Green Synthesis of Selenium Nanoparticles using Green Coffee Beans: An Optimization Study.

In this study, ultrasonication extraction of some bioactive compounds from green coffee beans was optimized with the response surface method using Box-Behnken experimental design. The best condition was selected as 90.90 W ultrasonic power, 33.63 min sonication time and 30 % solid concentration. The responses obtained under optimum conditions had TPC, DPPH and CUPRAC values identified as 6603.33±2025.94 ppm GAE, 9638.31±372.17 ppm TE and 98.83 mmol, respectively. Microwave-assisted selenium nanoparticle production was carried out using the extract obtained under optimized conditions. The produced selenium nanoparticles showed absorbance between 350-400 nm. The surface morphology and size of the nanoparticles were determined by transmission electron microscopy (TEM) and spherical nanoparticles of about 100 nm were produced. Functional groups affecting the reduction were determined by FTIR analysis. In addition, the produced selenium nanoparticles had amorphous (non-uniform) structure and could maintain their stability at high temperatures.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract.

INTRODUCTION: Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. OBJECTIVES: The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. MATERIAL AND METHODS: In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. RESULTS: The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. CONCLUSION: The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Climate and disease: tackling coffee brown-eye spot with advanced forecasting models.

BACKGROUND: Climate influences the interaction between pathogens and their hosts significantly. This is particularly evident in the coffee industry, where fungal diseases like Cercospora coffeicola, causing brown-eye spot, can reduce yields drastically. This study focuses on forecasting coffee brown-eye spot using various models that incorporate agrometeorological data, allowing for predictions at least 1 week prior to the occurrence of disease. Data were gathered from eight locations across São Paulo and Minas Gerais, encompassing the South and Cerrado regions of Minas Gerais state. In the initial phase, various machine learning (ML) models and topologies were calibrated to forecast brown-eye spot, identifying one with potential for advanced decision-making. The top-performing models were then employed in the next stage to forecast and spatially project the severity of brown-eye spot across 2681 key Brazilian coffee-producing municipalities. Meteorological data were sourced from NASA's Prediction of Worldwide Energy Resources platform, and the Penman-Monteith method was used to estimate reference evapotranspiration, leading to a Thornthwaite and Mather water-balance calculation. Six ML models - K-nearest neighbors (KNN), artificial neural network multilayer perceptron (MLP), support vector machine (SVM), random forests (RF), extreme gradient boosting (XGBoost), and gradient boosting regression (GradBOOSTING) - were employed, considering disease latency to time define input variables. RESULTS: These models utilized climatic elements such as average air temperature, relative humidity, leaf wetness duration, rainfall, evapotranspiration, water deficit, and surplus. The XGBoost model proved most effective in high-yielding conditions, demonstrating high precision and accuracy. Conversely, the SVM model excelled in low-yielding scenarios. The incidence of brown-eye spot varied noticeably between high- and low-yield conditions, with significant regional differences observed. The accuracy of predicting brown-eye spot severity in coffee plantations depended on the biennial production cycle. High-yielding trees showed superior results with the XGBoost model (R2 = 0.77, root mean squared error, RMSE = 10.53), whereas the SVM model performed better under low-yielding conditions (precision 0.76, RMSE = 12.82). CONCLUSION: The study's application of agrometeorological variables and ML models successfully predicted the incidence of brown-eye spot in coffee plantations with a 7 day lead time, illustrating that they were valuable tools for managing this significant agricultural challenge. © 2024 Society of Chemical Industry.

Using underutilized residues of coffee to obtain valuable dietary and antioxidant bioactive compounds.

BACKGROUND: Coffee cultivation and agroindustry generate residues that are rich in several metabolites. These compounds, such as phenolic compounds and alkaloids, are known for their antioxidant activity and are usually consumed as nutraceuticals. The purpose of this study was to evaluate the occurrence of chemical and antioxidant components of low-pruned coffee stems under different fertilizer regimes. Extractives and lignin composition, histochemical, chromatographic, and antioxidant analyses were performed. RESULTS: Multiple compounds were found to accumulate in the stems of coffee trees. Furthermore, the presence of phenolic compounds such as chlorogenic acid, vanillin, resveratrol, and the alkaloids caffeine and trigonelline varied depending on the type of fertilization. In all samples examined, optimal performance was observed at the highest tested concentration (500 µg mL-1 ). All samples analyzed presented a great performance at the highest concentration tested (500 µg mL-1 ), with the dose 70% and the dose 100%, which is the recommended for the culture, showing the highest values for most of the concentrations and the best half-maximal inhibitory concentration (IC50 ) when compared with the other samples tested. CONCLUSION: As shown in the results, the reuse of stem residues as antioxidant material, with the potential to be profitable, and has the added benefit of providing a sustainable destination for material that until now has been underutilized. © 2023 Society of Chemical Industry.

Models for predicting coffee yield from chemical characteristics of soil and leaves using machine learning.

BACKGROUND: Coffee farming constitutes a substantial economic resource, representing a source of income for several countries due to the high consumption of coffee worldwide. Precise management of coffee crops involves collecting crop attributes (characteristics of the soil and the plant), mapping, and applying inputs according to the plants' needs. This differentiated management is precision coffee growing and it stands out for its increased yield and sustainability. RESULTS: This research aimed to predict yield in coffee plantations by applying machine learning methodologies to soil and plant attributes. The data were obtained in a field of 54.6 ha during two consecutive seasons, applying varied fertilization rates in accordance with the recommendations of soil attribute maps. Leaf analysis maps also were monitored with the aim of establishing a correlation between input parameters and yield prediction. The machine-learning models obtained from these data predicted coffee yield efficiently. The best model demonstrated predictive fit results with a Pearson correlation of 0.86. Soil chemical attributes did not interfere with the prediction models, indicating that this analysis can be dispensed with when applying these models. CONCLUSION: These findings have important implications for optimizing coffee management and cultivation, providing valuable insights for producers and researchers interested in maximizing yield using precision agriculture. © 2024 Society of Chemical Industry.

Feasibility of using colorimetric devices for whole and ground coffee roasting degrees prediction.

BACKGROUND: Coffee roasting is one of the crucial steps in obtaining a high-quality product as it forms the product's color and flavor characteristics. Roast control is made by visual inspection or traditional instruments such as the Agtron spectrophotometer, which can have high implementation costs. Therefore, the present study evaluated colorimetric approaches (a bench colorimeter, smartphone digital images, and a colorimetric sensor) to predict the Agtron roasting degrees of whole and ground coffee. Two calibration approaches were assessed, that is, multiple linear regression and least-squares support vector machine. For that, 70 samples of whole and ground roasted coffees comprising the Agtron roasting range were prepared. RESULTS: The results showed that all three colorimetric acquisition types were efficient for the model building, but the bench colorimeter and the smartphone digital images generally performed with good determination coefficients and low errors as measured by external validation. For the whole bean coffee, the best model presented a determination coefficient (R2) of 0.99 and a root-mean-squared error (RMSE) of 1.91%, while R2 of 0.99 and RMSE of 0.87% was obtained for ground coffee, both using the colorimeter. CONCLUSION: The obtained models presented good prediction capability, as assessed by external validation and randomization tests. The obtained findings point to an alternative for coffee roasting monitoring that can lead to higher digitalization and local control of the process, even for smaller producers, due to its lower costs. © 2024 Society of Chemical Industry.

Profiling flavor characteristics of cold brew coffee with GC-MS, electronic nose and tongue: effect of roasting degrees and freeze-drying.

BACKGROUND: Roasting is an important process in the formation of coffee flavor characteristics, which determines the quality of coffee and consumer acceptance. However, the influence of roasting degree on the flavor characteristics of cold brew coffee has not been fully described. RESULTS: In the present study, the flavor characteristics of cold brew coffee with different roasting degrees were compared in detail by using chromatographic and electronic sensory approaches, and the flavor changes induced by freeze-drying were investigated. Pyrazine and heterocyclic compounds were the main aroma compounds in coffee, and gradually dominated with the increase of roasting. Pyridine was consistently present in cold brew coffees of different roasting degrees and showed significant gradient of quantity accumulation. Aroma compounds such as pyrazine, linalool and furfuryl acetate were the main contributors to coffee roasting, floral and fruity flavor. Freeze-drying preserved the fruity and floral aromas of medium-roasted cold brew coffee, whereas reducing the bitterness, astringency and acidity properties that are off-putting to consumers. CONCLUSION: The higher consumer acceptance and enjoyment in medium roast cold brew coffee may be related to its stronger floral and fruity aroma. The aroma profile qualities of freeze-drying processed medium roasted cold brewed coffee were more dominant and more suitable for freeze-drying processing than medium dark roasting. Application of freeze-drying for cold brew coffee will promote the convenience of drinking. The present study provides valuable technical guidance in improving the flavor and quality of cold brew coffee, and also promotes its commercialization process. © 2024 Society of Chemical Industry.

Yeasts are essential for mucilage degradation of coffee beans during wet fermentation.

During wet fermentation, mucilage layers in coffee cherries must be removed completely. To explain mucilage degradation, several controversial hypotheses have been proposed. The aim of this work was to improve our understanding of the kinetics of mucilage breakdown. Pulped coffee beans were wet fermented with seven different treatments for 36 h. Endogenous bacteria and yeasts are selectively suppressed, and pectinases or lactic acid are added. They also involve maintaining the beans at pH 7 throughout fermentation and using spontaneous fermentation without additives as a control. During spontaneous fermentation, yeast and lactic acid bacteria were detected and significantly increased to 5.5 log colony-forming units (CFU)/mL and 5.2 log CFU/mL, respectively. In the first 12 h of fermentation, there was a significant degree of endogenous pectinolytic activity, which resulted in partly destroyed beans in the absence of microorganisms. By adding pectinase and lactic acid to the fermentation mass, the breakdown process was accelerated in less than 8 h. When yeast was present throughout the fermentation, complete degradation was achieved. Bacteria played no critical role in the degradation. Klebsiella pneumoniae and Erwinia soli were found in a lower population and showed weaker pectinolytic activities compared to Hanseniaspora uvarum and Pichia kudriavzevii. During wet fermentation, mucilage degradation appears to be mediated by endogenous enzymes at the early stage, whereas microbial contributions, mainly yeasts, occur subsequently. H. uvarum and P. kudriavzevii may be promising candidates to be tested in future studies as coffee starter cultures to better control the mucilage degradation process.

Identification of potential quality markers in Indonesia's Arabica specialty coffee using GC/MS-based metabolomics approach.

INTRODUCTION: The cupping test is a widely used method for quality assessment of Arabica coffee. However, the cupping test is limited by the low number of certified panelists and the low throughput. Therefore, an analytical-based quality assessment may be a promising tool to complement the cupping test. A present, there is no report investigating quality marker candidates, focusing only on "specialty" grade Arabica coffee from Indonesia. OBJECTIVE: This study identified the potential quality marker(s) in Arabica Specialty coffee at different stages (green beans, roasted beans, and brewed coffee. METHODS: The metabolite profiles of ten different Arabica specialty-grade coffees were analyzed with different cup scores using gas chromatography-mass spectrometry (GC/MS). From the ten samples, green coffee beans, roasted coffee beans, and brewed coffee were selected. In addition, an orthogonal projection to latent structure (OPLS) regression analysis was conducted to obtain a potential quality marker based on the variable importance in projection (VIP). The potential quality marker(s) were validated by GC/MS metabolome profiling and OPLS analysis of different sets of samples consisting of 35 Arabica specialty-grade coffee samples. RESULTS: In Arabica coffee samples, the OPLS model of the three stages showed galactinol to have a high VIP score. Galactinol showed a consistent positive correlation with cup scores at all stages of coffee production (green beans, roasted beans, and brewed coffee). The correlation suggests galactinol is a potential quality marker after further validation using different samples. CONCLUSION: GC/MS combined with OPLS regression analysis suggested galactinol as a quality marker and provide an early screening method for Arabica coffee quality that complements the cupping test performed by certified panelists.

Current strategies to guarantee the authenticity of coffee.

As they become more health conscious, consumers are paying increasing attention to food quality and safety. In coffee production, fraudulent strategies to reduce costs and maximize profits include mixing beans from two species of different economic value, the addition of other substances and/or foods, and mislabeling. Therefore, testing for coffee authenticity and detecting adulterants is required for value assessment and consumer protection. Here we provide an overview of the chromatography, spectroscopy, and single-nucleotide polymorphism-based methods used to distinguish between the major coffee species Arabica and Robusta. This review also describes the techniques applied to trace the geographical origin of coffee, based mainly on the chemical composition of the beans, an approach that can discriminate between coffee-growing regions on a continental or more local level. Finally, the analytical techniques used to detect coffee adulteration with other foods and/or coffee by-products are discussed, with a look at the practice of adding pharmacologically active compounds to coffee, and their harmful effects on health.

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.

Naringin from Coffee Inhibits Foodborne Aspergillus fumigatus via the NDK Pathway: Evidence from an In Silico Study.

In the tropics, coffee has been one of the most extensively cultivated economic crops, especially Arabica coffee (Coffea arabica L.). The coffee pulp, which includes phytochemicals with a proven antifungal action, is one of the most insufficiently utilized and neglected byproducts of coffee refining. In the current experiment, we carried out in silico screening of the isolated Arabica coffee phytochemicals for antifungal activity against Aspergillus fumigatus: a foodborne fungus of great public health importance. As determined by the molecular docking interactions of the library compounds indicated, the best interactions were found to occur between the nucleoside-diphosphate kinase protein 6XP7 and the test molecules Naringin (-6.771 kcal/mol), followed by Epigallocatechin gallate (-5.687 kcal/mol). Therefore, Naringin was opted for further validation with molecular dynamic simulations. The ligand-protein complex RMSD indicated a fairly stable Naringin-NDK ligand-protein complex throughout the simulation period (2-16 Å). In ADME and gastrointestinal absorbability testing, Naringin was observed to be orally bioavailable, with very low intestinal absorption and a bioavailability score of 0.17. This was further supported by the boiled egg analysis data, which clearly indicated that the GI absorption of the Naringin molecule was obscure. We found that naringin could be harmful only when swallowed at a median lethal dose between 2000 and 5000 mg/kg. In accordance with these findings, the toxicity prediction reports suggested that Naringin, found especially in citrus fruits and tomatoes, is safe for human consumption after further investigation. Overall, Naringin may be an ideal candidate for developing anti-A. fumigatus treatments and food packaging materials. Thus, this study addresses the simultaneous problems of discarded coffee waste management and antifungal resistance to available medications.

Chemical and Biological Characterization of Green and Processed Coffee Beans from Coffea arabica Varieties.

Coffee is one of the most consumed beverages in the world; its production is based mainly on varieties of the Coffea arabica species. Mexico stands out for its specialty and organic coffee. In Guerrero, the production is done by small indigenous community cooperatives that market their product as raw material. Official Mexico Standards stipulate the requirements for its commercialization within the national territory. In this work, the physical, chemical, and biological characterizations of green, medium, and dark roasted beans from C. arabica varieties were carried out. Analysis by HPLC showed higher chlorogenic acid (55 mg/g) and caffeine (1.8 mg/g) contents in the green beans of the Bourbon and Oro Azteca varieties. The caffeine (3.88 mg/g) and melanoidin (97 and 29 mg/g) contents increased according to the level of roasting; a dissimilar effect was found in the chlorogenic acid content (14.5 mg/g). The adequate nutritional content and the sensory evaluation allowed the classification of dark-roasted coffee as premium coffee (84.25 points) and medium-roasted coffee as specialty coffee (86.25 points). The roasted coffees presented antioxidant activity without cytotoxic effects; the presence of CGA and caffeine supports the beneficial effects of drinking coffee. The results obtained will serve as a basis for making decisions on improvements to the coffees analyzed.

Enhancing Bioactivity and Conjugation in Green Coffee Bean (Coffea arabica) Extract through Cold Plasma Treatment: Insights into Antioxidant Activity and Phenolic-Protein Conjugates.

Cold plasma technology is gaining attention as a promising approach to enhancing the bioactivity of plant extracts. However, its impact on green coffee bean extracts (GCBEs) still needs to be explored. In this study, an innovative underwater plasma jet system was employed to investigate the effects of cold plasma on Coffea arabica GCBEs, focusing on the conjugation reflected by the change in composition and bioactivity. The DPPH radical scavenging antioxidant activity exhibited a gradual increase with plasma treatment up to 35 min, followed by a decline. Remarkably, at 35 min, the plasma treatment resulted in a significant 66% increase in the DPPH radical scavenging activity of the GCBE. The total phenolic compound content also displayed a similar increasing trend to the DPPH radical scavenging activity. However, the phenolic profile analysis indicated a significant decrease in chlorogenic acids and caffeine. Furthermore, the chemical composition analysis revealed a decrease in free amino acids, while sucrose remained unchanged. Additionally, the SDS-PAGE results suggested a slight increase in protein size. The observed enhancement in antioxidant activity, despite the reduction in the two major antioxidants in the GCBE, along with the increase in protein size, might suggest the occurrence of conjugation processes induced by plasma, particularly involving proteins and phenolic compounds. Notably, the plasma treatment exhibited no adverse effects on the extract's safety, as confirmed by the MTT assay. These findings indicate that cold plasma treatment holds significant promise in improving the functional properties of GCBE while ensuring its safety. Incorporating cold plasma technology into the processing of natural extracts may offer exciting opportunities for developing novel and potent antioxidant-rich products.

Investigation of Bioactive Complexes of Chitosan and Green Coffee Bean or Artichoke Extracts.

The formation of water-insoluble complexes between chitosan (ChS) and caffeoylquinic acid (CQ) derivatives present in artichoke (AE) and green coffee bean (GCBE) extracts was investigated by the equilibrium adsorption method. The UPLC/HPLC analysis revealed that the phenolic compounds accounted for 8.1% and 74.6% of AE and GCBE respectively, and CQ derivatives were the predominant compounds. According to the applied Langmuir adsorption model, anionic compounds present in natural extracts were adsorbed onto the active centers of ChS, i.e., primary amino groups. The driving forces of adsorption were electrostatic interactions between cationic groups of ChS and anionic compounds of natural extracts. Chromatographic analysis revealed that not only CQ derivatives, but also other phenolic compounds of natural extracts were attached to ChS. The release of adsorbed compounds into different media as well as the bioactive properties of complexes were also studied. With the immobilization of bioactives onto ChS, increased and prolonged ABTS•+ radical scavenging activity and decreased antifungal activity against Fusarium graminearum and Botrytis cinerea were observed compared to those of ChS. The findings of the current study highlight that the adsorption approach could be used to successfully prepare water-insoluble complexes of ChS and components of natural extracts with prolonged antioxidant activity.

Influence of Post-Harvest Processing on Functional Properties of Coffee (Coffea arabica L.).

Coffee is one of the most popular beverages worldwide, valued for its sensory properties as well as for its psychoactive effects that are associated with caffeine content. Nevertheless, coffee also contains antioxidant substances. Therefore, it can be considered a functional beverage. The aim of this study is to evaluate the influence of four selected post-harvest coffee fruit treatments (natural, full washed, washed-extended fermentation, and anaerobic) on the antioxidant and psychoactive properties of Arabica coffee. Additionally, the impact of coffee processing on the selected quality parameters was checked. For this purpose, results for caffeine content, total phenolic content (TPC), DPPH assay, pH, titratable acidity, and water content were determined. The results show that natural and anaerobic processing allow the highest caffeine concentration to be retained. The selection of the processing method does not have a significant influence on the TPC or antiradical activity of coffee. The identified differences concerning water content and pH along with lack of significant discrepancies in titratable acidity may have an influence on the sensory profile of coffee.

The effect of post-brew holding time and carafe type on the sensory properties of drip brew coffee.

BACKGROUND: Coffee quality is believed to degrade quickly after brewing, and retail establishments discard unsold brewed coffee after a specified holding time period, sometimes as short as 30 min. We used trained sensory panels to evaluate the flavor profiles of light, medium, and dark roast coffees held in three different carafe types (glass on hot plate, thermal jacket, and vacuum insulated) for times ranging from 15 min to 3 h. Furthermore, a panel of 93 coffee-industry professionals performed a blind evaluation of fresh (30 min) versus held (180 min) coffee for overall liking and attribute level adequacy. RESULTS: Sourness increased over time, consistent with acidity increasing over time (i.e., higher titratable acidity, lower pH), but only for the light and medium roasts. Dark roasted coffee became significantly more acidic over 3 h post-brew but was not perceived as more sour over time by the sensory panel. Variations were observed between the thermal jacket and vacuum carafes for the light and dark roast, but few differences were observed with storage type in the medium roast. Surprisingly, the panel of coffee industry professionals showed no preference for fresh over held. CONCLUSIONS: More sensory attributes decreased than increased over time, suggesting that the primary concern with loss of quality during coffee holding may be the loss of volatile aroma compounds. Hedonic ratings suggest that even if the changes over time are noticeable, they may not negatively impact overall liking. © 2022 Society of Chemical Industry.

Improvement of Robusta coffee aroma with l-leucine powder.

BACKGROUND: l-Leucine powder (LP) was added to green Robusta coffee beans in order to reduce the difference in flavour between Robusta and Arabica coffee. l-Leucine was selected as an additive based on the Maillard reaction. The pre-treatment method conducted in this study was a short soaking (M1) or spraying procedure (M2), then LP was added at varying levels up to 3% (w/w, 30 g kg-1 ). All samples were roasted (240 °C for 15 min) and extracted using an espresso machine. Volatile compounds were analysed by solid-phase microextraction-gas chromatography-mass selective detection. RESULTS: Thirty volatile compounds (six pyrroles, eight pyrazines, three phenols, nine furans, two ketones, two aldehydes) were analysed. In 15 coffee samples, the levels of total volatile compounds (based on peak area ratios) ranged from 8.9 (M1-1) to 15. Non-treated Robusta had higher levels of bitter aroma compounds than Arabica coffee, and Robusta coffee had lower levels of bitter aroma compounds when pre-treated with LP. The sum of bitter volatiles (phenols, pyrroles, pyrazines) was lowest in M1-5 (3% LP), M2-1 (1% LP; both dried at 50 °C for 15 min) and M2-7 (3% LP, dried at 70 °C for 15 min) compared with non-treated Robusta (P < 0.05). CONCLUSION: From the results of this study it can be shown that pre-treatment with LP can improve the flavour of Robusta. © 2023 Society of Chemical Industry.

Genetic-environment interactions and climatic variables effect on bean physical characteristics and chemical composition of Coffea arabica.

BACKGROUND: The effects of the environment and genotype in the coffee bean chemical composition were studied using nine trials covering an altitudinal gradient [600-1100 m above sea level (a.s.l.)] with three genotypes of Coffea arabica in the northwest mountainous region of Vietnam. The impacts of the climatic conditions on bean physical characteristics and chemical composition were assessed. RESULTS: We showed that the environment had a significant effect on the bean density and on all bean chemical compounds. The environment effect was stronger than the genotype and genotype-environment interaction effects for cafestol, kahweol, arachidic (C20:0), behenic acid (C22:0), 2,3-butanediol, 2-methyl-2-buten-1-ol, benzaldehyde, benzene ethanol, butyrolactone, decane, dodecane, ethanol, pentanoic acid, and phenylacetaldehyde bean content. A 2 °C increase in temperature had more influence on bean chemical compounds than a 100 mm increase in soil water content. Temperature was positively correlated with lipids and volatile compounds. With an innovative method using iterative moving averages, we showed that correlation of temperature, vapour pressure deficit (VPD) and rainfall with lipids and volatiles was higher between the 10th and 20th weeks after flowering highlighting this period as crucial for the synthesis of these chemicals. Genotype specific responses were evidenced and could be considered in future breeding programmes to maintain coffee beverage quality in the midst of climate change. CONCLUSION: This first study of the effect of the genotype-environment interactions on chemical compounds enhances our understanding of the sensitivity of coffee quality to genotype environment interactions during bean development. This work addresses the growing concern of the effect of climate change on speciality crops and more specifically coffee. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Effect of pollination on the composition of raw arabica coffee (Coffea arabica L.): antioxidant capacity, bioactive compounds, and volatiles precursors.

BACKGROUND: The importance of pollination is recognized worldwide. This study investigates the influence of biotic pollination on the chemical composition of coffee (Coffea arabica L.) cultivated in the municipalities of Araguari and Monte Carmelo, in Minas Gerais state, Brazil. Twenty samples were analyzed, of which 10 were biotically pollinated (P) and 10 non-biotically pollinated (NP). Analyses of bioactive compounds, antioxidant capacity and centesimal composition of coffees were performed. RESULTS: The results revealed chemical differences between the P and NP samples, with significantly higher levels of the bioactive compounds caffeine, trigonelline, and chlorogenic acids in the P samples. The findings indicated that pollination of the coffee plants assisted germination and made the beans less susceptible to attack by external agents. CONCLUSION: The results demonstrated that pollination services are important mechanisms affecting the chemical composition of coffee beans. Considering that the compounds evaluated are precursors of volatile compounds in coffee, this directly affects the quality of the beans. © 2023 Society of Chemical Industry.