Modelling bacterial spoilage in cold-filled ready to drink beverages by Acinetobacter calcoaceticus and Gluconobacter oxydans.
OBJECTIVE
Mathematical models were created which predict the growth of spoilage bacteria in response to various preservation systems.


RESULTS
A Box-Behnken design included five variables: pH (2.8, 3.3, 3.8), titratable acidity (0.20%, 0.40%, 0.60%), sugar (8.0, 12.0, 16.0 * Brix), sodium benzoate concentration (100, 225, 350 ppm), and potassium sorbate concentration (100, 225, 350 ppm). Duplicate samples were inoculated with a bacterial cocktail (100 microl 50 ml(-1)) consisting of equal proportions of Acinetobacter calcoaceticus and Gluconobacter oxydans (5 x 10(5) cfu ml(-1) each). Bacteria from the inoculated samples were enumerated on malt extract agar at zero, one, two, four, six, and eight weeks.


CONCLUSIONS
The pH, titratable acidity, sugar content, sodium benzoate, and potassium sorbate levels were all significant factors in predicting the growth of spoilage bacteria.


CONCLUSIONS
This beverage spoilage model can be used to predict microbial stability in new beverage product development and potentially reduce the cost and time involved in microbial challenge testing.
Battey
A S
AS
Food Risk Analysis Initiative, Rutgers, The State University of New Jersey, New Brunswick, 08901-8520, USA.
Schaffner
D W
DW
D000150:Acinetobacter / Q000187:drug effects / Q000254:growth & development* / Q000378:metabolism; D001628:Beverages / Q000382:microbiology*; D002241:Carbohydrates / Q000032:analysis; D003080:Cold Temperature; D005516:Food Microbiology; D005519:Food Preservation; D020600:Gluconobacter oxydans / Q000187:drug effects / Q000254:growth & development* / Q000378:metabolism; D006863:Hydrogen-Ion Concentration; D008954:Models, Biological; D015203:Reproducibility of Results; D020160:Sodium Benzoate / Q000494:pharmacology; D013011:Sorbic Acid / Q000494:pharmacology; D017186:Titrimetry
D002241:Carbohydrates; D020160:Sodium Benzoate; D013011:Sorbic Acid