Raw Coffee Research Articles

Prediction of a wide range of compounds concentration in raw coffee beans using NIRS, PLS and variable selection

Near infrared spectroscopy coupled to chemometrics has been proposed as a low cost, rapid and eco-friendly methodology in both off-line and on-line analyses of coffee beans and coffee beverages. However, there are some methodological restrictions regarding its use to quantify chemical constituents in raw coffee beans. In this sense, attention can be drawn to the slight variability of the reference data needed for the construction of multivariate models and the number of analyses needed for the reference method. To overcome these limitations and favor the spectroscopy use, innovations were introduced in the methodological approach for quantifying caffeine, trigonelline and 5-caffeoylquinic acid (5-CQA). Novel mixtures and doping of matrices of different species as well as variable selection processes were proposed. Partial least squares regression (PLSR) was used as a multivariate analysis to build the calibration model for each compound. Using 7, 6 and 5 latent variables, the prediction models constructed for caffeine, trigonelline and 5-CQA contents resulted in a RMSEP of 0.08, 0.07 and 0.27 and rvc of 0.98, 0.96 and 0.96, respectively. In addition, a total of 46 wavelength regions were selected and discussed as important markers for predicting the compounds concentration.

Antioxidants and Mineral Contents of Chicory as Coffee Additive

In this study, roots of Turkish origin wild chicory (Cichorium intybus L.) genotypes were investigated for total flavonoid and phenolic contents, radical cation scavenging activity (ABTS), Free radical scavenging activity (DPPH), and radical, mineral content. These characteristics were also compared with other coffee varieties. The total flavonoid and phenolic contents ranged between 0.290-4.350 mg QE/g dry weight (DW) and 0.943-13.860 mg GAE/g DW. The DPPH was listed here from high to low value: raw coffee beans = roasted coffee beans > roasted fruits of turpentine tree > instant coffee = roots of chicory. The content of P, Ca, Mg, Zn, B, Cr, Co and Mo ranged between 0.71-2.78%, 0.25-0.46%, 7.29-20.66, 4.44-11.07, 0.40-1.67, 0.49-5.48 and 5.69-14.46 ppm, respectively. As a result, chicory roots exhibited low antioxidant activity, but higher mineral content compared to the other tested coffee varieties which indicates that chicory could be used a coffee additive.

Caffeine extraction from Arabic coffee

Objectives: The global population's primary intake of caffeine comes from the consumption of coffee. Arabic coffee is traditionally brewed and served using a unique process. The objective of this study was to examine the plausibility of two widespread myths regarding Arabic coffee; that the longer the cooking time, and/or the more roasted the coffee, the higher is the amount of caffeine extracted per kilo-gram of raw coffee (CE). Materials and Methods: A total of 12 different samples of traditionally brewed Arabic coffee (with correction of lost volume due to evaporation) were directly analyzed for their caffeine concentration using the ultra-high performance liquid chromatography. The amount of caffeine extracted per kilogram of raw coffee (CE) where then calculated. Comparisons were then made between the CE from three types of raw coffee beans; Yemeni Bari, Yemeni Kulani, and Ethiopian Harrari. They were each roasted to two different grades (light vs. medium-dark) and each grade was cooked for a different duration of time (15 min vs. 30 min). Results: The type of coffee bean used was shown to significantly affect the amount of CE from raw coffee (P = 0.011). The highest amount of caffeine was extracted from raw Ethiopian Harrari coffee bean, followed by the Yemeni Kulani bean (P = 0.020 and P = 0.027, respectively). A longer cooking time significantly decreased the amount of CE from raw coffee as compared to a shorter time (P = 0.041). Medium-dark roasting was observed to cause a slight but nonsignificant decrease in amount of CE compared to light roasting (P = 0.178). Conclusions: The type of coffee bean used in brewing Arabic coffee is the main determinant of the amount of caffeine extracted from raw coffee. Longer cooking time and a darker roast both decrease the amount of extracted caffeine in the final brew, rendering the old myths nonplausible.

Thermal and Physicochemical Characterization of Fibers from Coffee Hulls as Filler for Linear Low Density Polyethylene (LLDPE)

This work presents the thermal, physical and chemical characterization of Coffee canephora, from littoral region of Cameroon, for their use as reinforcement for polymeric materials. The infrared of coffee hulls shows the presence of a large peak intensity at 3299 cm-1 that can be attributed to O-H stretching group of alcohol (cellulose content in coffee pulp). The intensity 2926 cm-1 can be attributed to C-H stretching group of alkanes or the vibration of methoxy group of lignin. Thermo gravimetric analysis shows that around 440°C, the biomass has been completely consumed; the temperature profiles show a peak at 86°C that could correspond to the loss of water as evaporation at a percentage of 8%; the peak at 321°C is accompanied by a water loss of 64.50%; this temperature is assimilated to the degradation of hemicelluloses; the temperature range from 321°C to 401°C is accompanied by a loss of mass of 22.80%, which would be due to the degradation of cellulose. SEM images of the surface of raw coffee hulls, coffee hulls treated with caustic soda respectively clearly reveal gaps between the fibers. The results showed that the incorporation of coffee hulls fiber in LLDPE matrix might result in composites with suitable property application for various industrial fields; especially those that were mechanical features are crucial, such as the replacement of engineering plastics.

Chemoenzymatic semisynthesis of caffeic acid β-phenethyl ester, an antioxidative component in propolis, from raw coffee bean extract.

Caffeic acid β-phenethyl ester (CAPE), an antioxidative bioactive catechol isolated from propolis, was semisynthesized from chlorogenic acid and related compounds in an extract of raw (unroasted) Robusta coffee (Coffea canephora) beans in 5 steps and a total yield of 31%. Oxidative degradation of the intermediates and target molecule was prevented by alkaline hydrolysis of the chlorogenic acids in the presence of sodium dithionite (Na2S2O4) and deprotection of the catecholic diacetate precursor by Candida antarctica lipase B-mediated transesterification as the final step.

Organoleptic Approach of Drinks Formulations from Coffee and Cocoa Extracts

Aims: The current work evaluates some organoleptic characteristics of various formulations from diluted coffee and cocoa extracts.
 Study Design: Raw extract produced from Cocoa and Coffee beans, Diluted Extract Formulations processed, and Organoleptic Analyses performed for Sensory profile and Sensory acceptance of the formulations.
 Place and Duration of Study: Laboratory of Biochemistry and Food Sciences from Felix Houphouët-Boigny University in Abidjan, between March 2019 and July 2019.
 Methodology: Six (6) diluted formulations of coffee extracts (dilutions 1/5, 1/10, and 1/20) and cocoa extracts (dilutions 1/3, 1/5, and 1/8) were prepared using variable amounts of concentrated raw coffee and cocoa extracts and mineral water. The acceptance of these formulations by consumers was thus probed, just as the sensory perception index of their appearance (brown), texture (turbidity), and flavor (sweet, acid, bitter). The sensory assessment was achieved from taster's panels.
 Results: The coffee extract dilutions 1/5 to 1/20 were filled invarious coffee aroma (2.58/7 to 3.25/7) and sweetness (0.92/7 to 1.33/7). But the coffee dilution 1/20 has enjoyed 50% tasters and highlighted light brown appearance (2.58/7) and light acid flavor and bitterness (1.92/7 and 2.25/7). The cocoa extract dilutions 1/3, 1/5 and 1/8 exhibited similar and light sweetness of 1/7 to 1.33/7. However, the dilution 1/8 was accepted by 48.33% panellists. It was rated with lightest brown appearance (3.25/7), cocoa aroma (2.67/7), and bitterness (3.08/7), and also moderate acid flavor (2.67/7).
 Conclusion: Diluted extract formulations of coffee 3 (dilution 1/20) and cocoa 3 (dilution 1/8) could be used for the formulation of new drinks products.

Financial analysis of coffee from agroforest managed by women farmers group in Tanggamus Lampung

Coffee (Coffea robusta) is one of the most important products of the community forest (HKm) of Beringin Jaya in Tanggamus Lampung. A women farmers group called KWT Himawari is managing the business of coffee processing. The KWT Himawari was established in 2014 and currently operating a set of coffee processing equipment. This group produces several coffee brands, i.e. Kopi Codot (bat battered coffee), Kopi Merah (red coffee), and Kopi Premium (premium coffee). This study aims to evaluate business feasibility of the coffee processing of KWT Himawari using the financial criteria of Net Present Value (NPV), Benefit Cost Ratio (BCR) and Internal Rate of Return (IRR) within an investment period of 15-years. This study concludes that without any improvement in the business process, the KWT Himawari will potentially lose hundreds million rupiah, indicated by the negative Net Present Value (NPV) of (IDR 181,518,037), Internal Rate of Return (IRR) of (5.245%) and Benefit Cost Ratio (BCR) of 0.781 or less than 1. This study suggests some business improvement to make the women group business feasible. The improved business of coffee processing, so called optimal business model, will make the business profitable with a great potential gain, i.e. NPV of IDR 2,356,763,475, BCR of 1.33 and IRR of 259.57%. The optimal business model can be reached by optimizing production and market that provides several multiplier effects, such as increasing the women’s group income, raising the employment absorption, and stabilizing price of raw coffee from farmers around the forest area.

The use of rice and coffee husks for biosorption of U (total), 241Am, and 137Cs in radioactive liquid organic waste.

Rice and coffee husks (raw and chemically activated) are examined as potential biosorption materials regarding their capacity to remove U (total), 241Am, and 137Cs. The physical parameters evaluated were the morphological characteristics of the biomass, real and apparent density, and surface area. Contact times for the batch experiments were 0.5, 1, 2, and 4h, and the concentrations tested ranged between 10% of the total concentration and the radioactive waste itself without any dilution. The results were evaluated by experimental sorption capacity, ternary isotherm, and kinetics models. The kinetics results showed that equilibrium was reached after 2h for all biomass. Raw coffee husk showed the best adsorption results in terms of maximum capacity (qmax) for all three radionuclides, which were 1.96, 39.4 × 10-6, and 46.6 × 10-9mgg-1 for U, Am, and Cs, respectively. The biosorption process for the raw and activated rice husks was best represented by the Langmuir ternary isotherm model with two sites. For the coffee husk, in the raw and activated states, the biosorption process was best described by the modified Jain and Snoeyink ternary model. These results suggest that biosorption with these biomaterials can be applied in the treatment of liquid organic radioactive waste containing mainly uranium and americium.

Irrigated and CO2 level effects on metabolism in Coffea arabica beans from mixture design – near infrared fingerprints

Coffee bean metabolites are regulated in response to environmental factors, such as climate change and abiotic stress that could influence the quality of beverage. Therefore, the development of methodologies that can indicate chemical changes owing to these perturbations becomes important for making decisions about the coffee culture future. The present study proposes an exploratory analysis of metabolic changes of Coffea arabica beans by means of the spectral fingerprints acquired by Near Infrared Spectroscopy (NIR) combined with Principal Component Analysis (PCA). Coffee plants were cultivated in Free-Air Carbon dioxide Enrichment (FACE) experiment under two CO2 levels, current or elevated, supplied with irrigation or cultivated under rainfed conditions (unirrigated). When measurements were made directly on the raw coffee beans in reflectance mode, the results of the NIR spectra fingerprints did not discriminate the coffee beans originated from different cultivation conditions. An alternative methodology was proposed, using NIR spectral fingerprints in transmittance mode obtained from the statistical mixture design extract solutions. Among ethanol, dichloromethane, hexane, ethyl ether and their combinations, the PCA showed that pure ethanol and the mixture involving ethanol and dichloromethane (1:1 v/v) were the solvents permitting the coffee beans discrimination. A larger number of samples then confirmed the discrimination between the different CO2 levels and irrigation conditions for these extracts. Bands in different regions were responsible for these discriminations and were different for extracts of ethanol and the mixture ethanol and dichloromethane. Results indicate that labeling depends on the intrinsic properties of the organic matrix and the type of solvent used. Furthermore, in the impossibility of an exploratory analysis of the NIR spectra acquired directly on the raw coffee beans, the experimental design, to obtain extracts using different solvents, associated with the obtaining of the spectral fingerprints in the NIR region in transmittance mode, showed an alternative to this situation.

Designing the quality of coffee bean detection application using Hue Saturation Intensity

This study discusses the design of applications that can detect the quality of raw coffee beans both good and bad based on the value of HSI (Hue Saturation Intensity) in the coffee beans using digital image processing and Backpropagation artificial neural networks. The process of identifying coffee beans is based on the intensity of the HSI value that is owned by coffee beans. The HSI value is converted from RGB values, then the training process is performed on backpropagation artificial neural networks to recognize good quality seeds and poor-quality seeds. The testing phase is carried out using an interface designed in the MATLAB R2013a software. Based on the results of testing, it was found that this application was able to detect samples of coffee beans that were not properly trained.

Coffee parchment as potential biofuel for cement industries of Ethiopia

ABSTRACTThis study explores the biofuel potential of raw coffee parchment and its pellets to supplement the energy demand of the cement industries of Ethiopia by characterizing their combustion characteristics and ash qualities for clinker production. The raw and pelletized coffee parchments were characterized for ultimate and proximate composition, calorific value, heavy metals, and ash oxides. The ultimate analysis confirmed higher carbon (45.5%) and hydrogen (6.5%) content and lower nitrogen (0.4%) and sulfur (0.1%) content in the pellets as compared to the commonly used biomass fuels. The moisture content (11.2%) and ash content (5.97%) of the pellets meet the ISO standard for non-wood pellets (ISO 17225–6, 2014). Pelletization of the coffee parchment enhanced the gross heating value of the biomass. The ash analysis revealed that the ash may supplement a sufficient amount of oxides of calcium, silica, aluminum, and iron required for clinker production. Overall, the results signify that coffee parchment and its pellets have suitable properties to be used as cheap, sustainable and eco-friendly bio-fuel for the cement industries of Ethiopia.

Mycotoxigenic Moulds Associated with Coffee and Their Management (A Review)

Coffee is produced in tropical countries where climatic conditions favor mould growth and development. Moulds are multicellular, filamentous fungi that can grow and produce mycotoxins as secondary metabolites on plants either during pre-harvest or post-harvest, storage, transport, processing, and feeding. Mycotoxins are fungal metabolites and chemical defenses that cause lowered performance, sickness or death in human or animals. Aspergillus, Penicillium and Fusarium species are common and important moulds in the human environment and are among the main agents of spoilage of food and feeds. Problems associated with the occurrence of mycotoxins in coffee have become concern to consumers as well as producers. Several studies have reported Ochratoxin A (OTA) presence in raw coffee. OTA is a form of mycotoxin, produced as a metabolic product of Aspergillus ochraceus , Aspergillus carbonarius and strains of Aspergillus niger . Its presence or absence in any sample is probably related to the length of storage rather than to geographical location or other factors. Most importing countries regulate mycotoxins by setting maximum allowable concentration. The European Union (EU) which are among major buyers of coffee from producing countries set maximum permissible limits for OTA of 5 particles per billion (ppb) in roasted and ground coffee, and 10 ppb in instant coffees. This is a serious indicator for coffee producing and selling countries on how they manage their products. Key factors in the successful management of OTA involve good agricultural practices (GAP) and good manufacturing practices (GMP). As it has great influence on countries economy in general and producers income in particular Strict measures should be taken to improve post-harvest handling and processing of coffee, specially drying of bulk coffee along asphalt roads and bare soils should seriously be discouraged. Research is needed on identification of inexpensive and appropriate sampling and testing protocols of mycotoxins associated with coffee in various coffee agro-ecologies and production systems. Keywords : moulds , Ochratoxin A DOI : 10.7176/JBAH/9-8-06 Publication date : April 30 th 2019

The Role of Microbes in Coffee Fermentation and Their Impact on Coffee Quality

Coffee is one of the most important and widely used commercial crops in the world. After ripe coffee cherries are harvested, coffee must pass through several steps to become (green) raw coffee beans. Commonly, there are three different processing methods used to obtain green coffee beans from coffee cherries, namely, the wet, dry, and semidry methods. Microorganisms (yeasts and bacteria) play a major role in coffee fermentation process by degrading mucilage by producing different enzymes (pectinase), acids, and alcohols. Starter culture development is crucial and is done by selecting microorganisms that have certain characteristics, such as mucilage degradation ability, tolerance to stress during fermentation, the ability to suppress the growth of pathogenic fungi, and a positive impact on the sensory quality of the coffee. Currently, green coffee beans obtained from farms that use any of the above processing methods are fermented with selected microorganisms to improve the flavour and aroma of the coffee. This is the result of a new insight into the development of unique flavoured coffee and into engaging with the coffee market to better benefit. This review gives a comprehensive overview of the fermentation process, microorganisms and starter cultures, and fermentation’s impact on coffee quality. Future prospects are also discussed through the incorporation of recent research.

Cosmeceutical activities of ethanol extract and its ethyl acetate fraction from coffee silverskin

BackgroundCoffee silverskin is a thin film that covers the raw coffee bean. In general, coffee silverskin, which detaches during the coffee roasting process, is disposed as firelighters or dispatched to landfills and can cause serious environmental pollution. The aim of this study was to investigate the feasibility of using coffee silverskin as a functional material in cosmetics by evaluating its bioactive ingredients, antioxidative activity, cytoprotective effect, matrix metalloproteinase-1 (MMP-1)-inhibiting effect, and anti-melanogenesis effect.ResultsTo this end, a 50% ethanol (EtOH) extract and its ethyl acetate (EtOAc) fraction were prepared from coffee silverskin; caffeine was found to be the major compound in the extract. Both the 50% EtOH extract and its EtOAc fraction exhibited antioxidant activities. However, the EtOAc fraction showed a greater radical-scavenging activity and reducing power than that shown by the 50% EtOH extract. Furthermore, the EtOAc fraction increased cell viability in a UVB-irradiated human keratinocyte injury model and significantly suppressed UVB-induced MMP-1 expression and α-melanocyte-stimulating hormone (α-MSH)-stimulated melanin production in HaCaT keratinocytes and B16F1 melanocytes, respectively. Interestingly, caffeine, the major component of the EtOAc fraction, did not show an inhibitory effect. Thus, the antioxidant capacity of the coffee silverskin extract may be attributable to some compounds that exhibit a high antioxidant capacity even at low concentrations or the total antioxidant capacity of various constituent phenolic compounds.ConclusionOur findings indicate that coffee silverskin has the potential for application as a natural functional material in multifunctional cosmetics.

Coffee – from plant to popular beverage

Coffee, one of the most popular beverages in modern world, is obtained from the beans of perennial bush Coffea. The distinctive aroma and taste of coffee is obtained by thermal treatment (roasting) of raw coffee beans. There are different degrees of roasting that can be divided according to the color of the grain: easy, medium, dark and Italian. The most famous types of coffee used in the production of beverages are Arabica and Robusta. Raw coffee beans contain a certain amount of caffeine, sugar, essential oil, potassium, calcium and magnesium. Roasting the grains leads to the loss of dry matter through formation of carbon dioxide, water and volatile products of pyrolysis. Coffee also has a moderate healing effect, while in overdoses it causes rapid heartbeat, insomnia, even euphoria.

Coffee Grading with Convolutional Neural Networks using Small Datasets with High Variance

Convolutional Neural Networks (CNNs) have been established as a powerful class of models for image recognition problems. Despite their success in other areas, CNNs have been applied only for very limited agricultural applications due to the need for large datasets. The aim of this research is to design a robust CNN model that classifies raw coffee beans into their 12 quality grades using small datasets which have high data variability. The dataset contains images of raw coffee beans acquired in two sets using different acquisition technique under varying illuminations which poses a complex challenge to designing a robust model. To design the model, preprocessing techniques were applied to the input in order to reduce task irrelevant features. But adding the preprocessing techniques did not improve the performance of the CNN model for our dataset. We have also used ensemble methods to solve the high variance that exists in networks when working with small datasets. Finally, we were able to design a model that classifies the beans into their quality grades with an accuracy of 89.01% on the test dataset.

Identifying Arabica Raw Coffee Bean Varieties through Feature Extraction GLCM and Circularity

The morphology of raw coffee bean which has colour, texture, size and circularity features are used as standardization to calculate the price and the quality of the raw coffee bean. Meanwhile, coffee farmers have difficulties to distinguish the coffee varieties based on the features of raw coffee bean. Generally, the way of the distinguish the varieties of the coffee is through their own visual perception in form of the tree, leaves, and raw coffee bean. They find it difficult to distinguish the coffee varieties due to the similarity of the varieties forms and colours. This research proposes to solve the problem through the image processing method as the second opinion to help the coffee farmers in identifying the coffee varieties. The research is conducted in three steps processes: The first is pre-processing by cropping the image of raw coffee bean. The second is extracting the image feature of raw coffee bean with Gray Level Co-occurrence Matrices (GLCM) and circularity feature. The last is classifying the feature with multilayer perceptron. The results of the image processing method indicate that the accuracy is 90% with sensitivity is 90%, and 90% specific.

The global coffee paradox and coffee marketing in Zimbabwe; 1980-2000

This article examines coffee marketing in Zimbabwe amidst debates on the contribution of agricultural commodities to sustainable economic development in Africa. It uses the concept of linkages and declining terms-of-trade to reconnoitre these debates. The article argues that between 1980 and 2015, coffee production, and in particular marketing, faced a myriad of internal and external challenges, which limited its overall contribution to the economy. Among these constraints was the lack of a significant domestic market, which tied the sector to external markets. The externality of the coffee industry weakened the linkages between the sector and the rest of the local economy, thereby turning the sector into an enclave of external economies. This exposed the industry to risks on the international market— including price volatility. The setup perpetuated the unfair global division of labour, where Zimbabwe suffered declining terms-of-trade as an exporter of raw coffee and an importer of manufactured products. This article, therefore, contends that the externality of the coffee industry in Zimbabwe plunged the country into an exploitative dependency relationship with consuming countries. Failure to export processed coffee was mainly a function of the restrictive tariff policies in the consuming countries.

Coffee processing industrial wastewater treatment using batch electrochemical coagulation with stainless steel and Fe electrodes and their combinations, and recovery and reuse of sludge.

The efficiency of chemical oxygen demand (COD) and color removal from raw coffee processing wastewater (CPWW) using batch electrochemical coagulation (BECC) treatment process using stainless steel (SS) and iron (Fe) electrode combinations are investigated. Of the combinations: four SS, four Fe, Fe-Fe-SS-SS, Fe-SS-Fe-SS, SS-SS-Fe-Fe, and SS-Fe-SS-Fe; four SS electrodes operated at 23 V having 120 A/m2 current density was found as a good operating condition to achieve ∼87% COD removal from its initial COD of 1,984 mg/L and corresponding color removal of 97.1% (initial color 7,000 PCU). The second best electrode combination, SS-SS-Fe-Fe, had COD and color removals of 75% and 91%. When using polyaluminum chloride (PAC) as aid with different dosages of 20-100 mg/L, 50 mg/L PAC showed maximum COD and color removals of 80% and 92%. Comparison of proximate and ultimate analyses of various solid fuels with CPWW ECC sludge showed its usefulness as a soil supplement and as an adsorbent for reutilization. The solid residue obtained after BECC was characterized using energy dispersive X-ray spectroscopy and other analyses. Summarizing the results, it was concluded that BECC can be effectively used for maximum removal of organics from raw CPWW with clean water reclamations of up to ∼90% using ECC as a novel treatment technique.

PROFILE OF ORGANIC ACIDS AND BIOACTIVE COMPOUNDS IN THE SENSORY QUALITY DISCRIMINATION OF ARABICA COFFEE

O presente estudo foi desenvolvido para investigar o potencial dos ácidos orgânicos e bioativos presentes no grão cru para discriminar a qualidade sensorial do café proveniente de diferentes genótipos e métodos de processamento. Durante as safras 2010, 2011 e 2012, foram analisadas a qualidade da bebida do café e o perfil de ácidos orgânicos e dos bioativos, cafeína, trigonelina e ácidos clorogênicos (3,4 e 5-CQA) do grão cru de amostras representativas dos genótipos Bourbon Amarelo e Acaiá. As amostras foram coletadas em lavouras comerciais com altitudes variando entre 932 a 1391 m, no município de Carmo de Minas, MG, Brasil. Os métodos de processamento adotados foram: via seca (café natural) e via úmida com descascamento e desmucilamento mecânico do fruto. Todos os procedimentos de colheita e pós-colheita foram realizados conforme as principais tecnologias para produção de cafés especiais. A análise sensorial foi realizada utilizando-se a metodologia proposta pela Associação Americana de Cafés Especiais (SCAA). As análises químicas foram realizadas por HPLC. Os dados foram investigados aplicando-se a Análise de Componentes Principais (ACP). As variações nos teores de ácidos orgânicos e dos bioativos analisados ocorreram em razão do método de processamento do café. Para os genótipos Bourbon Amarelo e Acaiá, as diferenças existentes no perfil de ácidos orgânicos associado com os bioativos, cafeína, trigonelina e ácidos clorogênicos (3,4 e 5-CQA) foram determinantes para discriminar a qualidade do café descascado e desmucilado mecanicamente.