Do You Want to Add Alternaria Toxins and Ergot Alkaloids in Your Multi-Mycotoxin Analysis? Part 3: Matrix Effect and Quantitative Standard Calibration4 Jan 2023
Similar to other types of multi-compound analysis in food by LC-MS/MS, one would need to mitigate the matrix effect, either suppression or enhancement, for accurate quantification of multi-mycotoxins in various food commodities. Due to significant variation in chemical compositions, most of the sample cleanup protocols would not result in acceptable recoveries for different types of mycotoxins across many different food commodities. A single step extraction followed by crude extract dilution and analysis by LC-MS/MS is gaining popularity partly due to its simplicity. This type of practice, however, could encounter difficulty in precise quantification resulting from differential matrix effects for each analyte. The use of stable isotopes as internal standards for quantitative standard calibration is the most direct approach to correct matrix effects. This approach, however, would not be applicable to most multi-mycotoxin analyses due to the lack of isotopically-labeled compounds for certain analytes. In this respect, the matrix-matched external standard calibration is more suitable for multi-mycotoxin analysis as it can equally compensate the matrix effect of calibration standards and sample solutions for accurate quantification. The shortcoming of matrix-matched calibration methodology is that to analyze a specific food product for mycotoxins, it is necessary to identify a representative food commodity containing relatively low levels of incurred mycotoxins to be used as the blank matrix. Indeed, we have experienced the difficulty of finding the mycotoxin-clean foods in the local grocery stores.
In this multi-mycotoxin analysis, matrix-matched calibration was implemented for the quantification of 37 mycotoxins in four food products representing a wide variety of food matrices including baby wheat cereal (baby food), tomato puree (fruit with high water content food), peanut (high fat food), and blended flour (high carbohydrate and high protein food). The food products with the smallest levels of incurred mycotoxins were picked for the method validation. A blended flour sample was made by mixing different types of flours to represent a grain-based flour and to dilute out the incurred mycotoxin from a specific flour sample. The concentration of incurred mycotoxins was evaluated in the blank or non-fortified sample extracts. By examining the calculation consistency for recoveries of the food samples with the lowest fortified concentration, it was determined that there was no concentration correction needed if the signals of incurred mycotoxins was less than 30% of the lowest concentrated standard. Otherwise, the signals of incurred mycotoxins were corrected by peak area subtraction of matrix-matched standards and fortified sample extract from the blank extract.