Coffea arabica and C. canephora discrimination in roasted and ground coffee from reference material candidates by real-time PCR

Evaluation of Reference Genes for Normalizing RT-qPCR and Analysis of the Expression Patterns of WRKY1 Transcription Factor and Rhynchophylline Biosynthesis-Related Genes in Uncaria rhynchophylla

Uncaria rhynchophylla (Miq.) Miq. ex Havil, a traditional medicinal herb, is enriched with several pharmacologically active terpenoid indole alkaloids (TIAs). At present, no method has been reported that can comprehensively select and evaluate the appropriate reference genes for gene expression analysis, especially the transcription factors and key enzyme genes involved in the biosynthesis pathway of TIAs in U. rhynchophylla. Reverse transcription quantitative PCR (RT-qPCR) is currently the most common method for detecting gene expression levels due to its high sensitivity, specificity, reproducibility, and ease of use. However, this methodology is dependent on selecting an optimal reference gene to accurately normalize the RT-qPCR results. Ten candidate reference genes, which are homologues of genes used in other plant species and are common reference genes, were used to evaluate the expression stability under three stress-related experimental treatments (methyl jasmonate, ethylene, and low temperature) using multiple stability analysis methodologies. The results showed that, among the candidate reference genes, S-adenosylmethionine decarboxylase (SAM) exhibited a higher expression stability under the experimental conditions tested. Using SAM as a reference gene, the expression profiles of 14 genes for key TIA enzymes and a WRKY1 transcription factor were examined under three experimental stress treatments that affect the accumulation of TIAs in U. rhynchophylla. The expression pattern of WRKY1 was similar to that of tryptophan decarboxylase (TDC) under ETH treatment. This research is the first to report the stability of reference genes in U. rhynchophylla and provides an important foundation for future gene expression analyses in U. rhynchophylla. The RT-qPCR results indicate that the expression of WRKY1 is similar to that of TDC under ETH treatment. It may coordinate the expression of TDC, providing a possible method to enhance alkaloid production in the future through synthetic biology.

New genetic markers for 100% arabica coffee demonstrate high discriminatory potential for InDel-HRM-based coffee authentication

Food authenticity is crucial in today's society, given the heightened consumer awareness and attention to the products they consume. Reliable and efficient techniques are needed to quickly detect potential food adulterations that can negatively impact product quality and economic value. Coffee, a globally traded agricultural product, holds immense economic importance, with an estimated value of USD 83 billion. It is widely consumed and recognized as a functional food that provides minerals (K, Mg, Mn, Cr), niacin, and antioxidants. However, the preferred coffee species, Coffea arabica, known for its superior drink quality, is often adulterated with Coffea canephora (Robusta and Conilon) beans, even in 100% Arabica coffee. To distinguish between these two coffee species, a comprehensive study was conducted using a robust approach to identify differences in Single-Ortholog Copy (SOC) based on InDel regions in these gene pairs. These differences were validated using a meticulous methodology that considered variations in amplicon size: electrophoretic profile, and high-resolution melting (HRM). The innovative combination of InDels and HRM resulted in highly distinctive HRM profiles, outperforming SNP-based methods previously used. The targeted InDel approach utilized in this study facilitated precise quantification of Coffea species beans with a detection sensitivity of 0.5%. The study's findings establish the reliability and accuracy in distinguishing between the two coffee species, showcasing the valuable application of InDels for quality control and ensuring the authenticity of coffee beans. This pioneering research contributes to the advancement of authenticity verification methods for both imported and exported coffee beans, as well as in future studies that require significant genetic differences between these species, such as C. arabica and C. canephora.

SHS-GC-MS applied in Coffea arabica and Coffea canephora blend assessment

Considering the great economic significance of Coffea arabica (arabica) associated with the lower production cost of C. canephora (conilon), blends of these coffees are commercially available to reduce costs and combine sensory attributes. Thus, analytical tools are required to ensure consistency between real and labeled compositions. In this sense, chromatographic methods based on volatile analysis using static headspace-gas chromatography-mass spectrometry (SHS-GC-MS) and Fourier transform infrared (FTIR) spectroscopy associated with chemometric tools were proposed for the identification and quantification of arabica and conilon blends. The peak integration from the total ion chromatogram (TIC) and extracted ion chromatogram (EIC) was compared in multivariate and univariate scenarios. The optimized partial least squares (PLS) models with uninformative variable elimination (UVE) and chromatographic data (TIC and EIC) have similar accuracy according to a randomized test, with prediction errors between 3.3% and 4.7% and R_p² > 0.98. There was no difference between the univariate models for the TIC and EIC, but the FTIR model presented a lower performance than GC-MS. The multivariate and univariate models based on chromatographic data had similar accuracy. For the classification models, the FTIR, TIC, and EIC data presented accuracies from 96% to 100% and error rates from 0% to 5%. Multivariate and univariate analyses combined with chromatographic and spectroscopic data allow the investigation of coffee blends.

Near-Infrared Spectroscopy Applied to the Detection of Multiple Adulterants in Roasted and Ground Arabica Coffee

Roasted coffee has been the target of increasingly complex adulterations. Sensitive, non-destructive, rapid and multicomponent techniques for their detection are sought after. This work proposes the detection of several common adulterants (corn, barley, soybean, rice, coffee husks and robusta coffee) in roasted ground arabica coffee (from different geographic regions), combining near-infrared (NIR) spectroscopy and chemometrics (Principal Component Analysis—PCA). Adulterated samples were composed of one to six adulterants, ranging from 0.25 to 80% (w/w). The results showed that NIR spectroscopy was able to discriminate pure arabica coffee samples from adulterated ones (for all the concentrations tested), including robusta coffees or coffee husks, and independently of being single or multiple adulterations. The identification of the adulterant in the sample was only feasible for single or double adulterations and in concentrations ≥10%. NIR spectroscopy also showed potential for the geographical discrimination of arabica coffees (South and Central America).

Reliable Discrimination of Green Coffee Beans Species: A Comparison of UV-Vis-Based Determination of Caffeine and Chlorogenic Acid with Non-Targeted Near-Infrared Spectroscopy

Species adulteration is a common problem in the coffee trade. Several attempts have been made to differentiate among species. However, finding an applicable methodology that would consider the various aspects of adulteration remains a challenge. This study investigated an ultraviolet–visible (UV-Vis) spectroscopy-based determination of caffeine and chlorogenic acid contents, as well as the applicability of non-targeted near-infrared (NIR) spectroscopy, to discriminate between green coffee beans of the Coffea arabica (Arabica) and Coffea canephora (Robusta) species from Java Island, Indonesia. The discrimination was conducted by measuring the caffeine and chlorogenic acid content in the beans using UV-Vis spectroscopy. The data related to both compounds was processed using linear discriminant analysis (LDA). Information about the diffuse reflectance (log 1/R) spectra of intact beans was determined by NIR spectroscopy and analyzed using multivariate analysis. UV-Vis spectroscopy attained an accuracy of 97% in comparison to NIR spectroscopy’s accuracy by selected wavelengths of LDA (95%). The study suggests that both methods are applicable to discriminate reliably among species.

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches.

A Critical Review on the Role of Food and Nutrition in the Energy Balance

The mass media has increasingly frequently suggested to the general population that specific foods or nutritional schemes are able to affect both human metabolism and energy expenditure, thus facilitating weight loss. This critical review is aimed at assessing available evidence on the roles of nutrients, food and dietary regimens in energy intake and energy expenditure. We queried the National Library of Medicine, the Cochrane Library, Excerpta Medica dataBASEand the Cumulative Index to Nursing and Allied Health Literature database, and a search strategy was performed by using database-specific subject headings and keywords. We found that available scientific evidence on these topics is scarce, and that the limited number of available studies often have poor methodological quality. Only a few foods show beneficial effects on metabolism and energy expenditure, as the human energy balance is complex and multifactorial. Finally, microbiota may interfere with the intake, use and expenditure of energy in the human body. Conclusive evidence is still lacking, and, at present, it is not possible to identify a food or a diet with a significant impact on human energy expenditure.