loading page

Particle Size Distribution of Growing Media Constituents Using Dynamic Image Analysis: Parametrization and Comparison to Sieving
  • +1
  • Stan Durand,
  • William Fonteno,
  • Brian Jackson,
  • Jean-Charles Michel
Stan Durand
L'Institut Agro Rennes-Angers - Campus d'Angers

Corresponding Author:[email protected]

Author Profile
William Fonteno
NC State University College of Agriculture and Life Sciences
Author Profile
Brian Jackson
NC State University College of Agriculture and Life Sciences
Author Profile
Jean-Charles Michel
L'Institut Agro Rennes-Angers - Campus d'Angers
Author Profile

Abstract

Growing media constituents have heterogeneous particle size and shape, and their physical properties are partly related to them. Particle size distribution is usually analyzed through sieving process, segregating the particles by their width. However, sieving techniques are best describing more granular shapes and are not as reliable for materials exhibiting large varieties of shapes, like growing media constituents. A dynamic image analysis has been conducted for a multidimensional characterization of particle size distribution of several growing media constituents (white and black peats, pine bark, coir, wood fiber, and perlite), from particles that were segregated and dispersed in water. Diameters describing individual particle width and length were analyzed, then compared to particle size distribution obtained by sieving DM and HM methods. This work suggests the relevance of two parameters, Feret MAX and Chord MIN diameters for assessing particle length and width, respectively. They largely varied among the growing media constituents, confirming their non-spherical (i.e. elongated) shapes, demonstrating the advantages in using dynamic image analysis tools over traditional sieving methods. Furthermore, large differences in particle size distribution were also observed between dynamic image analysis and sieving procedures, with a finer distribution for dynamic image analysis. The discrepancies observed between methodologies were discussed (particle segregation, distribution weighing, etc.), while describing in details methodological limitations of dynamic image analysis.
14 Sep 2022Submitted to Soil Science Society of America
15 Sep 2022Submission Checks Completed
15 Sep 2022Assigned to Editor
15 Sep 2022Review(s) Completed, Editorial Evaluation Pending
18 Sep 2022Reviewer(s) Assigned
05 Nov 2022Editorial Decision: Revise Minor
22 Nov 20221st Revision Received
22 Nov 2022Review(s) Completed, Editorial Evaluation Pending
22 Nov 2022Submission Checks Completed
22 Nov 2022Assigned to Editor
22 Nov 2022Reviewer(s) Assigned
13 Dec 2022Editorial Decision: Revise Minor
20 Dec 2022Review(s) Completed, Editorial Evaluation Pending
20 Dec 20222nd Revision Received
29 Dec 2022Assigned to Editor
29 Dec 2022Submission Checks Completed
29 Dec 2022Editorial Decision: Accept