Development of an intelligent surgical knife rapid evaporative ionization mass spectrometry based method for real-time differentiation of cod from oilfish

Abstract

Oilfish is banned in some countries because of the unpleasant side-effects of eating oilfish. However, oilfish was easily mislabeled and sold as cod due to their closed appearance. In this study, an in situ and real-time method was developed to distinguish cod from oilfish by coupling intelligent surgical knife (iKnife) and rapid evaporative ionization mass spectrometry (REIMS). The fillets collected from the same position of adult fishes were analyzed directly without sample preparation. The iKnife-REIMS conditions were optimized as cutting speed ca. 5 mm·s−1 and stripe length 2 cm, power output 30 W, and flow rate of auxiliary solvent (propan-2-ol) 100 μL·min–1. 200 spectral data from oilfish and cod was acquired in negative ionization mode and the data was processed by background subtraction, peak detection, and absolute counts calculation, which were further statistically analyzed by multivariate statistical analyses, including principal component analysis (PCA) and orthogonal partial least-square analysis (OPLS-DA). The major contributors of cluster separation were verified by permutation test and receiver operating characteristic (ROC) analysis. The identities of oilfish and cod (Greenland cod, Pacific cod, and Atlantic cod) were successfully recognized with accuracy 96–100%. This study filled the application niche of REIMS in cod authenticity and paved the way for the administration of food security and quality for related functional departments and bureaus.