Comparison of Methods to Explore the Morphology and Granulometry of Biological Particles with Complex Shapes: Interpretation and Limitations

The particle size and morphology of the particles represent key factors that significantly influence the physicochemical properties of biological materials and suspensions, the transport phenomena inside the bioreactors and consequently the bioperformances. Many in-situ and ex-situ techniques are used to characterize the distribution functions of these properties. However, each method has its own advantages and disadvantages in defined conditions, and some differences may exist between methods resulting in variations and deviations of morphological measurements. This article aims to compare five different techniques (morphogranulometry MG, laser light diffraction LLD, flow cytometry CYT, settling velocity TSL, and focused beam reflectance measurement FBRM) used to characterize the morphology and granulometry of biological matrices with increasing complexity (model spherical particles, elongated yeast cells, and complex lignocellulosic substrates). The results and their interpretations highlighted several critical and limiting points: principles of measurement, technological and metrological specifications, identification of relevant parameters (diameter, shape), choice of distribution functions (number, volume), and statistical comparisons of populations. The results and their interpretations pointed out several critical points and limitations: principles of measurement, technological and metrological specifications, identification of pertinent parameters (diameter, shape), choice of distribution functions (number, volume), and statistical comparisons of populations. Granulometric methods may hide the complexity of diameter definitions. Examining shape parameters is richer than granulometry, and more complex descriptors (length, width, aspect ratio …) could be addressed. However, all these techniques enable to describe and interpret the observed phenomena (dimorphism, enzymatic hydrolysis) considering either absolute or relative data.