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commodities. A thorough understanding of matrix effects
would yield fundamental insights for different food matrices,
corresponding sample preparation, and subsequent instru-
ment performance, thus allowing major application needs
(identification and quantitation) to be addressed.
Generally, there are two types of matrix effects—matrix
interference and signal alteration. Matrix interference can be
caused by those coeluting components in sample extracts
that have similar ions in the MS/MS experiment. This type
of matrix effect can lead to false positive/negative identifi-
introduces more error, in terms of ac-
curacy and precision, for quantitative
results. Additionally, optimal dilution
factors depend on food matrices, instru-
ment sensitivity, target pesticides, and
LC conditions, so it is time-consuming
to optimize the experimental condi-
tions. Using internal standards might be
too expensive to apply in multi-residue
analysis. Matrix-matched calibration is
commonly used for quantitation, but
there are disadvantages associated with
this approach. First, it is hard to collect
blank matrix for each food commodity.
Second, analytes in a matrix-matched
environment are different from those in
real samples, in which the analytes first
interact with the matrix components
and then are “modified” by sample
preparation. Matrix-matched calibra-
tion standards would alleviate matrix
effects on quantification only if sample
matrices remained the same before and
after the sample preparation, which is
impossible to achieve. Therefore, this
approach might only work well for
simple matrices such as fresh produce,
but not for more complex matrices,
such as botanical samples. Third, it is la-
borious and time-consuming to prepare
matrix-matched calibration standards
for routine analysis, especially when
samples of different commodities have
to be analyzed on daily basis.
Obviously, the lack of well-suited ap-
proaches for circumventing matrix
effects requires us to systematically
investigate the problem so that, in
theory, we will be able to describe and
define the interactions between matrix
components and analytes. In practice,
we can quantitatively measure matrix
effects and estimate the impact on
quantitation and identification. At the
present time, LC-MS/MS is known as the
best instrument for target analysis and
quantitation; however, it is limited by
an incomplete understanding of matrix
effects. This presents a significant chal-
lenge to researchers working to harness
the sensitivity, selectivity, and specific-
ity of LC-MS/MS to meet the growing
need for better multi-residue analysis
procedures.
cation and can be resolved by using non-interfering MRM
transitions, extensive sample cleanup, or improving the LC
separation. Increased mass/charge selectivity, which can be
acquired by using a high resolution accurate mass spectrom-
eter, can help minimize matrix interference.
Matrix effects may also be caused by interactions (via van
der Waals, dipolar-dipolar, or electrostatic forces) between
pesticides and co-extractives in the prepared sample that
could suppress or enhance the ionization of a pesticide in
the ESI source. This can result in a lower or higher signal,
which affects the accuracy of the quantitative results. Several
approaches have been used to minimize the signal suppres-
sion or enhancement resulting from the matrix components.
These include extensive sample cleanup, improvement of the
LC separation to avoid coelutions with matrix components, or
serial dilution of the final extract, such that fewer matrix com-
ponents will be injected into the analytical system. Splitting
of the LC eluent flow before entering the mass spectrometer
may also help eliminate matrix suppression or enhancement.
Unlike the above approaches, standard addition, internal
standards, or matrix-matched calibration curves are common-
ly used to compensate for, but not to reduce, signal suppres-
sion or enhancement.
None of the above approaches will completely eliminate
matrix effects. Increased selectivity (e.g., using specific transi-
tions or improving mass resolution/accuracy) can minimize
matrix interferences, but signal suppression or enhancement
may still be observed because signal alteration happens in
the ion source prior to detection. Using dilution or a smaller
injection volume requires more sensitive instruments and
The effect of the matrix is a phenomenon
in electrospray ionization (ESI) LC-MS/MS
analysis that impacts the data quality …
and presents one of today’s most
challenging analytical issues.