Food Protection Trends - November/December 2017 - 404
of pathogenic bacteria. Bosilevac et al. (3) estimated
the prevalence of Salmonella, Campylobacter, Listeria
monocytogenes, and Shiga toxin gene markers to be
0.8% (4/487), 1.3% (5/393), 5.0% (17/341), and 30%
(147/487), respectively, in boneless beef trim collected
in U.S. facilities, and Hill et al. (10) found Salmonella
and Escherichia coli O157 in 1.6% (14,272/892,029) and
0.82% (7,315/892,029) of trim samples collected from 20
commercial beef processing facilities in the Midwestern
U.S. between 2005 and 2008 (10). Additionally, routine
verification testing programs from the U.S. Department of
Agriculture, Food Safety and Inspection Service (USDAFSIS) show that in 2015 and 2016, respectively, 0.06%
(2/3,308) and 0.19% (7/3,779) of trim samples used as
raw ground beef product components, i.e., beef trimmings,
collected from federally inspected facilities were positive
for E. coli O157:H7 (18, 20). Furthermore, non-O157 Shiga
toxigenic E. coli were present in 0.53% (12/2,264) of trim
samples collected for verification activities in 2012 (18).
Given that pathogenic bacteria may be present in
beef trim destined for human consumption, there is a
need to validate the in-plant sanitation conditions and
antimicrobial interventions intended to prevent, reduce,
and/or eliminate microbial hazards (6). This task may
be performed by estimating the prevalence and/or
concentration of the food safety hazards (6). However, the
distribution of pathogens in live animals, carcasses, and
raw meat products such as trimmings and ground beef is
extremely variable, and this variability limits the degree
of confidence with which a sampling plan can indicate the
presence of a pathogen in a product lot (1, 15). In these
cases, testing for indicator organisms, such as aerobic
bacteria and generic E. coli, is the best approach to the
validation and verification of a process control system
that is designed to reduce microbial contamination. These
organisms may be indicative of environmental and fecal
contamination, and because their expected frequency
is much higher than that of pathogens, they are more
suitable as process control indicators (1, 15).
The greatest compositional variable in a beef carcass is
the amount of fat (2, 12, 13). The fat content of the resulting
cuts and ground beef greatly influences physicochemical,
functional, and sensory properties, but the effect on
microbiological characteristics is not clear (2, 12, 13).
The subcutaneous fat layer comprises the major outer
surface of the carcass, and it has been hypothesized that
this tissue is most likely one of the first to be contaminated
during slaughter and carcass dressing procedures (12),
which may in turn impact the microbiological status of
beef trim. Additionally, because primal and subprimal cuts
differ in surface fat content, it has been suggested that the
anatomical location of trimmings may influence bacterial
counts (2). The objective of this study was to determine
the impact of carcass anatomical location with varying
404
Food Protection Trends November/December
proportions of surface fat on the microbiological profile of
beef trimmings destined for ground beef production.
MATERIALS AND METHODS
Sample collection
Samples of beef trimmings destined for human consumption
were collected throughout the 2015/2016 fall and winter
months at a large beef fabrication facility in the Midwestern
U.S. Four different types of trimmings - chuck, heel, shank,
and sparse lean - were sampled. Each set of trimmings
represented different carcass locations and had distinct surface
fat contents as visually determined in the plant as follows:
Chuck (24-30% fat) - chuck area (shoulder); Heel (5-10%
fat) - outside round; Shank (5-10% fat) - fore and hind
shank; and Sparse lean (70% fat and higher) - various,
but primarily navel, plate (ribs) and flank. Seventy-five
trim samples were collected per replication throughout a
production day, 25 per shift (morning, midday, and evening).
Within a shift, five samples each of shank, heel, and chuck,
as well as 10 samples of sparse lean, were collected. Sample
collection was replicated five times on non-consecutive days,
for a total of 375 beef trimming samples (75 shank, 75 heel, 75
chuck, and 150 sparse lean).
Trimmings were swabbed with sterile EZ™ Reach sponges
pre-moistened with 25 ml of buffer peptone water (World
BioProducts, Mundelein, IL, USA) using a 10 cm × 10
cm sterile cardboard template. All sponge samples were
immediately chilled and shipped overnight to the Texas
Tech University Food Safety Laboratories in insulated
containers with ice packs.
Microbiological analyses
Upon arrival at the laboratory, sponge samples were
stomached for 30 seconds at 230 rpm, using a countertop
stomacher (Seward 400C Stomacher; England). One- and
two-fold serial decimal dilutions were created for every
sample in buffered peptone water (BPW; Becton Dickinson,
Sparks, MD). A 1-ml aliquot of each dilution was plated
onto duplicate Aerobic Count (AC) Petrifilms™ (3M™, St.
Paul, MN) and E. coli/Coliforms (ECC) Count Petrifilms™
(3M™, St. Paul MN). Aerobic, coliform, and generic E. coli
counts were estimated according to the manufacturer's
instructions. Briefly, AC Petrifilms™ were incubated at 35
± 1°C and red colonies were counted after 48 hours. ECC
Petrifilms™ were incubated at 35 ± 1°C and coliforms (red
colonies associated with gas) were counted after 24 hours,
while E. coli (blue colonies associated with gas) were
counted after 48 hours. Colonies were counted under a
QCount® 530 colony counter (Advanced Instruments, Inc.,
Norwood, MA).
Statistical analyses
All microbial counts were converted to log10CFU/cm2. A
single-factor analysis of variance was performed to compare
Table of Contents for the Digital Edition of Food Protection Trends - November/December 2017
The Cleanliness of Resusable Water Bottles: How Contamination Levels are Affected by Bottle Usage and Cleaning Behaviors of Bottle Owners
Impact of Carcass Anatomical Location on the Microbiological Profile of Beef Trimmings
Thermal Processing Parameters to Ensure a 5-log Reduction of Escherichia coli O157:H7, Salmonella enterica, and Listeria monocytogenes in Acidified Tomato-based Foods
Experimental Evaluation of Performance of Sampling Techniques for Microbiological Quantification on Carcass Services
Effect-based Analytics for Toxicological Screening - Concepts for Future Developments
Beyond the Bio - John Luchansky
PDF Highlight - Food Chemical Hazards and Food Allergy PDG
IAFP 2017 In Review
Industry Products
Coming Events
Food Protection Trends - November/December 2017 - Cover1
Food Protection Trends - November/December 2017 - Cover2
Food Protection Trends - November/December 2017 - 385
Food Protection Trends - November/December 2017 - 386
Food Protection Trends - November/December 2017 - 387
Food Protection Trends - November/December 2017 - 388
Food Protection Trends - November/December 2017 - 389
Food Protection Trends - November/December 2017 - 390
Food Protection Trends - November/December 2017 - 391
Food Protection Trends - November/December 2017 - The Cleanliness of Resusable Water Bottles: How Contamination Levels are Affected by Bottle Usage and Cleaning Behaviors of Bottle Owners
Food Protection Trends - November/December 2017 - 393
Food Protection Trends - November/December 2017 - 394
Food Protection Trends - November/December 2017 - 395
Food Protection Trends - November/December 2017 - 396
Food Protection Trends - November/December 2017 - 397
Food Protection Trends - November/December 2017 - 398
Food Protection Trends - November/December 2017 - 399
Food Protection Trends - November/December 2017 - 400
Food Protection Trends - November/December 2017 - 401
Food Protection Trends - November/December 2017 - 402
Food Protection Trends - November/December 2017 - Impact of Carcass Anatomical Location on the Microbiological Profile of Beef Trimmings
Food Protection Trends - November/December 2017 - 404
Food Protection Trends - November/December 2017 - 405
Food Protection Trends - November/December 2017 - 406
Food Protection Trends - November/December 2017 - 407
Food Protection Trends - November/December 2017 - 408
Food Protection Trends - November/December 2017 - Thermal Processing Parameters to Ensure a 5-log Reduction of Escherichia coli O157:H7, Salmonella enterica, and Listeria monocytogenes in Acidified Tomato-based Foods
Food Protection Trends - November/December 2017 - 410
Food Protection Trends - November/December 2017 - 411
Food Protection Trends - November/December 2017 - 412
Food Protection Trends - November/December 2017 - 413
Food Protection Trends - November/December 2017 - 414
Food Protection Trends - November/December 2017 - 415
Food Protection Trends - November/December 2017 - 416
Food Protection Trends - November/December 2017 - 417
Food Protection Trends - November/December 2017 - 418
Food Protection Trends - November/December 2017 - Experimental Evaluation of Performance of Sampling Techniques for Microbiological Quantification on Carcass Services
Food Protection Trends - November/December 2017 - 420
Food Protection Trends - November/December 2017 - 421
Food Protection Trends - November/December 2017 - 422
Food Protection Trends - November/December 2017 - 423
Food Protection Trends - November/December 2017 - 424
Food Protection Trends - November/December 2017 - 425
Food Protection Trends - November/December 2017 - 426
Food Protection Trends - November/December 2017 - 427
Food Protection Trends - November/December 2017 - 428
Food Protection Trends - November/December 2017 - 429
Food Protection Trends - November/December 2017 - Effect-based Analytics for Toxicological Screening - Concepts for Future Developments
Food Protection Trends - November/December 2017 - 431
Food Protection Trends - November/December 2017 - 432
Food Protection Trends - November/December 2017 - 433
Food Protection Trends - November/December 2017 - 434
Food Protection Trends - November/December 2017 - 435
Food Protection Trends - November/December 2017 - 436
Food Protection Trends - November/December 2017 - 437
Food Protection Trends - November/December 2017 - Beyond the Bio - John Luchansky
Food Protection Trends - November/December 2017 - 439
Food Protection Trends - November/December 2017 - 440
Food Protection Trends - November/December 2017 - PDF Highlight - Food Chemical Hazards and Food Allergy PDG
Food Protection Trends - November/December 2017 - 442
Food Protection Trends - November/December 2017 - 443
Food Protection Trends - November/December 2017 - 444
Food Protection Trends - November/December 2017 - IAFP 2017 In Review
Food Protection Trends - November/December 2017 - 446
Food Protection Trends - November/December 2017 - 447
Food Protection Trends - November/December 2017 - 448
Food Protection Trends - November/December 2017 - 449
Food Protection Trends - November/December 2017 - 450
Food Protection Trends - November/December 2017 - 451
Food Protection Trends - November/December 2017 - 452
Food Protection Trends - November/December 2017 - 453
Food Protection Trends - November/December 2017 - 454
Food Protection Trends - November/December 2017 - 455
Food Protection Trends - November/December 2017 - 456
Food Protection Trends - November/December 2017 - 457
Food Protection Trends - November/December 2017 - 458
Food Protection Trends - November/December 2017 - 459
Food Protection Trends - November/December 2017 - 460
Food Protection Trends - November/December 2017 - 461
Food Protection Trends - November/December 2017 - 462
Food Protection Trends - November/December 2017 - 463
Food Protection Trends - November/December 2017 - 464
Food Protection Trends - November/December 2017 - 465
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Food Protection Trends - November/December 2017 - 467
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Food Protection Trends - November/December 2017 - 481
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Food Protection Trends - November/December 2017 - 483
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Food Protection Trends - November/December 2017 - 485
Food Protection Trends - November/December 2017 - 486
Food Protection Trends - November/December 2017 - 487
Food Protection Trends - November/December 2017 - 488
Food Protection Trends - November/December 2017 - 489
Food Protection Trends - November/December 2017 - 490
Food Protection Trends - November/December 2017 - 491
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Food Protection Trends - November/December 2017 - 500
Food Protection Trends - November/December 2017 - 501
Food Protection Trends - November/December 2017 - 502
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Food Protection Trends - November/December 2017 - 504
Food Protection Trends - November/December 2017 - 505
Food Protection Trends - November/December 2017 - 506
Food Protection Trends - November/December 2017 - 507
Food Protection Trends - November/December 2017 - 508
Food Protection Trends - November/December 2017 - 509
Food Protection Trends - November/December 2017 - 510
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Food Protection Trends - November/December 2017 - 529
Food Protection Trends - November/December 2017 - 530
Food Protection Trends - November/December 2017 - 531
Food Protection Trends - November/December 2017 - 532
Food Protection Trends - November/December 2017 - 533
Food Protection Trends - November/December 2017 - Industry Products
Food Protection Trends - November/December 2017 - 535
Food Protection Trends - November/December 2017 - 536
Food Protection Trends - November/December 2017 - 537
Food Protection Trends - November/December 2017 - 538
Food Protection Trends - November/December 2017 - 539
Food Protection Trends - November/December 2017 - 540
Food Protection Trends - November/December 2017 - 541
Food Protection Trends - November/December 2017 - 542
Food Protection Trends - November/December 2017 - 543
Food Protection Trends - November/December 2017 - Coming Events
Food Protection Trends - November/December 2017 - Cover3
Food Protection Trends - November/December 2017 - Cover4
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