Infusion pasteurization of whole milk and skim milk: Influence on viscosity and particle size

Infusion pasteurization was performed on both whole milk and skim milk and at different temperatures in the range 72°C-120°C. The skim milk was prepared at a commercial dairy and had been heated to approx. 60°C during the separation process. The whole milk was skimmed by centrifugation prior to the analyses. In the analyses, the infusion pasteurized samples were compared to a standard low pasteurization on the same batches of milk and samples of the raw milks. Particle sizes were analyzed using dynamic light scattering, and the viscosity of the samples were measured with a capillary viscometer. The viscosity measurements showed no significant changes in viscosity after infusion pasteurization of skim milk, nor did the particle sizes change. On the other hand, when whole milk was infusion pasteurized an increase in viscosity of the skim milk fraction was seen as treatment temperature increased, and an increase in the z-average diameter of particles and broadening of the size distributions was observed. These observations were quite surprising and might be the result of influence of several different processes during and after infusion pasteurization

Probabilistic Modelling of Liquid Chromatography Time-of-Flight Mass Spectrometry

Liquid Chromatography Time-of-Flight Mass Spectrometry (LC-TOFMS) is an analytical platform that is widely used in the study of biological mixtures in the rapidly growing fields of proteomics and metabolomics. The development of statistical methods for the analysis of the very large data-sets that are typically produced in LC-TOFMS experiments is a very active area of research. However, the theoretical basis on which these methods are built is currently rather thin and as a result, inferences regarding the samples analysed are generally drawn in a somewhat qualitative fashion. This thesis concerns the development of a statistical formalism that can be used to describe and analyse the data produced in an LC-TOFMS experiment. This is done through the derivation of a number of probability distributions, each corresponding to a different level of approximation of the distribution of the empirically obtained data. Using such probabilistic models, statistically rigorous methods are developed and validated which are designed to address some of the central problems encountered in the practical analysis of LC-TOFMS data, most notably those related to the identification of unknown metabolites. Unlike most existing bioinformatics techniques, this work aims for rigour rather than generality. Consequently the methods developed are closely tailored to a particular type of TOF mass spectrometer, although they do carry over to other TOF instruments, albeit with important restrictions. And while the algorithms presented may constitute useful analytical tools for the mass spectrometers to which they can be applied, the broader implications of the general methodological approach that is taken are also of central importance. In particular, it is arguable that the main value of this work lies in its role as a proof-of-concept that detailed probabilistic modelling of TOFMS data is possible and can be used in practice to address important data analytical problems in a statistically rigorous manner

Infusion pasteurization of skim milk: Effects of different time-temperature combinations

Infusion pasteurization technology was used in different time-temperature combinations for heat treatment of skim milk and compared to untreated skim milk and a standard pasteurization treatment. Aerobic count of microorganisms and activity of alkaline phosphatase showed that all infusion-pasteurized samples had received proper pasteurization. There were no difference in the size of casein micelles, but differences were seen in activity of the enzyme xanthine oxidase. The results indicate possible differences in properties of infusion-pasteurized skim milk compared to standard pasteurized skim milk