Optimization of the QuEChERS Extraction of Mycotoxins in Maize Using Response Surface Methodology (RSM)

Abstract

AbstractSeveral methods have been developed for the analysis and detection of mycotoxins in food; however, most do not make use of critical statistics and mathematical tools for precise optimization. This study developed, optimized, and validated a modified quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction procedure for the extraction of multiple mycotoxins in maize and subsequent validation using liquid chromatography tandem mass spectrometry (LC–MS/MS). Central composite design (CCD) was used to optimize extraction conditions. Data analysis of full factorial screening experiments revealed that MeCN (%), FA (%), and extraction time significantly affected the mycotoxins recovery. Assessment of the statistical significance of the generated model using analysis of variance (ANOVA), coefficient tables, and surface plots showed the relative interactions of factors and the adequacy of the model. Thus, P values from the lack of fit (LOF) test ranged from 0.137– 0.467 and a composite desirability function of 0.91 was obtained. Using the optimum extraction conditions of 0.1% (v/v) FA in 80.2% MeCN for 74 min, 10 mycotoxins were effectively extracted with satisfactory recoveries (85–114%), coefficients of regression (R2 > 0.98), coefficients of variation (CVs < 15%), limit of quantifications (LOQs) (0.33–60.45 µg/kg), and other associated method validation parameters. The method validation was carried out according to Commission Implementing Regulation 2021/808 and Commission Regulation (EC) No 401/2006 of 23 February 2006. Application of this method to 20 maize samples collected from markets in Botswana showed detectable mycotoxins in 13 samples, with 2 exceeding the European Union (EU) maximum aflatoxin B1 (AFB1) limit, suggesting potential exposure to high levels of toxic mycotoxins in Botswana.