The floral development of the allotetraploid Coffea arabica L. correlates with a small RNA dynamic reprogramming.

Noncoding and coding RNAs are key regulators of plant growth, development, and stress responses. To investigate the types of transcripts accumulated during the vegetative to reproductive transition and floral development in the Coffea arabica L., we sequenced small RNA libraries from eight developmental stages, up to anthesis. We combined these data with messenger RNA and PARE sequencing of two important development stages that marks the transition of an apparent latent to a rapid growth stage. In addition, we took advantage of multiple in silico tools to characterize genomic loci producing small RNAs such as phasiRNAs, miRNAs, and tRFs. Our differential and co-expression analysis showed that some types of small RNAs such as tRNAs, snoRNAs, snRNAs, and phasiRNAs preferentially accumulate in a stage-specific manner. Members of the miR482/miR2118 superfamily and their 21-nucleotide phasiRNAs originating from resistance genes show a robust co-expression pattern that is maintained across all the evaluated developmental stages. Finally, the majority of miRNAs accumulate in a family stage-specific manner, related to modulated hormonal responses and transcription factor expression.

Combined sensory, volatilome and transcriptome analyses identify a limonene terpene synthase as a major contributor to the characteristic aroma of a Coffea arabica L. specialty coffee.

BACKGROUND: The fruity aromatic bouquet of coffee has attracted recent interest to differentiate high value market produce as specialty coffee. Although the volatile compounds present in green and roasted coffee beans have been extensively described, no study has yet linked varietal molecular differences to the greater abundance of specific substances and support the aroma specificity of specialty coffees. RESULTS: This study compared four Arabica genotypes including one, Geisha Especial, suggested to generate specialty coffee. Formal sensory evaluations of coffee beverages stressed the importance of coffee genotype in aroma perception and that Geisha Especial-made coffee stood out by having fine fruity, and floral, aromas and a more balanced acidity. Comparative SPME-GC-MS analyses of green and roasted bean volatile compounds indicated that those of Geisha Especial differed by having greater amounts of limonene and 3-methylbutanoic acid in agreement with the coffee cup aroma perception. A search for gene ontology differences of ripening beans transcriptomes of the four varieties revealed that they differed by metabolic processes linked to terpene biosynthesis due to the greater gene expression of prenyl-pyrophosphate biosynthetic genes and terpene synthases. Only one terpene synthase (CaTPS10-like) had an expression pattern that paralleled limonene loss during the final stage of berry ripening and limonene content in the studied four varieties beans. Its functional expression in tobacco leaves confirmed its functioning as a limonene synthase. CONCLUSIONS: Taken together, these data indicate that coffee variety genotypic specificities may influence ripe berry chemotype and final coffee aroma unicity. For the specialty coffee variety Geisha Especial, greater expression of terpene biosynthetic genes including CaTPS10-like, a limonene synthase, resulted in the greater abundance of limonene in green beans, roasted beans and a unique citrus note of the coffee drink.

Isolation, identification, and tolerance analysis of yeast during the natural fermentation process of Sidamo coffee beans.

Yeast, which plays a pivotal role in the brewing, food, and medical industries, exhibits a close relationship with human beings. In this study, we isolated and purified 60 yeast strains from the natural fermentation broth of Sidamo coffee beans to screen for indigenous beneficial yeasts. Among them, 25 strains were obtained through morphological characterization on nutritional agar medium from Wallerstein Laboratory (WL), with molecular biology identifying Saccharomyces cerevisiae strain YBB-47 and the remaining 24 yeast strains identified as Pichia kudriavzevii. We investigated the fermentation performance, alcohol tolerance, SO2 tolerance, pH tolerance, sugar tolerance, temperature tolerance, ester production capacity, ethanol production capacity, H2S production capacity, and other brewing characteristics of YBB-33 and YBB-47. The results demonstrated that both strains could tolerate up to 3% alcohol by volume at a high sucrose mass concentration (400 g/L) under elevated temperature conditions (40 ℃), while also exhibiting a remarkable ability to withstand an SO2 mass concentration of 300 g/L at pH 3.2. Moreover, S. cerevisiae YBB-47 displayed a rapid gas production rate and strong ethanol productivity. whereas P. kudriavzevii YBB-33 exhibited excellent alcohol tolerance. Furthermore, this systematic classification and characterization of coffee bean yeast strains from the Sidamo region can potentially uncover additional yeasts that offer high-quality resources for industrial-scale coffee bean production.

Crop-to-wild gene flow in wild coffee species: the case of Coffea canephora in the Democratic Republic of the Congo.

BACKGROUND AND AIMS: Plant breeders are increasingly turning to crop wild relatives (CWRs) to ensure food security in a rapidly changing environment. However, CWR populations are confronted with various human-induced threats, including hybridization with their nearby cultivated crops. This might be a particular problem for wild coffee species, which often occur near coffee cultivation areas. Here, we briefly review the evidence for wild Coffea arabica (cultivated as Arabica coffee) and Coffea canephora (cultivated as Robusta coffee) and then focused on C. canephora in the Yangambi region in the Democratic Republic of the Congo. There, we examined the geographical distribution of cultivated C. canephora and the incidence of hybridization between cultivated and wild individuals within the rainforest. METHODS: We collected 71 C. canephora individuals from home gardens and 12 C. canephora individuals from the tropical rainforest in the Yangambi region and genotyped them using genotyping-by-sequencing (GBS). We compared the fingerprints with existing GBS data from 388 C. canephora individuals from natural tropical rainforests and the INERA Coffee Collection, a Robusta coffee field gene bank and the most probable source of cultivated genotypes in the area. We then established robust diagnostic fingerprints that genetically differentiate cultivated from wild coffee, identified cultivated-wild hybrids and mapped their geographical position in the rainforest. KEY RESULTS: We identified cultivated genotypes and cultivated-wild hybrids in zones with clear anthropogenic activity, and where cultivated C. canephora in home gardens may serve as a source for crop-to-wild gene flow. We found relatively few hybrids and backcrosses in the rainforests. CONCLUSIONS: The cultivation of C. canephora in close proximity to its wild gene pool has led to cultivated genotypes and cultivated-wild hybrids appearing within the natural habitats of C. canephora. Yet, given the high genetic similarity between the cultivated and wild gene pool, together with the relatively low incidence of hybridization, our results indicate that the overall impact in terms of risk of introgression remains limited so far.

Genetic diversity and structure of the coffee leaf rust fungus Hemileia vastatrix across different coffee management systems in Ethiopia.

Although coffee leaf rust (CLR), caused by Hemileia vastatrix, poses an increasing threat to coffee production in Ethiopia, little is known regarding its genetic diversity and structure and how these are affected by coffee management. Here, we used genetic fingerprinting based on sequence-related amplified polymorphism (SRAP) markers to genotype H. vastatrix samples from different coffee shrubs, across 40 sites, covering four coffee production systems (forest coffee, semi plantation coffee, home garden coffee, and plantation coffee) and different altitudes in Ethiopia. In total, 96 H. vastatrix samples were successfully genotyped with three primer combinations, producing a total of 79 scorable bands. We found 35.44% of amplified bands to be polymorphic, and the polymorphic information content (PIC) was 0.45, suggesting high genetic diversity among our CLR isolates. We also found significant isolation-by-distance across the samples investigated and detected significant differences in fungal genetic composition among plantation coffee and home garden coffee and a marginally significant difference among plantation coffee and forest coffee. Furthermore, we found a significant effect of altitude on CLR genetic composition in the forest coffee and plantation systems. Our results suggest that both spore dispersal and different selection pressures in the different coffee management systems are likely responsible for the observed high genetic diversity and genetic structure of CLR isolates in Ethiopia. When selecting Ethiopian coffee genotypes for crop improvement, it is important that these genotypes carry some resistance against CLR. Because our study shows large variation in genetic composition across relatively short geographical distances, a broad selection of rust isolates must be used for coffee resistance screening.

Coffee Fruit Rot: The Previously Unrecognized Role of Fusarium and Its Interactions with the Coffee Berry Borer (Hypothenemus hampei).

Coffee fruit rot (CFR) is a well-known disease worldwide, mainly caused by Colletotrichum spp., the most important species being C. kahawae subsp. kahawae. In Puerto Rico, Colletotrichum spp. were identified as pathogens of coffee fruits. The coffee berry borer (CBB) was shown to be a dispersal agent of these fungi, and interaction of Fusarium with Colletotrichum affecting coffee fruits was suggested. In this study, we demonstrated that Fusarium spp. also cause CFR in Puerto Rico. Fusarium spp. are part of the CBB mycobiota, and this insect is responsible for spreading the pathogens in coffee fields. We identified nine Fusarium spp. (F. nirenbergiae, F. bostrycoides, F. crassum, F. hengyangense, F. solani-melongenae, F. pseudocircinatum, F. meridionale, F. concolor, and F. lateritium) belonging to six Fusarium species complexes isolated from CBBs and from rotten coffee fruits. Pathogenicity tests showed that F. bostrycoides, F. lateritium, F. nirenbergiae, F. solani-melongenae, and F. pseudocircinatum were pathogens causing CFR on green coffee fruits. F. bostrycoides was the predominant species isolated from the CBB mycobiota and coffee fruits with symptoms of CFR, suggesting a close relationship between F. bostrycoides and the CBB. To our knowledge, this is the first report of F. bostrycoides, F. solani-melongenae, F. pseudocircinatum, and F. nirenbergiae causing CFR worldwide and the first report of F. lateritium causing CFR in Puerto Rico. Understanding the CFR disease complex and how the CBB contributes to dispersing different Fusarium spp. on coffee farms is important to implement disease management practices in Puerto Rico and in other coffee-producing countries.

Impact of ontogenic changes on the dynamics of a fungal crop disease model motivated by coffee leaf rust.

Ontogenic resistance has been described for many plant-pathogen systems. Conversely, coffee leaf rust, a major fungal disease that drastically reduces coffee production, exhibits a form of ontogenic susceptibility, with a higher infection risk for mature leaves. To take into account stage-dependent crop response to phytopathogenic fungi, we developed an SEIR-U epidemiological model, where U stands for spores, which differentiates between young and mature leaves. Based on this model, we also explored the impact of ontogenic resistance on the sporulation rate. We computed the basic reproduction number [Formula: see text], which classically determines the stability of the disease-free equilibrium. We identified forward and backward bifurcation cases. The backward bifurcation is generated by the high sporulation of young leaves compared to mature ones. In this case, when the basic reproduction number is less than one, the disease can persist. These results provide useful insights on the disease dynamics and its control. In particular, ontogenic resistance may require higher control efforts to eradicate the disease.

Bacillus licheniformis M2-7 Decreases Ochratoxin A Concentrations in Coffee Beans During Storage.

Microbial contamination of coffee beans arises from various factors such as harvesting, handling, and storage practices, during which ochratoxin A (OTA)-producing fungi develop and proliferate. The presence of elevated concentrations of OTA poses a serious health risk to coffee consumers. Therefore, the implementation of a post-harvest treatment involving the use of bacteria known to antagonize OTA-producing fungi constitutes a safe alternative for reducing or eliminating the toxin's concentration in coffee beans. In this study, coffee beans (Coffea arabica L.) were inoculated with Bacillus licheniformis M2-7, after which we monitored fungal growth, in vitro antagonism, and OTA concentration. Our findings demonstrated that coffee beans inoculated with this bacterial strain exhibited a significant decrease in fungal populations belonging to the genera Aspergillus and Penicillium, which are known to produce OTA. Moreover, strain M2-7 decreased the growth rates of these fungi from 67.8% to 95.5% (P < 0.05). Similarly, inoculation with B. licheniformis strain M2-7 effectively reduced the OTA concentration from 24.35 ± 1.61 to 5.52 ± 1.69 µg/kg (P < 0.05) in stored coffee beans. These findings suggest that B. licheniformis M2-7 holds promise as a potential post-harvest treatment for coffee beans in storage, as it effectively inhibits the proliferation of OTA-producing fungi and lowers the toxin's concentration.

Evaluation of suitable reference genes for expression profile analyses of target genes in the coffee berry borer, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae).

The coffee berry borer, Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae), is a major destructive insect pest of coffee, which impacts the coffee crops negatively. As a draft genome has been completed for this insect, most molecular studies on gene transcriptional levels under different experimental conditions will be conducted using real-time reverse-transcription quantitative polymerase chain reactions (RT-qPCR). However, the lack of suitable internal reference genes will affect the accuracy of RT-qPCR results. In this study, the expression stability of nine candidate reference genes was evaluated under different developmental stages, temperature stress, and Beauveria bassiana infection. Data analyses were completed by four commonly used programs, BestKeeper, NormFinder, geNorm, and RefFinder. The result showed that RPL3 and EF1α combination were recommended as the most stable reference genes for developmental stages. EF1α and RPS3a combination were the top two stable reference genes for B. bassiana infection. RPS3a and RPL3 combination performed as the optimal reference genes both in temperature stress and all samples. Our results should provide a good foundation for the expression profile analyses of target genes in the future, especially for molecular studies on insect genetic development, temperature adaptability, and immune mechanism to entomogenous fungi in H. hampei.

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.

Valorization of coffee bean processing waste for bioethanol production: comparison and evaluation of mass transfer effects in fermentations using free and encapsulated cells of Saccharomyces cerevisiae.

Coffee husk, an agricultural waste abundant in carbohydrates and nutrients, is typically discarded through landfills, mixed with animal fodder, or incinerated. However, in alignment with sustainable development principles, researchers worldwide are exploring innovative methods to harness the value of coffee husk, transforming it into profitable products. One such avenue is the biotechnological approach to bioethanol production from agricultural wastes, offering an eco-friendly alternative to mitigate the adverse effects of fossil fuels. This study delves into the feasibility of utilizing coffee husk as a substrate for bioethanol production, employing and comparing various hydrolysis methods. The enzymatic hydrolysis method outshone thermochemical and thermal approaches, yielding 1.84 and 3.07 times more reducing sugars in the hydrolysate, respectively. In examining bioethanol production, a comparison between free and encapsulated cells in enzyme hydrolysate revealed that free-cell fermentation faced challenges due to cell viability issues. Under specific fermentation conditions, bioethanol yield (0.59 and 0.83 g of bioethanol/g of reducing sugar) and productivity (0.1 and 0.12 g/L h) were achieved for free and encapsulated cells, respectively. However, it was noted that bioethanol production by encapsulated cells was more significantly influenced by internal mass transfer effects, as indicated by the Thiele modulus and effectiveness factor. In conclusion, our findings underscore the potential of coffee husk as a valuable substrate for bioethanol production, showcasing its viability in contributing to sustainable and eco-friendly practices.

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.

MnOx-Coffea arabica Husk and Catha edulis Leftover Biochar Nanocomposites for Removal of Methylene Blue from Wastewater.

In this study, we investigated the use of manganese oxide-biochar nanocomposites (MnOx-BNC), synthesized from coffee husk (CH) and khat leftover (KL) for the removal of methylene blue (MB) from wastewater. Pristine biochars of each biomass (CH and KL) as well as their corresponding biochar-based nanocomposites were synthesized by pyrolyzing at 300°C for 1 h. The biochar-based nanocomposites were synthesized by pretreating 25 g of each biomass with 12.5 mmol of KMnO4. To assess the MB removal efficiency, we conducted preliminary tests using 0.2 g of each adsorbent, 20 mL of 20 mg·L-1 MB, pH 7.5, and shaking the mixture at 200 rpm and for 2 h at 25°C. The results showed that the pristine biochar of CH and KL removed 39.08% and 75.26% of MB from aqueous solutions, respectively. However, the MnOx-BNCs removed 99.27% with manganese oxide-coffee husk biochar nanocomposite (MnOx-CHBNC) and 98.20% with manganese oxide-khat leftover biochar nanocomposite (MnOx-KLBNC) of the MB, which are significantly higher than their corresponding pristine biochars. The adsorption process followed the Langmuir isotherm and a pseudo-second-order model, indicating favorable monolayer adsorption. The MnOx-CHBNC and MnOx-KLBNC demonstrated satisfactory removal efficiencies even after three and six cycles of reuse, respectively, indicating their potential effectiveness for alternative use in removing MB from wastewater.

Transcriptomic Analyses Reveal That Coffea arabica and Coffea canephora Have More Complex Responses under Combined Heat and Drought than under Individual Stressors.

Increasing exposure to unfavorable temperatures and water deficit imposes major constraints on most crops worldwide. Despite several studies regarding coffee responses to abiotic stresses, transcriptome modulation due to simultaneous stresses remains poorly understood. This study unravels transcriptomic responses under the combined action of drought and temperature in leaves from the two most traded species: Coffea canephora cv. Conilon Clone 153 (CL153) and C. arabica cv. Icatu. Substantial transcriptomic changes were found, especially in response to the combination of stresses that cannot be explained by an additive effect. A large number of genes were involved in stress responses, with photosynthesis and other physiologically related genes usually being negatively affected. In both genotypes, genes encoding for protective proteins, such as dehydrins and heat shock proteins, were positively regulated. Transcription factors (TFs), including MADS-box genes, were down-regulated, although responses were genotype-dependent. In contrast to Icatu, only a few drought- and heat-responsive DEGs were recorded in CL153, which also reacted more significantly in terms of the number of DEGs and enriched GO terms, suggesting a high ability to cope with stresses. This research provides novel insights into the molecular mechanisms underlying leaf Coffea responses to drought and heat, revealing their influence on gene expression.

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.

Unveiling the bioactivity and bioaccessibility of phenolic compounds from organic coffee husks using an in vitro digestion model.

BACKGROUND: The large quantities of by-products generated in the coffee industry are a problem. Studies related to the biological potential of organic coffee husks are still limited. The aim of this work was to investigate the occurrence of phenolic compounds in organic coffee husks and to evaluate their potential as a source of bioactive dietary components. RESULTS: To achieve this objective, three extracts were prepared, namely extractable polyphenols (EPs), hydrolyzable non-extractable polyphenols (H-NEPs), and non-extractable polyphenols (NEPs). These extracts were characterized and evaluated for their bioactive properties after simulated gastrointestinal digestion. The results show that the extraction process affected the occurrence of phenols from coffee peels, especially for caffeic acid, gallic acid, and chlorogenic acid. The free and bound polyphenols found in the extracts and digests not only showed antioxidant properties against 2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), ferric reducing antioxidant power (FRAP), and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals but were also strongly bioavailable and had good anticoagulant potential. CONCLUSION: These results highlight the potential health benefits of phytochemicals from coffee husks and open new perspectives for the use of such compounds in dietary supplements. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of 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.

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.

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.