Multilaboratory Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry for the Screening of 1087 Pesticides in Fresh Fruits and Vegetables

A nontarget Data Acquisition for Target Analysis (nDATA)
workflow
was developed to screen pesticides in fresh produce based on ultrahigh-performance
liquid chromatography-high-resolution full scan mass spectrometry/variable
data-independent tandem mass spectrometry acquisition (LC-FS MS/vDIA
MSMS) and a pesticide database. The MSMS spectral library was generated
to create a database consisting of 1087 pesticides based on authentic
pesticide standards. The retention time (±0.5 min), precursor
ion (≤± 5 ppm), and product ions (≤± 5 ppm)
were extracted for each pesticide from LC-FS MS/data-dependent MSMS
acquisition (LC-FS MS/DDA MSMS). Mass accuracy criteria, along with
±0.1 min retention time tolerance, were used for the identification
of pesticides. Three laboratories evaluated and validated the nDATA
workflow to screen and identify pesticides from produce extracts (apples,
bananas, broccoli, carrots, grapes, lettuce, oranges, potatoes, strawberry,
and tomatoes) prepared by the Quick, Easy, Cheap, Effective, Rugged,
and Safe (QuEChERS) procedure. Of the 1087 pesticides evaluated, false-positive
rates were ≤5% for 977 pesticides in blank matrices and false-negative
rates were ≤5% for 921 and 985 pesticides in fortified matrices
at 10 and 100 μg/kg, respectively. False positives detected
were misidentified pesticides, incurred residues, or contaminants
possibly resulting from process or system contamination detected below
the threshold level of 10 μg/kg. False negatives were attributed
to pesticides that did not sufficiently ionize or fragment or had
poor stabilities and QuEChERS extraction efficiencies. Incurred residues
in archived produce samples (apple, Chinese broccoli, grape, kale,
kohlrabi, orange, pepper, strawberry, tomato, and turnip green) were
prepared using QuEChERS, evaluated by the nDATA workflow, and the
results were compared and confirmed, if possible, to targeted GC-MS/MS,
LC-MS/MS, and LC-FS MS/DDA MSMS methods. The three laboratories identified
25 parent pesticides at levels >10 μg/kg that were consistent
with findings from targeted procedures and discovered 10 different
metabolites that were not provided in the multiple reaction monitoring
method or inclusion list of the targeted procedures. GC-MS/MS identified
two pesticides, chlorothalonil and dacthal, and a possible chlorothalonil
metabolite, pentachlorobenzonitrile, that were not amenable to LC-low
or LC-high-resolution mass spectrometry analysis in produce samples.
To improve the identification quality, the nDATA workflow further
implemented quality control, operational, and processing measures
to reduce the number of false detects, and the data evaluation workload.
As demonstrated in this study, the validated nDATA workflow creates
new opportunities for chemical residues analysis, offering a potential
screening complement to targeted LC-MS/MS, GC-MS/MS, and nontargeted
methods for pesticides and other contaminants of interest.