Developing an optical backscatter method for determining casein micelle particle size in heated milk
A plethora of different factors, such as heat treatment, pH, soluble calcium and phosphate concentrations, colloidal calcium phosphate, ionic strength, redox potential, etc., affect functionally of critical milk components such as casein micelles, fat globules and whey proteins. These physicochemica...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:265287 |
| Acceso en línea: | https://ddd.uab.cat/record/265287 https://dx.doi.org/urn:doi:10.1016/j.foodres.2022.111745 |
| Access Level: | acceso abierto |
| Palabra clave: | Casein micelle size Whey protein denaturation Process monitoring Optical sensor Near infrared spectroscopy Milk In-line |
| Sumario: | A plethora of different factors, such as heat treatment, pH, soluble calcium and phosphate concentrations, colloidal calcium phosphate, ionic strength, redox potential, etc., affect functionally of critical milk components such as casein micelles, fat globules and whey proteins. These physicochemical changes induce fat- or protein-protein interactions that would be associated to changes in particle size that might be revealed using light backscatter measurements. We hypothesized that inline, simple, low-cost light backscatter measurements might have the potential to provide functionally related information, representing an interesting opportunity for process control. Casein micelle particle size and near infrared light backscatter spectra were measured in milks heat treated at 80 and 90 °C and pH 6.3, 6.7 and 7.1 in order to obtain prediction models for estimating changes in casein micelle particle size during milk heat treatment. Light intensity was measured over a spectral range of 200-1100 nm using a simple optical backscatter sensor and was implemented into models for particle size predictions as a function of heat treatment temperature and pH. Models which included an exponential factor containing a ratio of two specific wavebands were found to improve R when compared to single wavelength models. The best model exhibited an R of 0.993 and SEP of 2.36 nm. The developed prediction models show promise for in-line monitoring of whey protein denaturation and casein micelle particle size. |
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