Development of Non-Targeted Mass Spectrometry Method for Distinguishing Spelt and Wheat.

Food fraud, even when not in the news, is ubiquitous and demands the development of innovative strategies to combat it. A new non-targeted method (NTM) for distinguishing spelt and wheat is described, which aids in food fraud detection and authenticity testing. A highly resolved fingerprint in the form of spectra is obtained for several cultivars of spelt and wheat using liquid chromatography coupled high-resolution mass spectrometry (LC-HRMS). Convolutional neural network (CNN) models are built using a nested cross validation (NCV) approach by appropriately training them using a calibration set comprising duplicate measurements of eleven cultivars of wheat and spelt, each. The results reveal that the CNNs automatically learn patterns and representations to best discriminate tested samples into spelt or wheat. This is further investigated using an external validation set comprising artificially mixed spectra, samples for processed goods (spelt bread and flour), eleven untypical spelt, and six old wheat cultivars. These cultivars were not part of model building. We introduce a metric called the D score to quantitatively evaluate and compare the classification decisions. Our results demonstrate that NTMs based on NCV and CNNs trained using appropriately chosen spectral data can be reliable enough to be used on a wider range of cultivars and their mixes.

Comparative quantification and differentiation of bracatinga (Mimosa scabrella Bentham) honeydew honey proteins using targeted peptide markers identified by high-resolution mass spectrometry.

Honey traceability is an important topic, especially for honeydew honeys, due to the increased incidence of adulteration. This study aimed to establish specific markers to quantify proteins in honey. A proteomics strategy to identify marker peptides from bracatinga honeydew honey was therefore developed. The proteomics approach was based on initial untargeted identification of honey proteins and peptides by LC-ESI-Triple-TOF-MS/MS, which identified the major royal jelly proteins (MRJP) presence. Afterwards, the peptides were selected by the in silico digestion. The marker peptides were quantified by the developed targeted LC-QqQ-MS/MS method, which provided good linearity and specificity, besides recoveries between 92 and 100% to quantify peptides from bracatinga honeydew honey. The uniqueness and high response in mass spectrometry were backed by further complementary protein analysis (SDS-PAGE). The selected marker peptides EALPHVPIFDR (MRJP 1), ILGANVK (MRJP 2), TFVTIER (MRJP 3), QNIDVVAR (MRJP 4), FINNDYNFNEVNFR (MRJP 5) and LLQPYPDWSWTK (MRJP 7), quantified by LC-QqQ-MS/MS, highlighted that the content of QNIDVVAR from MRJP 4 could be used to differentiate bracatinga honeydew honey from floral honeys (p < 0.05) as a potential marker for its authentication. Finally, principal components analysis highlighted the QNIDVVAR content as a good descriptor of the analyzed bracatinga honeydew honey samples.

A New Approach of Extraction of α-Amylase/trypsin Inhibitors from Wheat (Triticum aestivum L.), Based on Optimization Using Plackett-Burman and Box-Behnken Designs.

Wheat is one of the most consumed foods in the world and unfortunately causes allergic reactions which have important health effects. The α-amylase/trypsin inhibitors (ATIs) have been identified as potentially allergen components of wheat. Due to a lack of data on optimization of ATI extraction, a new wheat ATIs extraction approach combining solvent extraction and selective precipitation is proposed in this work. Two types of wheat cultivars (Triticum aestivum L.), Julius and Ponticus were used and parameters such as solvent type, extraction time, temperature, stirring speed, salt type, salt concentration, buffer pH and centrifugation speed were analyzed using the Plackett-Burman design. Salt concentration, extraction time and pH appeared to have significant effects on the recovery of ATIs (p < 0.01). In both wheat cultivars, Julius and Ponticus, ammonium sulfate substantially reduced protein concentration and inhibition of amylase activity (IAA) compared to sodium chloride. The optimal conditions with desirability levels of 0.94 and 0.91 according to the Doehlert design were: salt concentrations of 1.67 and 1.22 M, extraction times of 53 and 118 min, and pHs of 7.1 and 7.9 for Julius and Ponticus, respectively. The corresponding responses were: protein concentrations of 0.31 and 0.35 mg and IAAs of 91.6 and 83.3%. Electrophoresis and MALDI-TOF/MS analysis showed that the extracted ATIs masses were between 10 and 20 kDa. Based on the initial LC-MS/MS analysis, up to 10 individual ATIs were identified in the extracted proteins under the optimal conditions. The positive implication of the present study lies in the quick assessment of their content in different varieties especially while considering their allergenic potential.