Size characterization of selected food powders by five particle size distribution functions

The properties of a food particulate system are highly dependent on its particle size distribution. The knowledge of this distribution is essential to the analysis of the handling, processing, and functionality of the food powder. Properly selected distribution functions are excellent tools with which to simplify and accurately describe the particle size distribution. The objectives of this study were to identify appropriate distribution functions for characterizing the particle size distribution of selected food powders. Granular sugar, corn meal and instant non-fat milk powder were classified into six or seven particle size cuts for each powder. The experimental data were fitted by five particle size distribution functions: (i) Gates-Gaudin-Schuhmann (GGS); (ii) Rosin-Rammler (RR); (iii) Modified Gaudin-Meloy (MGM); (iv) Log-normal (LN); and (v) modified beta (MB). These models were selected for their mathematical simplicity, adequate statistical properties and usefulness in describing other particulate systems similar to the food powders under consideration. In all cases, it was found that the RR and MGM models were the best for the characterization of all food powders considered, the LN and MB were best for sugar, and the GGS was suitable for corn meal. All five models should be considered for characterizing other food powder particle size distributions because all of them offer enough flexibility to properly describe particle size distributions for different types of food powders.