S06 - Session O6 - Advances in substrate particle characterization using dynamic image analysis for predicting water retention properties.

Authors: Stan Durand *, Brian Jackson , William Fonteno , Jean-Charles Michel

Water/air retention and flow properties in horticultural substrates depend on pores which are created by particle arrangement and particle morphology. Manufacturers mainly select substrate components based on particle size determined through sieving processes. However, sieving methods are most suitable to characterize granular materials (with 1:1 length/width ratio). Particle size distribution of substrate components may be improperly assessed due to their much larger diversity of particle morphology (fibers, plates, etc.). Particle width and shape of numerous substrate components (white and black peats, bark, wood fiber, perlite, compost) were measured using dynamic image analysis, and compared with the mean particle size determined from the EN15428 sieving method. Dynamic image analysis showed much smaller mean particle width in comparison to sieving. It also provided additional information about particle length, confirming the non-granular shape of most of substrate components. Relationships between particle morphology and water holding capacity were explored. A strong correlation was observed between mean particle length and water holding capacity. This work reports the strong interest to deeply investigate particle morphology using dynamic image analysis for predicting physical properties.