Proposition and analysis of methods for determining the porosity of crystalline organogel solutions from micrographs

• Grant number: 23/04173-9
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2023
• End date: June 30, 2025
• Field of knowledge: Agronomical Sciences - Food Science and Technology - Food Engineering
• Principal Investigator: Ana Carolina Conti
• Grantee: Guilherme Broggio Sandoli
• Host Institution: Instituto de Biociências, Letras e Ciências Exatas (IBILCE). Universidade Estadual Paulista (UNESP). Campus de São José do Rio Preto. São José do Rio Preto , SP, Brazil

Abstract

The structuration of vegetable oils by using low concentrations of vegetable and animal waxes, forming organogels, is calling the attention of the food industry. These organogels are formation developed due to of a homogeneous colloidal dispersion of wax crystals, once the structuration is related to the crystal-crystal and crystal-liquid interactions. One of the most carried out analyses to study and comprehend organogels is the optical microscopy with polarized light that allows to observe the crystals morphology, dispersion, and crystals homogeneity in the solution. From the analysis of the micrographs, it may be possible to obtain the volume not filled with crystals, called porosity. These results may be related, for instance, with oil migration, crystal morphology, and crystallinity, to achieve more relevant and robust results of the research. On the other hand, although some articles have already reported results, there is no standard methodology to determine the porosity through micrographs of crystalline organogels. Therefore, the objective of this project is to validate and propose robust and practical methods to determine the porosity of candelila wax and rice wax in soy oil organogels at concentrations of 1 to5 % (w/w) through analysis of micrograph using ImageJ and algorithm of own authorship in Matlab. For this, we propose i) to determine which automatic methods present in ImageJ are the best for image conversion, ii) to use trained analysts to manually convert images in ImageJ and iii) to develop an algorithm in Matlab capable of converting the micrographs and determine the porosity of the solutions in a similar way to ImageJ.