Date of Award

1998

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

School of Nutrition and Food Sciences

First Advisor

Ronald H. Gough

Abstract

Raw milk samples (n = 246) and pasteurized milk samples (n = 104) were analyzed to determine adenosine triphosphate (ATP) and compared with the standard plate count (SPC). An ATP filtration method was used to filter milk samples prior to ATP determination, which was measured in relative light units (RLU). The ATP assay took approximately 7 minutes to complete and could allow rapid prediction of SPC which is a measure of raw milk quality. Linear regression analysis was performed on data from three raw milk treatments defined as; fresh milk samples, samples preliminarily incubated at 12.8 and 15.6$\sp\circ$C for 18 hours. Linear regression coefficients were significantly different from zero (P $<$ 0.01). The R$\sp2$ calculated using log$\sb{10}$ transformed SPC (LSPC) and log$\sb{10}$ RLU (LRLU) for fresh and preliminarily incubated samples at 12.8 and 15.6$\sp\circ$C were 0.58, 0.78, and 0.80, respectively and R$\sp2$ for all milk samples combined was 0.78. Differences in regressions among treatments were tested using a multiple slope and intercept model. The R$\sp2$ for the multiple slope model was 0.83 and the treatment intercepts and slopes were significantly different (P $<$ 0.01). Analysis of predicted values of LSPC and one standard deviation of a single prediction above and below the regression line indicated that SPC could be predicted with sufficient accuracy using ATP in raw milk samples. Pasteurized milk samples were subjected to two preliminary incubation temperatures: 12.8 and 15.6$\sp\circ$C for 18 hours. All of the 104 fresh pasteurized milk samples had a SPC count below 10$\sp4$ cfu/ml. Regression analyses as described for raw milk samples revealed that preliminary incubation at 15.6$\sp\circ$C for 18 hours did not result in a significant increase in the standard plate count of the same samples. The ATP method was not effective in predicting bacterial numbers of freshly pasteurized milk or PI-15.6$\sp\circ$C milk samples using linear regression. However, the SPC and RLU values increased for PI-21$\sp\circ$C pasteurized milk and the regression analyses revealed that there was a linear relationship between LSPC and LRLU for PI-21$\sp\circ$C samples.

ISBN

9780591998016

Pages

84

DOI

10.31390/gradschool_disstheses.6758

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