Food Protection Trends - November/December 2020 - 403

control programs, hygiene monitoring to provide rapid and
timely results is required so corrective actions can be taken
immediately. Visual assessment alone is not accurate and
reliable even though it is economical (5, 6). Traditional
bacterial cultures are often used for sanitation evaluation.
However, culture incubation takes a few days, precluding
immediate feedback and timely action. Protein swab tests
and lateral flow immunoassays are quick and simple methods
for identification of food debris and allergens. The swabbased protein test can be used to detect food residues and a
broad range of allergens, but these tests are qualitative and
nonspecific and may not be effective with low levels of residual
protein contamination (7). Lateral flow immunoassays can
be used to detect allergenic foods qualitatively and selectively
with high sensitivity and thus are suitable for the control
of allergens but are not appropriate for monitoring organic
debris that does not contain the target proteins (6). Hygiene
monitoring tests based on the presence of ATP have also
been widely used because of their speed and simplicity.
ATP is the energy molecule found in animals, plants, and
microorganisms. Although ATP tests are nonspecific, they can
reveal the presence of food debris and bacteria, indicating a
risk of bacterial proliferation and cross-contact with allergens.
ATP measurements is based on the firefly luciferase reaction in
which light is produced from luciferin and ATP. The amount
of light produced is proportional to the amount of ATP in a
sample and can be quantified by measuring the light with a
luminometer and is expressed as relative light units (RLU).
Benchmark values are set to determine baseline cleanliness in
a facility, and these benchmark values are important guidelines
for the evaluation of cleanliness. Cleanliness is designated as
"pass" when the measured RLU fall below the benchmark
value and as "fail" when the RLU are above the benchmark.
When the test indicates a failing result, the recommendation
is to reclean the test site, revise the cleaning procedures, or
replace the failed equipment.
However, conventional ATP test systems can be inefficient
because ATP is degraded to ADP and AMP by heat, acids, or
alkalis, and enzymes (3). Raw meat and fish contain mainly
ADP, regardless of species (3), and ADP is the predominant
adenylate in bovine, porcine, and poultry carcasses (14). In
contrast, raw whole eggs, shellfish (shrimp, oysters, scallops,
and abalone), and processed meats and seafood (sausage,
bacon, beef jerky, canned fish, and dried fish) contain large
amounts of AMP (3). AMP is also found abundantly in many
plant seeds and nuts, which are widely known as allergens
(3). Hence, conventional ATP tests that indicate only ATP
concentrations might fail to detect other food residues and
would fail to identify inadequately cleaned surfaces.
A novel ATP-ADP-AMP (A3) test has been developed
based on a luciferin-luciferase assay with advanced enzyme
chemistry (3, 4, 12). In the luciferase reaction, ATP is
degraded into AMP, which then inhibits luciferase, resulting in
a decrease in light production. To detect AMP simultaneously

and maintain light production, ATP is regenerated from AMP
with the pyruvate orthophosphate dikinase reaction (3).
ADP is then converted to ATP by a pyruvate kinase reaction.
A device to simultaneously detect ATP, ADP, and AMP has
been successfully developed. The limit of detection for each
adenylate is ca. 2.5 fmol (2). This A3 test has been validated for
the detection of ATP, ADP, and AMP on stainless steel surfaces
and has been approved by the Association of Official Analytical
Collaboration with a performance tested method certification
(2). This A3 test is expected to provide for a more sensitive and
reliable indicator of cleanliness than the conventional ATP test.
The protocol of an ATP test consists of sample collection by
swabbing, extraction of the swab material, a bioluminescence
reaction, and an instrument-based detection of light. In
our previous study comparing conventional ATP tests and
the A3 test, diluted food samples were pipetted onto each
swab (3, 12). Further comparisons that include swabbing
efficacy are also important because this essential component
of the sampling phase is also affected by the variability of
the performance of the swabbing devices and moistening
agents. In the present study, swabbing assays of food residues
on stainless steel coupons were carried out to compare the
sensitivity of the A3 test and conventional ATP tests.

FIGURE 1. The measurement of swabbing pressure on the scale pan
of the analytical balance using the A3 test swab. When the swab shaft
slightly bent, the balance showed approximately 70-100 g.

MATERIALS AND METHODS
A3 and ATP tests
The A3 test was performed with a commercially available
test kit (LuciPac A3 Surface/Lumitester PD-30, Kikkoman
Biochemifa, Tokyo, Japan) according to the manufacturer's
directions. The three ATP tests used in this study were also
commercially available and were performed in accordance
with manufacturers' instructions. The measurements in all tests
were recorded in RLU.

November/December Food Protection Trends

403



Food Protection Trends - November/December 2020

Table of Contents for the Digital Edition of Food Protection Trends - November/December 2020

Characterizing Microbial Cross-Contamination on Large Surfaces Using a Traditional “Cloth and Bucket” Disinfection Method
Sanitation Monitoring of Stainless Steel Surfaces with a Test for Total Adenylates
Variability in the Microbial Profile of Retail Cricket Powders in the U.S. Retail Market
Exploring Food Truck Food Safety Training and Practices in the United States: A Qualitative Study
Use of the Theory of Planned Behavior to Determine Food Safety Behavioral Intentions among Child Nutrition Employees
Produce Safety Alliance Train-the-Trainer Course: Developing Trainers to Support Fruit and Vegetable Growers
Beyond the Bio Manpreet Singh
PDG Highlight Food Packaging Professional Development Group
General Interest Paper Exploring Novel Technologies to Enhance Food Safety Training and Research Opportunities
General Interest Paper Food Safety and Quality Data Management Using Artificial Intelligence
Industry Products
Coming Events
Food Protection Trends - November/December 2020 - Cover1
Food Protection Trends - November/December 2020 - Cover2
Food Protection Trends - November/December 2020 - 385
Food Protection Trends - November/December 2020 - 386
Food Protection Trends - November/December 2020 - 387
Food Protection Trends - November/December 2020 - 388
Food Protection Trends - November/December 2020 - 389
Food Protection Trends - November/December 2020 - 390
Food Protection Trends - November/December 2020 - 391
Food Protection Trends - November/December 2020 - Characterizing Microbial Cross-Contamination on Large Surfaces Using a Traditional “Cloth and Bucket” Disinfection Method
Food Protection Trends - November/December 2020 - 393
Food Protection Trends - November/December 2020 - 394
Food Protection Trends - November/December 2020 - 395
Food Protection Trends - November/December 2020 - 396
Food Protection Trends - November/December 2020 - 397
Food Protection Trends - November/December 2020 - 398
Food Protection Trends - November/December 2020 - 399
Food Protection Trends - November/December 2020 - 400
Food Protection Trends - November/December 2020 - 401
Food Protection Trends - November/December 2020 - Sanitation Monitoring of Stainless Steel Surfaces with a Test for Total Adenylates
Food Protection Trends - November/December 2020 - 403
Food Protection Trends - November/December 2020 - 404
Food Protection Trends - November/December 2020 - 405
Food Protection Trends - November/December 2020 - 406
Food Protection Trends - November/December 2020 - Variability in the Microbial Profile of Retail Cricket Powders in the U.S. Retail Market
Food Protection Trends - November/December 2020 - 408
Food Protection Trends - November/December 2020 - 409
Food Protection Trends - November/December 2020 - 410
Food Protection Trends - November/December 2020 - 411
Food Protection Trends - November/December 2020 - 412
Food Protection Trends - November/December 2020 - Exploring Food Truck Food Safety Training and Practices in the United States: A Qualitative Study
Food Protection Trends - November/December 2020 - 414
Food Protection Trends - November/December 2020 - 415
Food Protection Trends - November/December 2020 - 416
Food Protection Trends - November/December 2020 - 417
Food Protection Trends - November/December 2020 - 418
Food Protection Trends - November/December 2020 - 419
Food Protection Trends - November/December 2020 - 420
Food Protection Trends - November/December 2020 - 421
Food Protection Trends - November/December 2020 - 422
Food Protection Trends - November/December 2020 - 423
Food Protection Trends - November/December 2020 - Use of the Theory of Planned Behavior to Determine Food Safety Behavioral Intentions among Child Nutrition Employees
Food Protection Trends - November/December 2020 - 425
Food Protection Trends - November/December 2020 - 426
Food Protection Trends - November/December 2020 - 427
Food Protection Trends - November/December 2020 - 428
Food Protection Trends - November/December 2020 - 429
Food Protection Trends - November/December 2020 - 430
Food Protection Trends - November/December 2020 - 431
Food Protection Trends - November/December 2020 - 432
Food Protection Trends - November/December 2020 - 433
Food Protection Trends - November/December 2020 - 434
Food Protection Trends - November/December 2020 - Produce Safety Alliance Train-the-Trainer Course: Developing Trainers to Support Fruit and Vegetable Growers
Food Protection Trends - November/December 2020 - 436
Food Protection Trends - November/December 2020 - 437
Food Protection Trends - November/December 2020 - 438
Food Protection Trends - November/December 2020 - 439
Food Protection Trends - November/December 2020 - 440
Food Protection Trends - November/December 2020 - 441
Food Protection Trends - November/December 2020 - 442
Food Protection Trends - November/December 2020 - 443
Food Protection Trends - November/December 2020 - 444
Food Protection Trends - November/December 2020 - 445
Food Protection Trends - November/December 2020 - 446
Food Protection Trends - November/December 2020 - 447
Food Protection Trends - November/December 2020 - 448
Food Protection Trends - November/December 2020 - 449
Food Protection Trends - November/December 2020 - 450
Food Protection Trends - November/December 2020 - 451
Food Protection Trends - November/December 2020 - Beyond the Bio Manpreet Singh
Food Protection Trends - November/December 2020 - 453
Food Protection Trends - November/December 2020 - 454
Food Protection Trends - November/December 2020 - PDG Highlight Food Packaging Professional Development Group
Food Protection Trends - November/December 2020 - General Interest Paper Exploring Novel Technologies to Enhance Food Safety Training and Research Opportunities
Food Protection Trends - November/December 2020 - 457
Food Protection Trends - November/December 2020 - 458
Food Protection Trends - November/December 2020 - 459
Food Protection Trends - November/December 2020 - 460
Food Protection Trends - November/December 2020 - 461
Food Protection Trends - November/December 2020 - 462
Food Protection Trends - November/December 2020 - 463
Food Protection Trends - November/December 2020 - General Interest Paper Food Safety and Quality Data Management Using Artificial Intelligence
Food Protection Trends - November/December 2020 - 465
Food Protection Trends - November/December 2020 - 466
Food Protection Trends - November/December 2020 - 467
Food Protection Trends - November/December 2020 - Industry Products
Food Protection Trends - November/December 2020 - 469
Food Protection Trends - November/December 2020 - 470
Food Protection Trends - November/December 2020 - 471
Food Protection Trends - November/December 2020 - Coming Events
Food Protection Trends - November/December 2020 - Cover3
Food Protection Trends - November/December 2020 - Cover4
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