An innovative approach for real-time authentication of cocoa butter using a combination of rapid evaporative ionization mass spectrometry and chemometrics

Detection of carob flour in cocoa powder by direct analysis in real time-mass spectrometry (DART-MS)

Cocoa is a high value product and therefore a potential target for economic adulteration with less expensive ingredients. Carob flour is less expensive than cocoa powder and is frequently cited as a potential cocoa substitute. While carob has legitimate uses as a cocoa replacement, these characteristics also make it a potential adulterant of cocoa powder. Direct analysis in real time mass spectrometry (DART-MS) is an ambient ionization MS technique that can be used to rapidly interrogate samples. Samples of cocoa powders, carob flours, and mixtures of the two were extracted with buffer and interrogated by DART-MS. The mass spectra were used to develop models to distinguish between cocoa powder and cocoa powder adulterated with carob. A principal component-linear discriminant analysis (PCA-LDA) model was used to discriminate between cocoa powder and cocoa powder amended with 15% carob flour. The accuracy using internal validation was 100%. Using an external validation dataset, the accuracy, precision, and recall were 96.0%, 94.8%, and 97.3%, respectively. These results demonstrate that DART-MS can be used to discriminate between cocoa powder and cocoa powder adulterated with 15% carob.

Rapid analysis technologies with chemometrics for food authenticity field: A review

In recent years, the problem of food adulteration has become increasingly rampant, seriously hindering the development of food production, consumption, and management. The common analytical methods used to determine food authenticity present challenges, such as complicated analysis processes and time-consuming procedures, necessitating the development of rapid, efficient analysis technology for food authentication. Spectroscopic techniques, ambient ionization mass spectrometry (AIMS), electronic sensors, and DNA-based technology have gradually been applied for food authentication due to advantages such as rapid analysis and simple operation. This paper summarizes the current research on rapid food authenticity analysis technology from three perspectives, including breeds or species determination, quality fraud detection, and geographical origin identification, and introduces chemometrics method adapted to rapid analysis techniques. It aims to promote the development of rapid analysis technology in the food authenticity field.

Authentication of Cocoa Products Based on Profiling and Fingerprinting Approaches: Assessment of Geographical, Varietal, Agricultural and Processing Features

Cocoa and its derivative products, especially chocolate, are highly appreciated by consumers for their exceptional organoleptic qualities, thus being often considered delicacies. They are also regarded as superfoods due to their nutritional and health properties. Cocoa is susceptible to adulteration to obtain illicit economic benefits, so strategies capable of authenticating its attributes are needed. Features such as cocoa variety, origin, fair trade, and organic production are increasingly important in our society, so they need to be guaranteed. Most of the methods dealing with food authentication rely on profiling and fingerprinting approaches. The compositional profiles of natural components -such as polyphenols, biogenic amines, amino acids, volatile organic compounds, and fatty acids- are the source of information to address these issues. As for fingerprinting, analytical techniques, such as chromatography, infrared, Raman, and mass spectrometry, generate rich fingerprints containing dozens of features to be used for discrimination purposes. In the two cases, the data generated are complex, so chemometric methods are usually applied to extract the underlying information. In this review, we present the state of the art of cocoa and chocolate authentication, highlighting the pros and cons of the different approaches. Besides, the relevance of the proposed methods in quality control and the novel trends for sample analysis are also discussed.

Atmospheric solids analysis probe-mass spectrometry (ASAP-MS) as a rapid fingerprinting technique to differentiate the harvest seasons of Tieguanyin oolong teas

Atmospheric solids analysis probe-mass spectrometry (ASAP-MS), an ambient mass spectrometry technique, was used to differentiate spring and autumn Tieguanyin teas. Two configurations were used to obtain their chemical fingerprints - ASAP attached to a high-resolution quadrupole time-of-flight mass spectrometer (i.e., ASAP-QTOF) and to a single-quadrupole mass spectrometer (i.e., Radian™ ASAP™ mass spectrometer). Then, orthogonal projections to latent structures-discriminant analysis was conducted to identify features that held promise in differentiating harvest seasons. Four machine learning models - decision tree, linear discriminant analysis, support vector machine, and k-nearest neighbour - were built using these features, and high classification accuracy of up to 100% was achieved. The markers were putatively identified using their accurate masses and MS/MS fragmentation patterns from ASAP-QTOF. This approach was successfully transferred to the Radian ASAP MS, which is more deployable in the field. Overall, this study demonstrated the potential of ASAP-MS as a rapid fingerprinting tool for differentiating spring and autumn Tieguanyin.