From the field to coffee cup: impact of planting design on chlorogenic acid isomers and other compounds in coffee beans and sensory attributes of coffee beverage

Investigating the role of chlorogenic acids and coffee type in coffee-induced teeth discoloration

OBJECTIVE

Coffee is one of the most popular beverages in the world, with millions of people consuming it every day. The effect of coffee on teeth discoloration has long been a concern for both coffee drinkers and dental professionals. To address this concern, this study aimed to investigate the role of chlorogenic acids (CGAs) and the type of coffee in coffee-induced teeth discoloration.

MATERIALS AND METHODS

High-performance liquid chromatography with a photodiode array detector was used to determine the CGA contents of instant coffee produced by five manufacturers (Starbucks, Dunkin' Donuts, Kanu, Ediya, Coffee Bean). A total of 180 bovine tooth specimens were immersed in the coffee samples for varying durations (3, 9, 24, 48, and 72 h), and the discoloration levels were measured using a spectrophotometer. A linear mixed-effects model analysis was used to determine the significance of L*, a*, and b* values in relation to the duration of coffee immersion and coffee type.

RESULTS

Both immersion time and coffee type had significant effects on tooth discoloration (p < 0.001), with some types of coffee being more strongly associated with tooth discoloration than others. The amount of CGAs present in coffee was found to be positively correlated with the degree of discoloration (p = 0.030).

CONCLUSIONS

Prolonged exposure to coffee can exacerbate teeth staining, and different types of coffee can cause varying degrees of discoloration. Furthermore, coffee with higher levels of CGAs may lead to greater tooth discoloration.

Evaluation of the behaviour of phenols and alkaloids in samples of roasted and ground coffee stored in different types of packaging: Implications for quality and shelf life

The most important factor in determining coffee quality and consumer choice is the flavour. During roasting, hundreds of simultaneous chemical reactions take place that contribute to the formation of the basic flavour of the coffee drink, imparting bitterness, astringency and acidity. The main chemical compounds responsible for these qualitative sensory properties are chlorogenic acids (CQAs), hydroxycinnamic acids and alkaloids. However, during storage, roasted and ground coffee can undergo several chemical and physical reactions that alter its flavour. This study focuses on LC-DAD analysis to investigate the effects of storing commercial coffee blends in different packaging, namely standard (multilayer film with aluminium barrier) and Eco-capsules. The results show relative stability of the phenolic and alkaloid fractions, although the CQA isomers behave differently and a decrease in caffeine and caffeic acid is observed during prolonged storage under 75% relative humidity compared to 65%, especially in Eco-friendly packaging.

Advances in Production of Hydroxycinnamoyl-Quinic Acids: From Natural Sources to Biotechnology

Hydroxycinnamoyl-quinic acids (HCQAs) are polyphenol esters formed of hydroxycinnamic acids and (-)-quinic acid. They are naturally synthesized by plants and some micro-organisms. The ester of caffeic acid and quinic acid, the chlorogenic acid, is an intermediate of lignin biosynthesis. HCQAs are biologically active dietary compounds exhibiting several important therapeutic properties, including antioxidant, antimicrobial, anti-inflammatory, neuroprotective, and other activities. They can also be used in the synthesis of nanoparticles or drugs. However, extraction of these compounds from biomass is a complex process and their synthesis requires costly precursors, limiting the industrial production and availability of a wider variety of HCQAs. The recently emerged production through the bioconversion is still in an early stage of development. In this paper, we discuss existing and potential future strategies for production of HCQAs.

Comparison of Different Extraction Techniques and Conditions for Optimizing an HPLC-DAD Method for the Routine Determination of the Content of Chlorogenic Acids in Green Coffee Beans

Chlorogenic acids (CGAs) are the main phenolic compounds found in green coffee beans. They are receiving more attention recently due to the proven health and nutrition benefits they offer, in addition to their role as markers for coffee quality. A relatively large number of studies are reported in the literature that are based on the analysis of these compounds. However, very limited research is dedicated to the evaluation of the performance of the analytical methods used, particularly the extraction procedures. Therefore, this work was dedicated to the comparison of different extraction techniques and conditions in order to evaluate their influence on the measured content of the three main CGAs in green coffee beans, namely, chlorogenic acid (5-CQA), neochlorogenic acid (3-CQA) and cryptochlorogenic acid (4-CQA). Five simple extraction techniques with affordable equipment were compared in order to develop a routine method suitable for most analytical and food analysis laboratories. The compared extraction techniques provided relatively similar extraction efficiency for the three compounds. However, due to the merits of ultrasonic-assisted extraction as a fast, effective, green, and economical technique, this was selected by comparing the extraction variables and developing an optimized routine method. The extraction solvent, temperature, time, solid-to-solvent ratio, and grinding treatments were the variables that were investigated. The extraction solvent and the solid-to-solvent ratio were found to be the most influencing variables that may improve the extraction efficiency to up to 50%. Based on this thorough investigation, an optimized method for the routine determination of the content of chlorogenic acids in green coffee beans was developed. The developed method is simple, fast, and efficient in the extraction of the three main CGAs.

Identification of Non-Volatile Compounds Generated during Storage That Impact Flavor Stability of Ready-to-Drink Coffee

Coffee brew flavor is known to degrade during storage. Untargeted and targeted LC/MS flavoromics analysis was applied to identify chemical compounds generated during storage that impacted the flavor stability of ready-to-drink (RTD) coffee. MS chemical profiles for sixteen RTD coffee samples stored for 0, 1, 2, and 4 months at 30 °C were modeled against the sensory degree of difference (DOD) scores by orthogonal partial least squares (OPLS) with good fit and predictive ability. Five highly predictive untargeted chemical features positively correlated to DOD were subsequently identified as 3-caffeoylquinic acid, 4-caffeoylquinic acid, 5-caffeoylquinic acid, 3-O-feruloylquinic acid, and 5-O-feruloylquinic acid. The increase in the six acidic compounds during storage was confirmed by sensory recombination tests to significantly impact the flavor stability of RTD coffee during storage. A decrease in pH, rather than an increase in total acidity, was supported to impact the coffee flavor profile.

Climate Change and Coffee Quality: Systematic Review on the Effects of Environmental and Management Variation on Secondary Metabolites and Sensory Attributes of Coffea arabica and Coffea canephora

Climate change is impacting crop performance and agricultural systems around the world with implications for farmers and consumers. We carried out a systematic review to synthesize evidence regarding the effects of environmental factors associated with climate change and management conditions associated with climate adaptation on the crop quality of a culturally-relevant perennial crop, coffee (Coffea arabica and Coffea canephora). Seventy-three articles were identified that addressed the study's research question including 42 articles on environmental factors, 20 articles on management conditions, and 11 articles on both. While variation was found between studies, findings highlight that coffee quality is vulnerable to changes in light exposure, altitude, water stress, temperature, carbon dioxide, and nutrient management. Both increases as well as decreases were found in secondary metabolites and sensory attributes that determine coffee quality in response to shifts in environmental and management conditions. The most consistent evidence identified through this systematic review includes the following two trends: (1) increased altitude is associated with improved sensory attributes of coffee and; (2) increased light exposure is associated with decreased sensory attributes of coffee. Research gaps were found regarding the effects of shifts in carbon dioxide, water stress, and temperature on the directionality (increase, decrease, or non-linear) of coffee quality and how this varies with location, elevation, and management conditions. This systematic review further identified the following research needs: (1) long-term studies that examine the interactive effects of multiple environmental factors and management conditions on coffee quality; (2) studies that examine the interaction between sensory attributes and secondary metabolites that determine coffee quality and; (3) studies on the feasibility of various climate-adaptation strategies for mitigating the effects of climate change on coffee quality. Evidence-based innovations are needed to mitigate climate impacts on coffee quality toward enhanced sustainability and resilience of the coffee sector from farm to cup.

Acids in coffee: A review of sensory measurements and meta-analysis of chemical composition

Coffee contains a variety of organic acids (OAs) and chlorogenic acids (CGAs) that contribute to overall sensory properties. Large variations in preparation and measurement methodology across the literature complicate interpretation of general trends. Here, we perform a systematic review and meta-analysis of the published literature to elucidate the concentrations of OAs and CGAs in both Coffea arabica (arabica) and Coffea canephora (robusta), for both green coffee and roasted coffee at multiple roast levels. A total of 129 publications were found to report acid concentration measurements, yielding 8,634 distinct data points. Analysis of the full data set reveals several trends. First, roasted robusta has considerably more acidic compounds than arabica with 2 to 5 times as much total OAs, and much larger amounts of formic and acetic acid. As for CGAs, in both arabica and robusta 5-CQA is the major component, and progressive roasting decreases the concentration of all CGAs. The total amount of CGA present was more dependent on roast level than the type of coffee (arabica vs. robusta). Overall, this meta-analysis suggests that the increases in certain OAs with roast level might play more of a role in the sensory profile of dark roast coffees than previously suspected.

Evaluation of chemical properties of intact green coffee beans using near-infrared spectroscopy

BACKGROUND

The chemical compounds in coffee are important indicators of quality. Its composition varies according to several factors related to the planting and processing of coffee. Thus, this study proposed to use near-infrared spectroscopy (NIR) associated with partial least squares (PLS) regression to estimate quickly some chemical properties (moisture content, soluble solids, and total and reducing sugars) in intact green coffee samples. For this, 250 samples produced in Brazil were analyzed in the laboratory by the standard method and also had their spectra recorded.

RESULTS

The calibration models were developed using PLS regression with cross-validation and tested in a validation set. The models were elaborated using original spectra and preprocessed by five different mathematical methods. These models were compared in relation to the coefficient of determination, root mean square error of cross-validation (RMSECV), root mean square error of test set validation (RMSEP), and ratio of performance to deviation (RPD) and demonstrated different predictive capabilities for the chemical properties of coffee. The best model was obtained to predict grain moisture and the worst performance was observed for the soluble solids model. The highest determination coefficients obtained for the samples in the validation set were equal to 0.810, 0.516, 0.694 and 0.781 for moisture, soluble solids, total sugar, and reducing sugars, respectively.

CONCLUSION

The statistics associated with these models indicate that NIR technology has the potential to be applied routinely to predict the chemical properties of green coffee, and in particular, for moisture analysis. However, the soluble solid and total sugar content did not show high correlations with the spectroscopic data and need to be improved. © 2020 Society of Chemical Industry.

The main effects of elevated CO2 and soil-water deficiency on 1H NMR-based metabolic fingerprints of Coffea arabica beans by factorial and mixture design

The metabolic response of Coffea arabica trees in the face of the rising atmospheric concentration of carbon dioxide (CO₂) combined with the reduction in soil-water availability is complex due to the various (bio)chemical feedbacks. Modern analytical tools and the experimental advance of agronomic science tend to advance in the understanding of the metabolic complexity of plants. In this work, Coffea arabica trees were grown in a Free-Air Carbon Dioxide Enrichment dispositive under factorial design (2²) conditions considering two CO₂ levels and two soil-water availabilities. The ¹H NMR mixture design-fingerprinting effects of CO₂ and soil-water levels on beans were strategically investigated using the principal component analysis (PCA), analysis of variance (ANOVA) - simultaneous component analysis (ASCA) and partial least squares-discriminant analysis (PLS-DA). From the ASCA, the CO₂ factor had a significant effect on changing the ¹H NMR profile of fingerprints. The soil-water factor and interaction (CO₂ × soil-water) were not significant. ¹H NMR fingerprints with PCA, ASCA and PLS-DA analysis determined spectral profiles for fatty acids, caffeine, trigonelline and glucose increases in beans from current CO₂, while quinic acid/chlorogenic acids, malic acid and kahweol/cafestol increased in coffee beans from elevated CO₂. PLS-DA results revealed a good classification performance between the significant effect of the atmospheric CO₂ levels on the fingerprints, regardless of the soil-water availabilities. Finally, the PLS-DA model showed good prediction ability, successfully classifying validation data-set of coffee beans collected over the vertical profile of the plants and included several fingerprints of different extracting solvents. The results of this investigation suggest that the association of experimental design, mixture design, PCA, ASCA and PLS-DA can provide accurate information on a series of metabolic changes provoked by climate changes in products of commercial importance, in addition to minimizing the extra work necessary in classic analytical approaches, encouraging the development of similar strategies.