The protein fractions of cocoa have been implicated influencing both the bioactive potential and sensory properties of cocoa and cocoa products. The objective of the present review is to show the impact of different stages of cultivation and processing with regard to the changes induced in the protein fractions. Special focus has been laid on the major seed storage proteins throughout the different stages of processing. The study starts with classical introduction of the extraction and the characterization methods used, while addressing classification approaches of cocoa proteins evolved during the timeline. The changes in protein composition during ripening and maturation of cocoa seeds, together with the possible modifications during the post-harvest processing (fermentation, drying, and roasting), have been documented. Finally, the bioactive potential arising directly or indirectly from cocoa proteins has been elucidated. The “state of the art” suggests that exploration of other potentially bioactive components in cocoa needs to be undertaken, while considering the complexity of reaction products occurring during the roasting phase of the post-harvest processing. Finally, the utilization of partially processed cocoa beans (e.g., fermented, conciliatory thermal treatment) can be recommended, providing a large reservoir of bioactive potentials arising from the protein components that could be instrumented in functionalizing foods.

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.

Many biochemical processes are involved in regulating the consecutive transition of different phases of dormancy in sweet cherry buds. An evaluation based on a metabolic approach has, as yet, only been partly addressed. The aim of this work, therefore, was to determine which plant metabolites could serve as biomarkers for the different transitions in sweet cherry buds. The focus here was on those metabolites involved in oxidation-reduction processes during bud dormancy, as determined by targeted and untargeted mass spectrometry-based methods. The metabolites addressed included phenolic compounds, ascorbate/dehydroascorbate, reducing sugars, carotenoids and chlorophylls. The results demonstrate that the content of phenolic compounds decrease until the end of endodormancy. After a long period of constancy until the end of ecodormancy, a final phase of further decrease followed up to the phenophase open cluster. The main phenolic compounds were caffeoylquinic acids, coumaroylquinic acids and catechins, as well as quercetin and kaempferol derivatives. The data also support the protective role of ascorbate and glutathione in the para- and endodormancy phases. Consistent trends in the content of reducing sugars can be elucidated for the different phenophases of dormancy, too. The untargeted approach with principle component analysis (PCA) clearly differentiates the different timings of dormancy giving further valuable information.

The α-amylase/trypsin inhibitors (ATIs) are discussed as being responsible for non-celiac wheat sensitivity (NCWS), besides being known as allergenic components for baker’s asthma. Different approaches for characterization and quantification including proteomics-based methods for wheat ATIs have been documented. In these studies generally the major ATIs have been addressed. The challenge of current study was then to develop a more comprehensive workflow encompassing all reviewed wheat-ATI entries in UniProt database. To substantially test proof of concept, 46 German and Turkish wheat samples were used. Two extractions systems based on chloroform/methanol mixture (CM) and under buffered denaturing conditions were evaluated. Three aspects were optimized, tryptic digestion, chromatographic separation, and targeted tandem mass spectrometric analysis (HPLC-MS/MS). Preliminary characterization with sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) documented the purity of the extracted ATIs with CM mixture and the amylase (60–80%)/trypsin (10–20%) inhibition demonstrated the bifunctional activity of ATIs. Thirteen (individual/common) biomarkers were established. Major ATIs (7–34%) were differently represented in samples. Finally, to our knowledge, the proposed HPLC-MS/MS method allowed for the first time so far the analysis of all 14 reviewed wheat ATI entries reported.

The detection and quantification of nut allergens remains a major challenge. The liquid chroma-tography tandem mass spectrometry (LC-MS/MS) is emerging as one of the most widely used methods, but sample preparation prior to the analysis is still a key issue. The objective of this work was to establish optimized protocols for extraction, tryptic digestion and LC-MS analysis of almond, cashew, hazelnut, peanut, pistachio and walnut samples. Ammonium bicar-bonate/urea extraction (Ambi/urea), SDS buffer extraction (SDS), polyvinylpolypyrroli-done (PVPP) extraction, trichloroacetic acid/acetone extraction (TCA/acetone) and chloro-form/methanol/sodium chloride precipitation (CM/NaCl) as well as the performances of con-ventional tryptic digestion and microwave-assisted breakdown were investigated. Overall, the protein extraction yields ranged from 14.9 ± 0.5 (almond extract from CM/NaCl) to 76.5 ± 1.3% (hazelnut extract from Ambi/urea). Electrophoretic profiling showed that the SDS extraction method clearly presented a high amount of extracted proteins in the range of 0–15 kDa, 15–35 kDa, 35–70 kDa and 70–250 kDa compared to the other methods. The linearity of the LC-MS methods in the range of 0 to 0.4 µg equivalent defatted nut flour was assessed and recovery of internal standards GWGG and DPLNV(d8)LKPR ranged from 80 to 120%. The identified bi-omarkers peptides were used to relatively quantifier selected allergenic protein form the inves-tigated nut samples. Considering the overall results, it can be concluded that SDS buffer allows a better protein extraction from almond, peanut and walnut samples while PVPP buffer is more appropriate for cashew, pistachio and hazelnut samples. It was also found that conventional overnight digestion is indicated for cashew, pistachio and hazelnut samples, while microwave assisted tryptic digestion is recommended for almond, hazelnut and peanut extracts.

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.