title: Validation of extrusion as a killing step for Enterococcus faecium in a balanced carbohydrate-protein meal by using a response surface design.
abstract: Outbreaks of salmonellosis and recalls of low-moisture foods including extruded products highlight the need for the food and feed industries to validate their extrusion processes to ensure the destruction of pathogenic microorganisms. Response surface methodology was employed to study  the effect of moisture and temperature on inactivation by extrusion of Enterococcus faecium NRRL B-2354 in a carbohydrate-protein mix. A balanced carbohydrate-protein mix was formulated to different combinations of moisture contents, ranging from 24.9 to 31.1%, and each was inoculated  with a pure culture of E. faecium to a final level of 5 log CFU/g. Each mix of various moistures was then extruded in a pilot scale extruder at different temperatures (ranging from 67.5 to 85°C). After the extruder was allowed to equilibrate for 10 min, samples were collected in  sterile bags, cooled in dry ice, and stored at 4°C prior to analysis. E. faecium was enumerated with tryptic soy agar and membrane Enterococcus media, followed by incubation at 35°C for 48 h. Each extrusion was repeated twice, with the central point of the design being  repeated four times. From each extrusion, three subsamples were collected for microbial counts and moisture determination. Based on the results, the response surface model was y = 185.04 - 3.11X(1) - 4.23X(2) + 0.02X(1)(2)  - 0.004X(1)X(2) + 0.08X(2)(2), with a good fit (R(2) = 0.92), which demonstrated the effects of moisture and temperature on the inactivation of E. faecium during extrusion. According to the response surface  analysis, the greatest reduction of E. faecium for the inoculation levels studied here (about 5 log) in a carbohydrate-protein meal would occur at the temperature of 81.1°C and moisture content of 28.1%. Other temperature and moisture combinations needed to achieve specific log  reductions were plotted in a three-dimensional response surface graph.
authors.affiliation: The Food Processing Center, University of Nebraska, Lincoln, Nebraska 68588, USA. abianchini2@unl.edu
authors.forename: Andreia
authors.initials: A
authors.lastname: Bianchini
authors.forename: Jayne
authors.initials: J
authors.lastname: Stratton
authors.forename: Steve
authors.initials: S
authors.lastname: Weier
authors.forename: Timothy
authors.initials: T
authors.lastname: Hartter
authors.forename: Brian
authors.initials: B
authors.lastname: Plattner
authors.forename: Galen
authors.initials: G
authors.lastname: Rokey
authors.forename: Gerry
authors.initials: G
authors.lastname: Hertzel
authors.forename: Lakshmi
authors.initials: L
authors.lastname: Gompa
authors.forename: Bismarck
authors.initials: B
authors.lastname: Martinez
authors.forename: Andkent M
authors.initials: AM
authors.lastname: Eskridge
mesh_terms: D055598:Chemical Phenomena; D002627:Chemistry, Physical; D015169:Colony Count, Microbial; D013293:Enterococcus faecalis / Q000254:growth & development*; D005511:Food Handling / Q000379:methods*; D019649:Food Industry; D005516:Food Microbiology; D012995:Solubility; D013696:Temperature; D014783:Viscosity; D014867:Water / Q000032:analysis*
chemical_list: D014867:Water