P3-36 The Effect of Pear Firmness on the Transfer of Salmonella during Mechanical Slicing

Wednesday, July 12, 2017
Exhibit Hall (Tampa Convention Center)
Hamoud Alnughaymishi , Michigan State University , East Lansing , MI
Elliot Ryser , Michigan State University , East Lansing , MI
Introduction: Numerous studies have examined the extent of microbial cross-contamination during preparation of fresh-cut produce, however few investigators have assessed the impact of specific processing parameters on pathogen transfer.

Purpose: This study aimed to evaluate the impact of pear firmness on transfer of Salmonella during mechanical slicing.

Methods: Locally purchased pears were categorized as firm (54 to 60 N), medium (31 to 42 N) or soft (<31 N) based on force measurements from a texture analyzer equipped with an eight mm diameter probe. The desired firmness was achieved by incubating the pears at 20°C for no more than 72 h. Pears were individually dip-inoculated with a three-strain Salmonella cocktail (Montevideo, Poona, Newport) at ~ five log CFU/cm2 and then air-dried for one hour. Thereafter, one pear was sliced to contaminate the NEMCO vertical slicer followed by 15 uninoculated pears. Three slices per pear were homogenized by stomaching, appropriately diluted and surface plated on trypticase soy agar with yeast extract containing 0.05% ferric ammonium citrate and 0.03% sodium thiosulfate to enumerate healthy and injured Salmonella.

Results: Based on triplicate experiments, samples from the 1st , 9th, and 15th firm pears yielded average Salmonella populations of 2.4±0.1, 0.8±0.5, and 0.4±0.1 log CFU/cm2, respectively, which were significantly lower (P<0.05) than medium (3.1±0.2 , 1.2±0.4, and 0.6±0.1 log CFU/cm2) and soft pears (3.6±0.1 , 1.5±0.2, and 1.1±0.3 log CFU/cm2). In addition, the total number of Salmonella cells transferred was statistically higher for firm (P<0.05) as compared to medium and soft pears.

Significance: The extent of cross-contamination of fresh produce during slicing is affected by firmness. These findings should prove useful in developing improved predictive models for bacterial transfer and expanding current risk assessments across a wider range of products.