Mayonnaise observation and label-free analysis of oil droplet particle size distribution using AI
Emulsification technology is used in a wide range of industrial fields, including the manufacture of mayonnaise, margarine, and cosmetic creams. Mayonnaise is an oil-in-water (O/W) type emulsion in which lecithin and lipoprotein contained in egg yolk act as emulsifiers, and oil is dispersed in the aqueous phase. Since droplet size affects the taste of foods and the long-term stability of emulsions, particle size distribution analysis of droplets and observation of membranes are performed during emulsifier development and stability testing. Although droplets can be observed with transmitted light, in bright-field images the contrast between droplets and their background is low, making it difficult to identify droplet regions by conventional binarization methods based on intensity values. This application note introduces a label-free observation method for droplets, and an example of particle size distribution analysis of mayonnaise by identifying droplets using the deep learning-based Segment.ai module.