Nontarget data acquisition for target
analysis (nDATA) workflows
using liquid chromatography-high-resolution accurate mass (LC-HRAM)
spectrometry, spectral screening software, and a compound database
have generated interest because of their potential for screening of
pesticides in foods. However, these procedures and particularly the
instrument processing software need to be thoroughly evaluated before
implementation in routine analysis. In this work, 25 laboratories
participated in a collaborative study to evaluate an nDATA workflow
on high moisture produce (apple, banana, broccoli, carrot, grape,
lettuce, orange, potato, strawberry, and tomato). Samples were extracted
in each laboratory by quick, easy, cheap, effective, rugged, and safe
(QuEChERS), and data were acquired by ultrahigh-performance liquid
chromatography (UHPLC) coupled to a high-resolution quadrupole Orbitrap
(QOrbitrap) or quadrupole time-of-flight (QTOF) mass spectrometer
operating in full-scan mass spectrometry (MS) data-independent tandem
mass spectrometry (LC-FS MS/DIA MS/MS) acquisition mode. The nDATA
workflow was evaluated using a restricted compound database with 51
pesticides and vendor processing software. Pesticide identifications
were determined by retention time (t
R,
±0.5 min relative to the reference retention times used in the
compound database) and mass errors (δM) of the precursor
(RTP, δM ≤ ±5 ppm) and product ions (RTPI,
δM ≤ ±10 ppm). The elution profiles of
all 51 pesticides were within ±0.5 min among 24 of the participating
laboratories. Successful screening was determined by false positive
and false negative rates of <5% in unfortified (pesticide-free)
and fortified (10 and 100 μg/kg) produce matrices. Pesticide
responses were dependent on the pesticide, matrix, and instrument.
The false negative rates were 0.7 and 0.1% at 10 and 100 μg/kg,
respectively, and the false positive rate was 1.1% from results of
the participating LC-HRAM platforms. Further evaluation was achieved
by providing produce samples spiked with pesticides at concentrations
blinded to the laboratories. Twenty-two of the 25 laboratories were
successful in identifying all fortified pesticides (0–7 pesticides
ranging from 5 to 50 μg/kg) for each produce sample (99.7% detection
rate). These studies provide convincing evidence that the nDATA comprehensive
approach broadens the screening capabilities of pesticide analyses
and provide a platform with the potential to be easily extended to
a larger number of other chemical residues and contaminants in foods.
