Influence of maturation and roasting on the quality and chemical composition of new conilon coffee cultivar by chemometrics

Maillard reaction products of soybean protein hydrolysates and reducing sugar: Structure and flavor insights

Maillard reaction products (MRPs) were prepared at high temperatures using soybean protein hydrolysates (SPH) and reducing pentose (xylose and arabinose), hexose (galactose and glucose), and disaccharide (maltose), and their potential as flavoring in plant protein foods was evaluated. The results indicated that, after sugar was involved in the reaction, the unfolding of proteins enabled aromatic amino acid residues to enter a more hydrophobic environment, contributing to the reduction of bitterness in MRPs and formation of caramelization. This effect was partially attributed to the interaction forces, hydrogen bonds and van der Waals forces, that existed between the sugars and SPH involved in Maillard reaction. More basic amino acid residues interacted with pentose during the reaction, which exhibited faster reaction rate and promoted the formation of pyrazines and oxygen containing compounds, thereby contributing to meaty, roasted and caramelized flavors. Trimethyl pyrazine, 3-ethyl-2,5-dimethylpyrazine, 2-methylpyrazine, and 2-heptanone were the most abundant in pentose MRPs, and these volatile compounds were positively correlated with umami and richness. Overall, MRPs prepared with arabinose may serve as a potential meaty flavoring with notable umami, and hexose contributed to the enrichment of nutty flavor profiles, while the MRPs formed by disaccharide exhibited the characteristics of superior fruity aromas. MRPs from different reducing sugar may be used to develop different food ingredients.

Multiplatform Path-ComDim study of Capixaba, indigenous and non-indigenous Amazonian Canephora coffees

Integrating diverse measurement platforms can yield profound insights. This study examined Brazilian Canephora coffees from Rondônia (Western Amazon) and Espírito Santo (southeast), hypothesizing that geographical and climatic differences along botanical varieties significantly impact coffee characteristics. To test this, capixaba, indigenous, and non-indigenous Amazonian canephora coffees were analyzed using nine distinct platforms, including both spectroscopic techniques and sensory evaluations, to obtain results that are more informative and complementary than conventional single-method analyses. By applying multi-block Path-ComDim analysis to the multiple data sets, we uncovered crucial correlations between instrumental and sensory measurements. This integrated approach not only confirmed the hypothesis but also demonstrated that combining multiple data sets provides a more nuanced understanding of coffee profiles than traditional single-method analyses. The results underscore the value of multiplatform approaches in enhancing coffee quality evaluation, offering a more detailed and comprehensive view of coffee characteristics that can drive future research and improve industry standards.

Enhancing mass spectrometry interpretability by ComDim-ICA multi-block analysis: Geographical and varietal traceability of Brazilian Coffea canephora

Mass spectrometry can gain analytical interpretability by studying complementarity and synergy between the data obtained by the same technique. To explore its potential in an untargeted metabolomic application, the objective of this work was to obtain organic and aqueous coffee extracts of three coffee Canephora groups produced in Brazil with distinctive aspects: geographical origin and botanical variety. Aqueous and organic extracts of roasted coffee beans were analyzed by direct infusion electrospray ionization mass spectrometry. Due to the large number of samples, the injector of the liquid chromatography system was used to automate the analysis. The column was removed, and a peak tube was added to connect the system directly to the mass spectrometer to inject both polar and nonpolar fractions of the coffee extracts individually. The technique provided characteristic fingerprinting mass spectra that not only allowed for differentiation of geographical origins but also between robusta and conilon botanical varieties. The mass spectra of the organic and water extracts represented two separate data blocks to be analyzed by the ComDim-ICA multi-block data analysis method. While the classical ComDim is based on applying PCA to the iteratively reweighted concatenated matrices, in the ComDim-ICA, the factorization is done using independent components analysis, which promotes specific improvements since it is based on extracting components that are statistically independent of one another. The results highlighted by ComDim-ICA show that both water and organic extracts contributed with important ions to the characterization of the coffee composition. However, the results revealed a high variability of metabolomic composition within each botanical variety (Robusta Amazônico and Conilon Capixaba) and geographical provenance (Rondônia indigenous-1, Rondônia non-indigenous-2 and Espírito Santo-3). Even so, water mass spectra differentiated the botanical variety Conilon from Robusta based on significant ions related to trigonelline, caffeic acid, caffeoylquinic acid, and methylpyridinium; both water and organic mass spectra differentiated Rondônia indigenous from Rondônia non-indigenous and Espírito Santo Conilon based on significant ions related to benzoic acid, pentose, coumaric acid, caffeine in the organic extract and malonic acid, pentose, caffeoylquinic acid, methyl pyridinium, caffeine, and sucrose present in the water extract. With the proposed approach acquiring ion fingerprints of different coffee extracts and their subsequent analysis by ComDim-ICA, new complementary chemical aspects of Brazilian Coffea canephora were put in evidence.

Authentication of indigenous Brazilian specialty canephora coffees using smartphone image analysis

The prevention of coffee fraud through the use of digital and intelligence-based technologies is an analytical challenge because depending on the adulterant, visual inspection is unreliable in roasted and ground coffee due to the similarity in color and texture of the materials used. In this work, a 3D-printed apparatus for smartphone image acquisiton is proposed. The digital images are used to authenticate the geographical origin of indigenous canephora coffees produced at Amazon region, Brazil, against canephora coffees from Espírito Santo, Brazil, and to capture the adulteration of indigenous samples. The results evidenced that the technology is favorable to identify the geographical origin and adulteration with multiple substances using smartphone technology. Pure coffees were adulterated with arabica coffee, spent coffee ground, low-quality Canephora coffee, coffee husks, açaí, corn, and soybean in increasing proportions of 10, 20, 30, 40, 50, 60, and 70 %. These adulterants were roasted and grounded similarly to Canephora coffees to mimetize a highly-sophisticated fraud. The images were converted into Red-Green-Blue (RGB) fingerprinting and used as analytical response to construct Data-Driven Soft Independent Modeling of Class Analogy (DD-SIMCA) models. A total of 95 % of all target and non-target samples in the test set were correctely identified, aiding producers and consumers in ensuring accurate labeling and supporting traditional communities economically and culturally. Smartphone-based method demonstrated potential to innovate the coffee safety control representing a new analytical tecnology.

An overview on the Brazilian Coffea canephora scenario and the current chemometrics-based spectroscopic research

This review explores the historical, botanical, sensory, and quality aspects of Coffea canephora, with a focus on Brazil's rise as a producer of specialty canephora coffees in the Amazon region, Espírito Santo, and Bahia. Brazil has gained global recognition through the first geographical indications for canephora: Matas de Rondônia for robusta amazônico coffee and Espírito Santo for conilon coffee. Despite this, comprehensive insights into how variety, terroir, environmental conditions, and cultivation practices influence the chemical and sensory attributes of Brazilian canephora remain underdeveloped compared to well-studied arabica coffee. Producers and researchers are working to elevate canephora coffees to higher market levels, despite technological, production, and perception challenges stemming from its historical reputation for poor quality. Ensuring the sustainability of Amazonian canephora coffee without deforestation is particularly challenging due to the need to verify practices across numerous small-scale farms. There is also a critical need for standardized production and tasting protocols for Brazilian canephora, leveraging local expertise and professional cuppers to ensure consistent quality and reliable sustainability claims. Significant opportunities exist in valuing the production chain of geographically unique canephora coffees, which could increase specialty exports, enhance economic prospects for local farmers, and support Amazon preservation. Recognizing and marketing these coffees as premium products with unique flavor profiles can boost their global appeal. Another challenge lies in establishing new specialty standards for soluble coffee from specialty canephora to meet consumer demands for convenience without compromising taste or ethical standards. In such a scenario, several analytical methods have been suggested to identify high-quality variants, combating their stigmatization. The potential of spectroscopy techniques and chemometrics-based data science is highlighted in confirming coffee quality, authenticity, traceability, and geographical origin, enhancing model interpretation and predictive accuracy through synergistic and complementary information. Non-targeted spectroscopic analyses, providing comprehensive spectral fingerprints, are contrasted with targeted analyses. Overall, this review offers valuable insights for the coffee scientific community, exporters, importers, roasters, and consumers in recognizing the potential of Brazilian canephora coffees.

Electronic Prediction of Chemical Contaminants in Aroma of Brewed Roasted Coffee and Quantification of Acrylamide Levels

The aim of this research was to apply an electronic device as indirect predictive technology to evaluate toxic chemical compounds in roasted espresso coffee. Fresh coffee beans were subjected to different thermal treatments and analyzed to determine volatile organic compounds, content of acrylamide and 5-hydroxymethylfurfural, sensory characteristics and electronic nose data. In total, 70 different volatile compounds were detected and grouped into 15 chemical families. The greatest percentage of these compounds were furans, pyrazines, pyridines and aldehydes. The positive aroma detected had the intensity of coffee odor and a roasted aroma, whereas the negative aroma was related to a burnt smell. A linear relationship between the toxic substances and the sensory defect was established. A high sensory defect implied a lower content of acrylamide and a higher content of 5-hydroxymethylfurfural. Finally, electronic signals were also correlated with the sensory defect. This relationship allowed us to predict the presence of these contaminants in the roasted coffee beverage with an indirect method by using this electronic device. Thus, this device may be useful to indirectly evaluate the chemical contaminants in coffee beverages according to their sensory characteristics.