate method utilized for horticultural substrate characterization.
However, sieve analysis is noted for its poor reproducibility and lack of valuable information.
To better quantify particle shape and size, the Computer Particle Analyzer II (CPA) by W.S. Tyler Group was evaluated for its potential use in substrate science.
The CPA was found to be approximately 97% accurate in both particle counts and dimensional measurements after calibration.
Touching particles and particle oscillation across the measurement zone are believed to account for the error incurred during analysis.
To validate the CPA’s analysis, coarse, medium, and fine horticultural sands were analyzed and compared to traditional sieve analysis.
Distribution error was calculated using the Chi-Square method, mean standard error, and a complex error term using the bin size and percent composition.
Some error was recorded in the CPA’s analysis of each sand.
This highlights the variability that may occur when calculating particle volumes from 2-D image analysis.
The 2-D characterization, accuracy, and customization of the CPA and its accompanying software can provide valuable data to more fully characterize substrate particle shape and size.
Sieve analysis is one of the most basic tests for fractioning particle sizes and the predominate method utilized for horticultural substrate characterization.
However, sieve analysis is noted for its poor reproducibility and lack of valuable information.
To better quantify particle shape and size, the Computer Particle Analyzer II (CPA) by W.S. Tyler Group was evaluated for its potential use in substrate science.
The CPA was found to be approximately 97% accurate in both particle counts and dimensional measurements after calibration.
Touching particles and particle oscillation across the measurement zone are believed to account for the error incurred during analysis.
To validate the CPA’s analysis, coarse, medium, and fine horticultural sands were analyzed and compared to traditional sieve analysis.
Distribution error was calculated using the Chi-Square method, mean standard error, and a complex error term using the bin size and percent composition.
Some error was recorded in the CPA’s analysis of each sand.
This highlights the variability that may occur when calculating particle volumes from 2-D image analysis.
The 2-D characterization, accuracy, and customization of the CPA and its accompanying software can provide valuable data to more fully characterize substrate particle shape and size.
Publication
Authors
P.C. Bartley, B.E. Jackson, W.C. Fonteno
Keywords
image analysis, substrate, growing media, particle size distribution, physical properties
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