Food Protection Trends - May/June 2023 - 218

TABLE 1. Average log CFU per gram or square centimeter (±SD) of E. coli recovered
from inoculated chicken, mask A and B contaminated from chicken, and lettuce
contaminated from mask B
Log CFU/g or log CFU/cm2
Inoculation level Slicing time (min)a
Chicken
High
Low
a
1
5
10
1
5
10
5.9 ± 0.2
3.8 ± 0.4
Mask Ab
3.2 ± 0.8
4.8 ± 0.2
4.6 ± 0.5
1.4 ± 0.3
2.6 ± 0.2
2.8 ± 0.4
Mask Bc
2.3 ± 1.1
4.1 ± 0.5
3.4 ± 0.7
0.9 ± 0.2
1.5 ± 0.4
2.1 ± 0.6
Lettuce
2.0 ± 0.8
3.2 ± 0.2
2.8 ± 0.5
1.0 ± 0.0
1.1 ± 0.2
1.4 ± 0.5
Slicing time refers to the number of minutes the chicken was sliced while touching masks once per minute. All lettuce was chopped
for 5 min while touching the contaminated mask once per minute.
bMask A was sampled immediately after chicken was sliced.
cMask B was sampled following chopping lettuce, in which it was used as the contamination source.
± SD
excluded because no effect was detected. The response (Yijk)
was investigated in two parts: 1) transfer from chicken to
mask and 2) transfer from mask to lettuce. Rank statistics
were used to evaluate the ratio of the transferred bacteria
from chicken to mask because the levels were on vastly
different scales. Use of ranks allowed better understanding
of data values with different scales, was free of assumptions
(such as the assumption of normality in a statistical model),
and is invariant to the log transformations. Analysis of
variance was used for subsequent analyses. All data analyses
were conducted in R Studio (R version 3.6.3) (18).
The interaction term (inoculation × mask-touching)ij
RESULTS
In studies that characterize cross-contamination, data may
be log-transformed and compared, or the percent transfer
may be calculated (11, 12). Although this transformation can
produce normalized data, it is not always a transformation
that yields normalized data that can be meaningfully
compared. The present study chose to log-transform CFU
per gram or square centimeter, calculate a transfer ratio,
and conduct rank statistics to evaluate significance after
normalization. The rank statistics allowed meaningful
comparison regardless of the difference in inoculation level
so that conclusions would not be drawn simply based on the
magnitude of difference between high and low inoculation.
Table 1 shows the log CFU per gram or square centimeter of
E. coli recovered from each chicken, mask, and lettuce sample,
and Fig. 2 shows the general progression of transfer (recovery
of E. coli) for each contamination and slicing scenario in the
218 Food Protection Trends May/June
was
form of a scatterplot. Transfer of E. coli was observed from
inoculated chicken to masks and from contaminated masks to
lettuce. The difference in inoculation level did not affect the
ranking of bacterial transfer. However, the number of touches
between inoculated chicken and mask did result in greater
bacterial transfer. The ranked statistical approach allowed
normalization of data and highlighted that contaminating
a mask 10 vs. 1 time contributed to significant transfer of
E. coli but that the difference between touching a mask 5
vs. 10 times was not significant. Furthermore, the number
of times the mask was touched during chicken slicing did
not proportionally affect bacterial transfer from the mask to
the lettuce. Mean and standard deviation (SD) of bacterial
transfers are reported in Table 1.
Transfer of E. coli from inoculated chicken to masks
Overall, the slicing time and subsequent number of
touches to the mask while slicing the inoculated chicken
significantly affected E. coli transfer. Evident in the
normalized ranking statistics, the more times a mask was
contaminated, the greater the bacterial transfer (P < 0.05).
In the case of slicing high-inoculated chicken breasts, the
transfer to the mask when touched every minute for 1, 5, and
10 min was 3.2, 4.8, and 4.6 log CFU/cm2
, respectively. In
the case of low-inoculated chicken breasts, touching masks
every minute for 1, 5, and 10 min resulted in recovery of 1.4,
2.6, and 2.8 log CFU/cm2
, respectively. Some touching time
intervals (1, 5, and 10 min) had significant effects on transfer
of E. coli. Significant differences were found between slicing
times of 1-5 min (P < 0.05) and 1-10 min (P < 0.05), with

Food Protection Trends - May/June 2023

Table of Contents for the Digital Edition of Food Protection Trends - May/June 2023

Food Allergy Knowledge and Attitudes of Owners and Managers of Independently Owned Restaurants in Metro Orlando, Florida
Face Masks as Sources of Cross-Contamination during Food Preparation
Food Safety Knowledge and Practices among Household Food Handlers in Mangweni Village of Mpumalanga Province in South Africa
Risk Management Options to Reduce Human Salmonellosis Cases Due to Consumption of Raw Poultry
Beyond the Bio Almaris Alonso-Claudio
PDG Highlight Viral and Parasitic Foodborne Disease PDG
General Interest Evaluating Microbiological Method Equivalence – A Decision Guide
Industry Products
Coming Events
Food Protection Trends - May/June 2023 - Cover1
Food Protection Trends - May/June 2023 - Cover2
Food Protection Trends - May/June 2023 - 197
Food Protection Trends - May/June 2023 - 198
Food Protection Trends - May/June 2023 - 199
Food Protection Trends - May/June 2023 - 200
Food Protection Trends - May/June 2023 - 201
Food Protection Trends - May/June 2023 - 202
Food Protection Trends - May/June 2023 - 203
Food Protection Trends - May/June 2023 - Food Allergy Knowledge and Attitudes of Owners and Managers of Independently Owned Restaurants in Metro Orlando, Florida
Food Protection Trends - May/June 2023 - 205
Food Protection Trends - May/June 2023 - 206
Food Protection Trends - May/June 2023 - 207
Food Protection Trends - May/June 2023 - 208
Food Protection Trends - May/June 2023 - 209
Food Protection Trends - May/June 2023 - 210
Food Protection Trends - May/June 2023 - 211
Food Protection Trends - May/June 2023 - 212
Food Protection Trends - May/June 2023 - 213
Food Protection Trends - May/June 2023 - 214
Food Protection Trends - May/June 2023 - Face Masks as Sources of Cross-Contamination during Food Preparation
Food Protection Trends - May/June 2023 - 216
Food Protection Trends - May/June 2023 - 217
Food Protection Trends - May/June 2023 - 218
Food Protection Trends - May/June 2023 - 219
Food Protection Trends - May/June 2023 - 220
Food Protection Trends - May/June 2023 - 221
Food Protection Trends - May/June 2023 - 222
Food Protection Trends - May/June 2023 - Food Safety Knowledge and Practices among Household Food Handlers in Mangweni Village of Mpumalanga Province in South Africa
Food Protection Trends - May/June 2023 - 224
Food Protection Trends - May/June 2023 - 225
Food Protection Trends - May/June 2023 - 226
Food Protection Trends - May/June 2023 - 227
Food Protection Trends - May/June 2023 - 228
Food Protection Trends - May/June 2023 - 229
Food Protection Trends - May/June 2023 - 230
Food Protection Trends - May/June 2023 - 231
Food Protection Trends - May/June 2023 - Risk Management Options to Reduce Human Salmonellosis Cases Due to Consumption of Raw Poultry
Food Protection Trends - May/June 2023 - 233
Food Protection Trends - May/June 2023 - 234
Food Protection Trends - May/June 2023 - 235
Food Protection Trends - May/June 2023 - 236
Food Protection Trends - May/June 2023 - 237
Food Protection Trends - May/June 2023 - 238
Food Protection Trends - May/June 2023 - 239
Food Protection Trends - May/June 2023 - Beyond the Bio Almaris Alonso-Claudio
Food Protection Trends - May/June 2023 - 241
Food Protection Trends - May/June 2023 - 242
Food Protection Trends - May/June 2023 - PDG Highlight Viral and Parasitic Foodborne Disease PDG
Food Protection Trends - May/June 2023 - 244
Food Protection Trends - May/June 2023 - 245
Food Protection Trends - May/June 2023 - 246
Food Protection Trends - May/June 2023 - 247
Food Protection Trends - May/June 2023 - 248
Food Protection Trends - May/June 2023 - 249
Food Protection Trends - May/June 2023 - 250
Food Protection Trends - May/June 2023 - 251
Food Protection Trends - May/June 2023 - 252
Food Protection Trends - May/June 2023 - 253
Food Protection Trends - May/June 2023 - 254
Food Protection Trends - May/June 2023 - 255
Food Protection Trends - May/June 2023 - 256
Food Protection Trends - May/June 2023 - 257
Food Protection Trends - May/June 2023 - 258
Food Protection Trends - May/June 2023 - 259
Food Protection Trends - May/June 2023 - 260
Food Protection Trends - May/June 2023 - 261
Food Protection Trends - May/June 2023 - 262
Food Protection Trends - May/June 2023 - 263
Food Protection Trends - May/June 2023 - 264
Food Protection Trends - May/June 2023 - 265
Food Protection Trends - May/June 2023 - 266
Food Protection Trends - May/June 2023 - 267
Food Protection Trends - May/June 2023 - 268
Food Protection Trends - May/June 2023 - 269
Food Protection Trends - May/June 2023 - 270
Food Protection Trends - May/June 2023 - 271
Food Protection Trends - May/June 2023 - 272
Food Protection Trends - May/June 2023 - 273
Food Protection Trends - May/June 2023 - 274
Food Protection Trends - May/June 2023 - General Interest Evaluating Microbiological Method Equivalence – A Decision Guide
Food Protection Trends - May/June 2023 - 276
Food Protection Trends - May/June 2023 - 277
Food Protection Trends - May/June 2023 - 278
Food Protection Trends - May/June 2023 - 279
Food Protection Trends - May/June 2023 - 280
Food Protection Trends - May/June 2023 - Industry Products
Food Protection Trends - May/June 2023 - 282
Food Protection Trends - May/June 2023 - 283
Food Protection Trends - May/June 2023 - Coming Events
Food Protection Trends - May/June 2023 - Cover3
Food Protection Trends - May/June 2023 - Cover4
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