Predictions of some product parameters based on the processing conditions of ultra-high-temperature milk plants

Full text for this resource is not available from the Research Repository.

Tran, H, Datta, Nivedita, Lewis, M. J and Deeth, H. C (2008) Predictions of some product parameters based on the processing conditions of ultra-high-temperature milk plants. International Dairy Journal, 18 (9). pp. 939-944. ISSN 0958-6946

Abstract

The temperature–time profiles of 22 Australian industrial ultra-high-temperature (UHT) plants and 3 pilot plants, using both indirect and direct heating, were surveyed. From these data, the operating parameters of each plant, the chemical index C*, the bacteriological index B* and the predicted changes in the levels of β-lactoglobulin, α-lactalbumin, lactulose, furosine and browning were determined using a simulation program based on published formulae and reaction kinetics data. There was a wide spread of heating conditions used, some of which resulted in a large margin of bacteriological safety and high chemical indices. However, no conditions were severe enough to cause browning during processing. The data showed a clear distinction between the indirect and direct heating plants. They also indicated that degree of denaturation of α-lactalbumin varied over a wide range and may be a useful discriminatory index of heat treatment. Application of the program to pilot plants illustrated its value in determining processing conditions in these plants to simulate the conditions in industrial UHT plants.

Item type Article
URI https://vuir.vu.edu.au/id/eprint/4006
Official URL http://www.sciencedirect.com/science/article/pii/S...
Subjects Historical > FOR Classification > 0908 Food Sciences
Historical > Faculty/School/Research Centre/Department > School of Biomedical and Health Sciences
Keywords ResPubID17936. product parameters, operating parameters, milk processing, UHT milk, UHT milk plants, ultra-high temperatures
Citations in Scopus 23 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login