Statistical evaluation to validate matrix-matched calibration for standardized beany odor compound quantitation in yellow pea flour using HS-SPME-GC-MS

Abstract

Accurate and precise quantitation of beany odor compounds is important in developing yellow pea (Pisum sativum L., YP) flour-based foods. Aiming at establishing standardized external calibration using an internal standard (ECIS) quantitation method, the effect of solvent extraction on matrix deodorization and systematic statistical analysis on quantitation was evaluated. Initially, accelerated dichloromethane extraction on YP flour and starch produced two clearest deodorized matrix-matched matrices. Secondly, due to the heteroskedasticity, weighted least squares regression (WLSR) was introduced to build calibration curves. The curve linearity and regression parameters were further confirmed via a t-test. Lastly, methodology indicators including LOD/LOQ, accuracy and precision, and the matrix effect (ME) were assessed. Results showed that there were no significant differences in the quantity of beany odor compounds interpolated from two deodorized matrices. This study demonstrated for the first time that despite the unignorable ME, deodorized starch is a feasible and affordable alternative to deodorized YP flour in the quantitation of beany odor compounds to achieve a reliable result.