Coffee Science_v.19, 2024

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    Converting Arabica Coffee Parchment into value added products: Technical and Economic Assessment
    (Editora UFLA, 2024-07-29) Setiawan, Adi; Sitepu, Billy B.; Muhammad; Anshar, Khairul; Riskina, Shafira; Nurjannah, Siti; Hakim, Lukman
    The coffee processing industry is experiencing a continuous rise in residues due to increased coffee-cherry production. However, the utilization of coffee parchment, which contains toxic compounds, remains limited and requires further investigation. This study aims to convert coffee parchment into biochar for potential use as a raw material for porous carbon material. The research was conducted using a purpose-built pilot-scale reactor. The goal was to address challenges related to operational cost, simplicity in operation, and maintenance, utilizing the Net Present Value (NPV) approach. Results indicated that coffee parchment comprised 34.5% biochar, 42.15% bio-oil, and balanced un-condensable-gas. Additionally, biochar products consisted of 42.02% fixed carbon and 38.63% volatile matter. The pyrolysis equipment designed for coffee parchment showcased economic viability, considering optimized annual operating days and scalability for production.
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    Effect of demucilagination and soaking in water with organic acids on the microbial, chemical, and sensory characteristics of coffee (Coffea arabica)
    (Editora UFLA, 2024-04-30) Ponce, Jorge Alfredo Cardona; Mejía, Luis Fernando Maldonado
    There are divided opinions regarding sensory quality of mechanically demucilaginated (MD) coffee versus coffee that has undergone conventional fermentation (biological demucilagination). Fermenting and washing (wet process) requires high amounts of water that has contaminating effects upon its completion. Studies indicate that MD with soaking in organic acids could develop similar sensory quality to wet processed coffee. Organic acids are bioactive compounds that are naturally produced during conventional fermentation, which is why coffee has unique characteristics in the final cup profile. This study was conducted to assess the effects of soaking with organic acids (citric, ascorbic, and acetic) on the microbial, chemical, and sensory attributes of MD coffee. A Completely Randomized Design (CRD) was used, with a factorial arrangement (2×4+2) for a total of 10 treatments. The treatments were two soaking times (24 and 48 hours) and four soaking solutions (citric, ascorbic, acetic acid and water) in coffee with mechanical demucilagination, one treatment with mechanical demucilagination and one with fermentation and washing, both without soaking or acids. Microbiological counts of fungi, yeasts, and lactic acid bacteria (LAB) were carried out before and after soaking. Sensory characteristics were evaluated through cupping and chemical content and properties were studied by liquid chromatography and spectrophotometry. Microbial population demonstrated normal succession throughout the experiment with LAB been the most prevalent family during MD and fermentation. Soaking coffee in acid solutions maintained overall cupping scores with different attributes being detected by panelists. Phenolic compounds, caffeine and chlorogenic acids increased in soaked samples (acetic acid) but were similar to the control (fermentation). Flavonoid content ranged from 22 to 35 mg EC/g and was higher in samples soaked in acids compared to the controls. Green coffee extracts in general showed antioxidant activities greater than 80.9% comparable to other studies. Soaking time did not improve the quality characteristics of the coffee, but the type of acid used was able to modify the content and proportion of various families of chlorogenic acids in green coffee and total polyphenols, while maintaining sensory properties in comparison to fermented coffee.
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    Influence of filter holder materials on the physicochemical and antioxidant characteristics of coffee beverages
    (Editora UFLA, 2024-09-19) Santos, Wallysson Wagner Vilela; Oliveira, Rodrigo Lira de; Silva, Marcelo Edvan dos Santos; Lucena, Rodrigo Mendonça de; Silva, Suzana Pedroza da
    Coffee is one of the most consumed beverages in the world, and this study aimed to evaluate the influence of different manufacturing materials of Koar® filter holders (acrylic, stainless steel, ceramic, and porcelain) on the physicochemical characteristics and antioxidant activity of coffee beverages. The results showed that despite having similar design features (such as outlet diameter, grooves, and angle), the material of each Koar filter significantly affected the extraction dynamics of coffee components, resulting in beverages with distinct physicochemical compositions and antioxidant activities. Through multivariate statistical analysis, similarities were identified between the filter materials and the parameters evaluated. In general, coffee extracts obtained from acrylic and ceramic filters exhibited higher values of total phenolics, ABTS antioxidant capacity, reducing sugars, total soluble solids, and extraction percentage. In addition, coffee drinks from stainless steel and porcelain filters presented higher values of total titratable acidity, electrical conductivity, DPPH antioxidant capacity, and caffeine content. Understanding the effects of different filter materials on coffee extraction can contribute to optimizing brewing methods and enhancing consumer satisfaction. These findings highlight the importance of careful selection of filter holder material to ensure different sensory profiles of coffee beverages, providing valuable information for the industry and coffee enthusiasts.
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    Physicochemical and sensory profile of commercial wine coffee in the Gayo Highlands, Indonesia
    (Editora UFLA, 2024-06-13) Muzaifa, Murna; Abubakar, Yusya; Nilda, Cut
    The Gayo Highlands is one of the largest Arabica coffee producing areas in Indonesia. Wine coffee processing is currently very popular in the Gayo High-lands. This study aims to determine of physicochemical and sensory characteristics of commercial wine coffee in Gayo Highlands. Samples were obtained from active wine coffee producers in Central Aceh and Bener Meriah. Analysis was carried out on coffee beans and brewing, including analysis of bean size, moisture content, color, pH, total dissolved solids (TDS), total phenolic content (TPC), and cupping quality. The results found that Gayo arabica wine coffee has a medium size, moisture content of 8.53%-11.67%, and yellow to brown color. Physicochemical characteristics of brewed wine coffee also showed varying results. The pH of coffee wine brewing ranges from 4.68 to 4.95, TDS 3.93 to 4.5 oBrix, and TPC 12.82 to 30 GAE mg/g. Sensory analysis was conducted using the cupping test method. The cupping score of wine coffee on each attribute varied, except body and sweetness. The wine coffee aroma obtained was 6 (good) to 7.75 (very good), wine coffee flavor 6 (good) to 7.5 (very good), wine coffee aftertaste 6 (good) to 7.0 (very good), wine coffee acidity 6 (good) to 7.0 (very good), wine coffee balance 6 (good) to 6.75 (good), overall wine coffee 6 (good) to 7 (very good). Specific fruit aroma charac-teristics that dominated the coffee wine were pineapple, banana, passion fruit, lemon/lime, and berries. Aroma characteristics related to fermentation, namely winey, vinegar, overripe, and soury were detected in all wine coffee samples. Further research is needed to analyze the more complex chemical components of wine coffee (volatile and non-volatile) and their correlation with brewing quality to obtain more comprehensive scientific information on wine coffee quality.
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    Nutrient content and cutting anatomy can affect the production of Conilon clonal plantlets
    (Editora UFLA, 2024-09-19) Bazoni, Patricia Alves; Espindula, Marcelo Curitiba; Araújo, Larissa Fatarelli Bento de; Vasconcelos, Jaqueline Martins; Giuriatto Júnior, Jurandyr José Ton; Campanharo, Marcela
    Cutting is the main vegetative propagation method used to produce Coffea canephora plantlets. In this method, the nutritional quality of the vegetative propagule (stem cuttings) is one of the determining factors for the rooting speed and the final quality of the plantlets. Thus, the objective in this study was to verify possible variations in nutrient content and anatomical characteristics in cuttings collected at different times of the year and their relationship with the production of Coffea canephora clonal plantlets. The study was divided into two phases: 1) Nutritional composition and anatomy of C. canephora cuttings grown at different times; 2) Production of C. canephora seedlings under greenhouse conditions. The treatments consisted of cuttings collection and plantlets production at different times of the year: January, May and September 2017. We observed that there is seasonal variation for the content of N, P, K and Mg; and anatomical changes in xylem, phloem and vascular cylinder thickness in cuttings harvested at different times of the year. We conclude that although nutritional and anatomical aspects of the vegetative propagule may result in different vegetative growth rates of C. canephora clonal plantlets, this result is more dependent on the management of the nursery environment conditions, especially temperature and relative air humidity.
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    Physicochemical characterization of coffee parchment of species Coffea arabica variety Castillo®
    (Universidade Federal de Lavras, 2024-07-03) Campuzano, Francisco; Escobar, Diana Marcela; L., Ana María Torres
    Coffee parchment is one of the most abundant wastes from coffee processing in Colombia, representing 5.8% of dry weight of the berry. This waste has been scarcely characterized, then this work is a complete physicochemical characterization of coffee parchment of the species Coffea arabica variety Castillo®. The coffee parchment composition was studied, determining the fractions of cellulose (49 %), hemicellulose (21 %), lignin (28 %), and inorganics (3 %) presented. Also, FTIR analysis was made to explore the different functional groups of the constituent molecules and confirm their presence, likewise the thermal profile was determined to confirm the composition and explore the thermal stability of this waste. Crystallinity was determined by the Segal method using XRD. A morphological analysis by SEM and a granulometric analysis of this raw material is also presented. All these analyses are important for proposing alternative uses of coffee parchment, such as obtaining cellulose.
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    Physicochemical and sensory analysis of coffee: A determination in different parts of the plant
    (Universidade Federal de Lavras, 2024-07-29) Sousa, Rachel Machado de; Paiva, Leandro Carlos
    The quality of the Arabica coffee drink (Coffea arábica L) is the result of the interaction of several factors, such as climatic conditions, terroir, altitude, nutritional factor, management aspects, stage of fruit maturation, harvest, among others. The objective was to evaluate the physical-chemical quality of coffee fruits, through the soluble solids content of coffee beans, in different parts of the plant, in order to define which position/location on the plant presents the best results in relation to sensory attributes of the drink. The analysis of soluble solids (SS) in ºBrix of cherry and raw coffee, mass grains (MMG) and sensory evaluation, the Catuaí IAC 144 variety presented better results in relation to the Paraíso MG 419- 1 variety. Regarding electrical conductivity (EC), total titratable acidity (TTA) of raw coffee, pH, color the results of the two varieties were representative for quality, the values found in the analyzes are within the defined ranges. The experimental design used was randomized blocks and each variety was harvested in three blocks. Each block consisted of a plant, each plant was divided into twelve subdivisions. The treatments were arranged in a 12x2x3 factorial scheme and subjected to analysis of variance (ANOVA) and the means compared using the Scott Knott post hoc test with a significance level (p-value ≤ 0.05). The correlation matrix was used between the variables under study, in order to verify whether there is a linear relationship or not between the variable’s soluble solids ºBrix of cherry and raw coffee, aroma and body of the drink with the final average score of the tasters. Interpreting the generated equation, there is an association between body and final score, when increasing one unit in the body, an increase of 2.21 in the final score is expected. The positions on the coffee plant, upper third and lower third, in relation to the varieties Catuaí IAC 144 and Paraíso MG 419-1, were the most promising from the perspective of the results found in the physical-chemical and sensorial analysis.
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    System dynamic model of green supply chain management robusta coffee Argopuro in Indonesia: A case study
    (Universidade Federal de Lavras, 2024-06-19) Purnomo, Bambang Herry; Ni’maturrakhmat, Viko Nurluthfiyadi; Wibowo, Yuli
    Small-scale Argopuro Robusta coffee agroindustry has the potential to harm the environment in every supply chain activity. Even though the waste processing process has been carried out, this is still not enough to reduce the environmental impact. Performance measurement of Green Supply Chain Management (GSCM) in the business is complex because it considers environmental indicators and operational business as a whole. GSCM performance is also dynamic because the behavior of the supply chain system often changes over time. Therefore, it is necessary to develop a performance diagnosis model that has complex and dynamic characteristics through a system dynamic model. This research aims to diagnose and improve the GSCM performance index for currently and future using a system dynamic model. The scope of the model starts from harvesting coffee cherries to selling processed products. Research result shows that there are 13 performance indicators. The indicator values are then determined using the system dynamic model to obtain an index value of GSCM. The simulation results show that in 2023, the GSCM performance value will be 35.40, which is included in the good enough status, and 2035 the performance value increase by 54.8. To improve its performance, an optimistic scenario is used. This scenario is built by providing intervention to increase the percentage of waste processing by 90% for solid waste and 70% for liquid waste. Increase the number of pickup trucks by 4 units and reduce the motorcycle by 45 units to be more optimal and reduce the amount of emissions produced. The simulation results show that with that scenario the GSCM performance index was successfully increased to 68.2 (good status) in 2035.
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    Influence of water quality on CO2 degassing and sensory attributes in lampung robusta espresso
    (Universidade Federal de Lavras, 2024-07-05) Haviz, Muhammad; Djana, MIftahul; Nandini, Ni Putu Ariessa; Eltri, Amandha Putri; Fahrani, Nadila Aura; RIna, Oktaf
    Water quality plays a crucial role in shaping the sensory attributes and overall taste experience of Espresso Coffee (EC). This study aimed to investigate the influence of water quality parameters, specifically acidity (pH) and total dissolved solids (TDS), on CO2 degassing kinetics and sensory characteristics in Lampung Robusta espresso. Five different brands of bottled water were utilized for EC extraction, and their impact on CO2 degassing behavior, pH, TDS, and sensory attributes was evaluated. Analysis of variance (ANOVA) and Tukey’s Honest Significant Difference (HSD) post-hoc tests were employed to assess the significance of differences in CO2 degassing levels among water brands. Two-way ANOVA was used to examine variations in pH and TDS before and after espresso extraction. Sensory evaluation by trained panelists was conducted to assess sensory characteristics. ANOVA revealed significant differences in CO2 degassing levels among water brands (F= 41.21, p= 1.41E-16), with specific brand pairs exhibiting significant variations identified by Tukey’s HSD test. Brand D water maintained the lowest average CO2 emissions (865 ppm) compared to other brands, indicating its potential in stabilizing the release of CO2 during the EC extraction. Two-way ANOVA demonstrated significant differences in pH (F= 38380.37, p < 0.001) and TDS (F= 1178385, p < 0.001) among water brands before and after espresso extraction. The highest TDS elevation observed in brand A post-extraction (7258 ppm) suggests a potential for over-extraction. The lowest final pH in EC was recorded with brand B (5.11) and the highest final pH of brand A (5.32) Sensory evaluation revealed variations in aroma, acidity, bitterness, body, crema, sweetness, mouthfeel, and flavor notes among espresso samples prepared with different water brands. This study highlights the significant impact of water quality on CO2 degassing and sensory attributes in Lampung Robusta espresso.
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    Analysis of shape features by applying gain ratio and machine learning for coffee bean classification
    (Universidade Federal de Lavras, 2024-06-28) Septiarini, Anindita; Hamdani, Hamdani; Sela, Enny Itje; Hidayat, Nurul; Afuan, Lasmedi
    Coffee is one of the daily consumed beverages in many countries. It is yielded from coffee beans, which have proceeded through several processes. Several common coffee beans have been produced in Indonesia, such as Arabica, Robusta, Liberica, and Excelsa. Nevertheless, many coffee fanatics are unable to distinguish the various coffee bean types visually based on those shapes. Accordingly, it is necessary to classify the types of coffee beans. The work applied training and testing steps. Both involved ROI detection, pre-processing, segmentation, feature extraction, selection, and classification. Image processing was used in ROI detection, pre-processing, and segmentation to simplify the procedure and separate the coffee bean from the background. The feature extraction produced 14 shape features to distinguish the coffee bean’s class, but the proposed method’s performance has yet to reach the optimal result. The gain ratio was used to reduce the features; hence, only 4 features were selected, including aspect ratio, eccentricity, equivalent diameter, and area. These features were utilized as input data for classification using Naive Bayes, Artificial Neural Network (ANN), Support Vector Machine (SVM), C4.5, and decision tree. The proposed method used 4 features and a decision tree classifier. The local dataset has 400 coffee bean photos in four classes of 100 images each. The photos were divided for training and testing using k-fold 10 cross-validation. The accuracy evaluation parameter reached 0.995.