Novel uses of attenuated total reflectance infrared microspectroscopy combined with multivariate analysis in food processing
The overall objective of this thesis was to demonstrate the application of attenuated total reflectance infrared microspectroscopy (ATR-IRMS) combined with multivariate analysis (soft independent modeling of class analogy) as a rapid, simple and robust analytical technique to obtain more insight whe...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Rovira i virgili (URV) |
| Repositorio: | Repositori Institucional de la Universitat Rovira i Virgili |
| OAI Identifier: | oai:urv.cat:TDX:1213 |
| Acceso en línea: | https://hdl.handle.net/20.500.11797/TDX1213 http://hdl.handle.net/10803/119557 |
| Access Level: | acceso abierto |
| Palabra clave: | 66 - Enginyeria, tecnologia i indústria química. Metal·lúrgia |
| Sumario: | The overall objective of this thesis was to demonstrate the application of attenuated total reflectance infrared microspectroscopy (ATR-IRMS) combined with multivariate analysis (soft independent modeling of class analogy) as a rapid, simple and robust analytical technique to obtain more insight when several emerging technologies are applied to produce food emulsions or inactivate microorganisms. In the first part of the thesis, ATR-IRMS was used to detect if whey protein was involved on the fouling phenomena detected to membrane surfaces used to produce sunflower oil and water emulsions. This technique was also evaluated to easily detect which cleaning protocol used to reduce the fouling was the most effective between those tasted. In the second part of the thesis, ATR-IRMS combined with multivariate analysis was the key technique to detect the E. coli O157:H7 cell structures mainly affected by heat and pulsed electric fields treatments applied at pH 4.0 and 7.0. Calibration models were built up with the IR data and E. coli O157:H7 log cycles of inactivation showing good correlation and potential to be used to predict injured bacteria. |
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