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Specialty coffee is generally found in areas with an altitude around 1000 meters above sea level (m a.s.l.) and is known to have a different distinctive flavor. One of the coffee plantations in South Sulawesi that has the potential to upgrade its status as a specialty coffee is the Sinjai regency. The sensory quality and chemical characteristics are the most important component of specialty coffee. The purpose of the study was to evaluate the chemical compounds and sensory quality in Manipi coffee beans in South Sulawesi, which has the potential to be classified as specialty coffee. The coffee cherries were collected from two locations based on different altitudes namely MA1 = 1200 m a.s.l. and MA2 = 1400 m a.s.l. The coffee cherries directly processed the wet method referring to Enrekang Arabica as a reference sample EA1 = 1200 m a.s.l. and EA2 = 1400 m a.s.l. The results showed that the chemical content and quality of sensory in Manipi Arabica coffee beans were affected by altitude. MA2 had the highest protein content (13.26%), lipid (7.67%), and caffeine (1.42%), whereas green arabica coffee beans with the highest carbohydrate content was MA1 (23.38%). The Enrekang Arabica were similar in terms of Manipi Arabica coffee beans had the highest protein, lipid, and caffeine content at an altitude of 1400 m a.s.l. respectively (12.41%), (10.73%), and (1.32%). The sensory quality of MA1 is 85.75, relatively similar to MA2 is 85.25. The Manipi Arabica coffee beans showed a specific flavor, namely brown sugar and vanilla notes from both altitudes. It had the potential to be developed into specialty coffee with a cup test score > 80.

Juremian and Kirmanan are other names for the Sintaro 2 and Sintaro 3 coffee clones, the national superior robusta coffee clones that have been cultivated in Sidorejo Village. This study aims to determine the quality and physical properties of coffee beans, chemical properties and ground coffee quality of Juremian and Kirmanan clones. The quality and physical properties of coffee beans are evaluated according to the Indonesian National Standard (SNI) 01-02907-2008 procedure. The chemical properties and quality of ground coffee powder were evaluated based on SNI 01-3542-204 procedure as well as the cupping test method (Specialty Coffee Association of America). The results showed that Juremian coffee beans had fewer defects and bean sizes, more peaberry beans, and better bean quality than Kirmanan coffee beans. Based on coffee extract content, "medium dark roast" and "dark roast" Ground coffee Juremian and Kirmanan are categorized as quality 1. "Medium dark roasted" Juremian coffee got a total score of 8.00, with the "excelent" category on the cupping test. The aromas found in Juremian coffee include chocholety, black tea, fruity, and nutty. The quality of the coffee beans, the high percentage of peaberry, and the roasting rate are thought to have contributed to the brewing quality of Juremian and Kirmanan coffees.

The detection of coffee bean defects is the most crucial step prior to bean roasting. Existing defect detection methods used in the specialty coffee bean industry entail manual screening and sorting, require substantial human resources, and are not standardized. To solve these problems, this study developed a deep learning algorithm to detect defects in coffee beans. The results reveal that when the pooling layer was used to enhance features and reduce neural dimensionality, some of the coffee been features were lost or misclassified. Therefore, a novel dimensionality reduction method was adopted to increase the ability of feature extraction. The developed model also overcame the drawbacks of padding causing blurred image boundaries and the dead neurons causing impeding feature propagation. Images of eight types of coffee beans were used to train and test the proposed detection model. The proposed method was verified to reduce the bias when classifying defects in coffee beans. The detection accuracy rate of the proposed model was 95.2%. When the model was only used to detect the presence of defects, the accuracy rate increased to 100%. Thus, the proposed model is highly accurate in coffee bean defect detection in the classification of eight types of coffee beans.

The specialty coffee market has grown significantly in the past decades and has several cultivars with productive potential. The objective of this study was to evaluate the sensory profile of the beverage produced from Coffea arabica L. genotypes based on postharvest processing and to identify cultivars with the greatest genetic potential for coffee cultivation in the city of Araponga, Minas Gerais, Brazil. The experiment was a randomized complete block design with two replicates and 11 genotypes with different levels of resistance to rust. The sensory profile demonstrated an interaction between the genotype and the processing technique. Five of the genotypes presented total scores above 85 points according to the SCAA protocol. Moreover, two of these genotypes yielded heightened sensory notes after undergoing dry processing. The selection of coffee genotypes should consider the level of technology involved in the drying of the coffee beans, which preserves the potential quality of the beverage.

This study uses data from 1,024 coffee producing households to address two critical questions regarding the role of cooperatives in Rwanda’s coffee sector: Does cooperative membership increase adoption of best practices and coffee productivity? and do cooperatives improve farm household welfare? Using a propensity score matching technique to account for selection bias, we find that cooperatives are a critical institution for building farmer capacity, promoting adoption of improved technologies and inputs, and increasing productivity. We discuss the role that cooperatives can play in increasing farmer welfare and reestablishing the coffee sector as a pillar of growth in the country.

Opportunities open a coffee shop in the mall and office buildings are still very open because for the city, drink coffee together has become a necessity. Everyone loved the coffee and coffee atmosphere relaxed, loose and information enjoyed while chatting, chat/browsing internet, small meeting or discussion. More than that the coffee shop has become a strategic place to make a deal and business negotiation or a place to spend time waiting for hours jammed in the capital. Café Republic (KKR) is the concept of specialty coffee bar espresso coffee made from ingredients of real coffee from various parts of Indonesia elected and diverse. KKR offer experience (experience) coffee with coffee bar atmosphere to enjoy a coffee ritual into something fun. This concept is made different from the coffee shop that currently exists in Indonesia.

Indonesian arabica coffee is now a special coffee and is the best type of coffee, with a distinctive aroma because it has a special market. Its potential development in Indonesia is still very open, especially with the shift of ordinary coffee consumers to specialty coffee. This study aims to analyze the sustainability of Bawakaraeng Arabica coffee farming. This research was conducted in Sinjai Barat Subdistrict, Sinjai Regency, which took place from May to August 2017. Sampling / respondents were conducted randomly as many as 60 farmers. The data obtained were analyzed using the Multidimensional Scaling (MDS) approach which was the development of the Raled SBH method. The results showed that the production and income of Bawakaraeng Arabica coffee farming was less profitable for farmers because income per month for arabica coffee (peco) was approximately Rp. 340,981 and for Arabica coffee (logs) income per month Rp. 439,618, this is far below the minimum wage (UMP) of South Sulawesi province of Rp. 2,435,625 per month. Development of Arabica Bawakaraeng coffee farming based on ecological dimensions, economic dimensions, socio-cultural dimensions, infrastructure and technology dimensions, unsustainable legal and institutional dimensions.

Purpose- The impacts of eight dimensions, including customer communication, customer relationship management, customer satisfaction, customer loyalty, strategy management, customer trust, and service quality, on the business of specialty coffee shops were investigated, Methodology- A questionnaire was designed to collect the data from 197 valid respondents; Structural Equation Modeling (SEM) was utilized to analyze the data, and finally, Smart PLS was employed to validate the structural model. Findings- Nine of the eleven hypothesized relationships were confirmed and supported, while two were not supported. Conclusion- Results of this study can provide business owners of specialty coffee shops with valuable information and management implications.

Coffee chain enterprises in Nan province were small groups, most of businesses interdependent with other business in Nan coffee industry. This research studied about sustainable supply chain in Nan’s coffee chain enterprises from the beginning as coffee agriculture to selling coffee to customers. Coffee shop in Nan downtown use the coffee beans that cultivate and process in Nan, for this reason that farmers are able to sale more beans, not only to coffee manufactories but also to SMEs coffee houses. Moreover, to increase number of new specialty coffee drinkers. The researchers founded that government agencies included governor, ministry of Tourism and Sports etc. also supported Nan’s coffee products and travelling follow coffee places. Besides, the growth rate of Nan coffee chain enterprises made new blood returned their homes in order to start coffee businesses. Accordingly, Nan new generations continue coffee business which conform to Nan dominant. This research aimed to conduct new entrants in coffee chain industry and other industries about sustainable industry in each hometown.

Specialty coffee has gained immense popularity for its unique flavor and improved quality. There are large varieties of coffee trending every day due to the widened demand. Still, specialty coffee holds its place for its distinct processing inside the animal digestive system. Specialty coffees are also considered the most expensive due to coffee varieties with novelty in processing which leads to limited availability and less productivity. The digested coffee's uniqueness and rarity led to higher consumer demand, which paved the way for animal abuse in captivity and the production of fake authenticity to tackle the increased market requirement. In the context of coffee processing through conventional methods, the application of enzymes and microbes has brought about an improvement in coffee fermentation. Much research has been focused on the isolation of microbial cultures from the animal excreta and gastrointestinal tract. This review emphasizes the types of specialty coffee, its uniqueness compared to the traditional varieties, the bio-processing method of specialty coffee inside the animal gut and its taste profile.

Background Specialty coffee fascinates people with its bountiful flavors. Currently, flavor descriptions of specialty coffee beans are only offered by certified coffee cuppers. However, such professionals are rare, and the market demand is tremendous. The hypothesis of this study was to investigate the feasibility to train machine learning (ML) and deep learning (DL) models for predicting the flavors of specialty coffee using near-infrared spectra of ground coffee as the input. Successful model development would provide a new and objective framework to predict complex flavors in food and beverage products. Results In predicting seven categories of coffee flavors, the models developed using the ML method (i.e. support vector machine) and the deep convolutional neural network (DCNN) achieved similar performance, with the recall and accuracy being 70-73% and 75-77% respectively. Through the proposed visualization method - a focusing plot - the potential correlation among the highly weighted spectral region of the DCNN model, the predicted flavor categories, and the corresponding chemical composition are presented. Conclusion This study has proven the feasibility of applying ML and DL methods on the near-infrared spectra of ground coffee to predict specialty coffee flavors. The effective models provided moderate prediction for seven flavor categories based on 266 samples. The results of classification and visualization indicate that the DCNN model developed is a promising and explainable method for coffee flavor prediction. © 2021 Society of Chemical Industry.

Current climate change impact studies on coffee have not considered impact on coffee typicities that depend on local microclimatic, topographic and soil characteristics. Thus, this study aims to provide a quantitative risk assessment of the impact of climate change on suitability of five premium specialty coffees in Ethiopia. We implement an ensemble model of three machine learning algorithms to predict current and future (2030s, 2050s, 2070s, and 2090s) suitability for each specialty coffee under four Shared Socio-economic Pathways (SSPs). Results show that the importance of variables determining coffee suitability in the combined model is different from those for specialty coffees despite the climatic factors remaining more important in determining suitability than topographic and soil variables. Our model predicts that 27% of the country is generally suitable for coffee, and of this area, only up to 30% is suitable for specialty coffees. The impact modelling showed that the combined model projects a net gain in coffee production suitability under climate change in general but losses in five out of the six modelled specialty coffee growing areas. We conclude that depending on drivers of suitability and projected impacts, climate change will significantly affect the Ethiopian speciality coffee sector and area-specific adaptation measures are required to build resilience.

One of the biggest challenges in markets where products have ambiguous values (like fine art, specialty coffee, and wine) is to determine the structure of the market. As products in these markets are unique and values are private, it is difficult to determine its market structure using traditional methods. In this chapter, we present a method to determine the market structure of ambiguously valued products using bidding data from auctions. We create a sociomatrix of artists based on bidders revealed bidding preferences and uncover the market structure with artists as the unit of analysis. We demonstrate our approach using bidding data from an online auction of Modern Indian Art. This approach resulted in the extraction of a two-dimensional art market structure with color and price being the two dimensions. This chapter concludes with a discussion on the implications and limitations of our approach, and directions for future research.

Study aim: we aimed to outline the direct trade of specialty coffees’ global research and adoption, highlighting its contributions, limitations and theoretical and empirical gaps, providing insights for future studies. Method: integrative systematic review of selected academic materials from the Web of Knowledge, SciELO, Scopus, Science Direct and Scholar Google databases, as well as technical materials from the Specialty Coffee Association and the Perfect Daily Grind portals, which were analyzed using the qualitative and open grid categorical content analysis technique. Main results: we identified three categories of contributions associated with Direct Trade - "Relationship and Coordination", "Origin and Sustainability" and "Quality and Differentiation" and three categories of its limitations - "Conceptual and Regulatory", "Execution and Monitoring" and "Potential of Transformation and Accessibility". Despite its potential to contribute to the promotion of the sustainability of this market, Direct Trade is not the only solution to the many and complex challenges of the activity. Therefore, it should be adapted to local realities and be carefully adopted, preferably in conjunction with other initiatives aimed at opening different markets and reaching different consumer audiences. Relevance/originality: this is the first systematic review of the subject, required by the rapid growth of studies in the field, despite its currentness and only recent expansion of the debate. Theoretical/methodological contributions: we presented a new concept of Direct Trade, subdivided the practice into two perspectives - relational and transactional – and elaborated a framework for its realization.

Learning outcomes The main pedagogical objectives of the case are: illustrate how Latin American companies dedicated to the production and harvesting of commodities can be vertically integrated to gain a larger share of the value created throughout the production chain. Understand how futures and options contracts in commodities can be used to hedge price risk on long and short positions in the underlying products. Understand how option contracts add value by hedging risk in those contexts where the counterparty has optionality. Discuss the implications of Fair Trade for commodity traders and producers. Case overview/synopsis In the case, Hernan Arosamena, CFO of The Specialty Coffee Trading Co. (TSCT), faces the challenge of designing an effective strategy to hedge the price risk caused by the increasing demand of the so-called Fair Trade coffee. Hernan Arosamena decides to review how the company has typically managed the price risk in its business transactions using future contracts to then incorporate the additional elements that trading Fair Trade coffee may entail. The typical price risk hedging strategy involves the use of coffee future contracts in long and short positions to ensure that the company obtains the desired margin in its coffee trading negotiations. To hedge the exposure to the risk of fluctuations in the price of coffee when the company sells Fair Trade coffee requires the additional use of put options. Complexity academic level The case is appropriate for students enrolled in courses or specialization programs at both the undergraduate and graduate levels. Supplementary materials Teaching notes are available for educators only. Subject code CSS 5: International Business.

Companies have been under pressure from different sectors of society to make their processes more environmentally sustainable, a fact that drives the joint adoption of Lean and Green production systems. Studies relating these systems have intensified in the past decade and follow a growth trend. However, this can be considered a relatively new field with many gaps to be filled. One of these gaps is found in the agricultural sector, where no studies relating Lean and Green have been identified. The main contribution of this article is to develop a model for the evaluation of the integration of Lean and Green systems (Lean Green Synergy – LGS) through the formulation of a conceptual framework. In order to demonstrate the viability of the model, a case study was carried out on a set of six specialty coffee producing properties, located in the state of Quindio, Colombia. The research carried out provides a non-subjective means to establish the maturity of the Lean and Green systems and establishes 20 metrics capable of providing the information necessary to carry out the LGS calculations. The calculation method described allows the replication of the model and its adaptation to other sectors by defining the appropriate metrics for it, encouraging the joint adoption of Lean and Green systems.

The near-infrared spectrometry combined with the one-class classification method was applied as quality control of the agroforestry-grown specialty coffee. A total of 34 samples were analyzed in this study. Spectral data were obtained using a NIR portable and different pre-treatment strategies for baseline correction were evaluated. Unsupervised pattern recognition (PCA and HCA) techniques were performed. The construction of the classification model was carried out using the dd -SIMCA algorithm with 19 samples acquired directly from producers that are recognized for the best quality control of the specialty type coffee. In order to test the model, 15 samples of non-specialty type, obtained in local markets, were evaluated. The classification model with the highest correct classification rate (CCR) scored 100% and 87% in the validation and test groups, respectively. The results demonstrated that the application of this strategy was successful in verifying the authenticity of specialty type agroforestry-grown coffee samples.

Specialty coffee markets that recognize coffee-quality price premiums can improve business conditions for smallholders and promote agro-ecological practices. We studied the Relationship Coffee Model (RCM), a business model that supports long-term partnerships between coffee buyers and smallholders based on product quality. We examined how biophysical conditions and production practices affect smallholders’ ability to participate in this model. Furthermore, we considered common unobservable variables driving growers’ participation such as farm soil quality and connection to social networks. In turn, we evaluated key environmental, socio-economic and technological outcomes, including tree and bird population diversity. Our estimations indicated that RCM participants employed more sustainable resource management practices, had better access to credit and were more informed and optimistic about the coffee business. However, we did not find significant farm-gate price differences. Increased adoption of organic farming and shade-grown systems to elevate coffee quality can stimulate sustainable business strategies. Copyright © 2018 John Wiley & Sons, Ltd and ERP Environment

Fair trade and organic coffee are alternative production and trade systems designed to promote the equitable and environmentally sustainable production of coffee. The purpose of this study is to analyze the functioning of different coffee supply chains in Bolivia and find policy changes necessary to sustain specialty coffee production in that country. Based on the primary and secondary data collected from various market functionaries, we find that the Bolivian coffee growers and other intermediaries have benefited financially from participating in fair trade and organic markets. However, the producers continue to face challenges, including increasing costs of production, stagnant premium, price floors, and declining yield. Institutional reforms within the supply chain and greater support from the government are necessary to ensure a better functioning Bolivian market. The government should also prioritize certified coffee as a part of its national food sovereignty agenda since Bolivians consume in...

Indonesia's potential as the top five coffee producers and exporters in the world will create opportunities in order to meet the high demand of US coffee consumption. However, competition for the world coffee export commodity market in the United States is very competitive. Indonesia launched a foreign policy on coffee diplomacy that involved a variety of stakeholders to increase Indonesia's coffee exports to the United States and give branding to Indonesian specialty coffee. The author aims to show the success of coffee diplomacy in the United States-Indonesia coffee commodity export cooperation seen by the increase in exports from year to year. The author uses descriptive-analytical methods to provide an overview of Indonesian coffee exports to the United States. Therefore, it easier for readers to obtain information about coffee diplomacy analysis which is motivated by several determinants of Indonesian foreign policy and national interests contained in legal instruments. Analysis of the coffee diplomacy policy also involves historical, cultural and political aspects to explain the flow of foreign policy formulation from domestic factors. Keywords: Coffee, Bilateral Cooperation, Coffee Diplomacy, Indonesia, United States DOI : https://doi.org/10.33005/jgp.v7i02.1830

In the production process from green beans to coffee bean packages, the defective bean removal (or in short, defect removal) is one of most labor-consuming stages, and many companies investigate the automation of this stage for minimizing human efforts. In this paper, we propose a deep-learning-based defective bean inspection scheme (DL-DBIS), together with a GAN (generative-adversarial network)-structured automated labeled data augmentation method (GALDAM) for enhancing the proposed scheme, so that the automation degree of bean removal with robotic arms can be further improved for coffee industries. The proposed scheme is aimed at providing an effective model to a deep-learning-based object detection module for accurately identifying defects among dense beans. The proposed GALDAM can be used to greatly reduce labor costs, since the data labeling is the most labor-intensive work in this sort of solutions. Our proposed scheme brings two main impacts to intelligent agriculture. First, our proposed scheme is can be easily adopted by industries as human effort in labeling coffee beans are minimized. The users can easily customize their own defective bean model without spending a great amount of time on labeling small and dense objects. Second, our scheme can inspect all classes of defective beans categorized by the SCAA (Specialty Coffee Association of America) at the same time and can be easily extended if more classes of defective beans are added. These two advantages increase the degree of automation in the coffee industry. The prototype of the proposed scheme was developed for studying integrated tests. Testing results of a case study reveal that the proposed scheme can efficiently and effectively generate models for identifying defective beans with accuracy and precision values up to 80 % .

The Specialty Coffee Association Brewing Control chart has been used for the past 50 years, and is intended to assist the coffee brewer by stating the brew ratio and TDS (total dissolved solids) value needed to brew an “ideal” cup of coffee. Since coffee is a common and popular beverage that is consumed among populations ranging from children to elders, the objective of this study was to find out whether taste preferences in coffee vary based on age and whether these preferences match the current brewing control chart standard. Data collected in this study was based on a taste test with 32 total participants selected randomly. Of these participants, 10 fell into the 10-19 years old age range, 5 in the 20-29 range, 4 in the 30-39 range, 7 in the 40-49 range, and 6 in the 50-59 range. Based on the data from these respondents, no obvious trend between age range and coffee preference was observed; but, this is subject to change with larger sample sizes.Overall taste preferences, however, do generally fit the current standard ideal range on the coffee brewing control chart.

Coffee is an important economic crop and one of the most popular beverages worldwide. The rise of specialty coffees has changed peoples standards regarding coffee quality. However, green coffee beans are often mixed with impurities and unpleasant beans. Therefore, this study aimed to solve the problem of time-consuming and labor-intensive manual selection of coffee beans for specialty coffee products. The second objective of our study was to develop an automatic coffee bean picking system. We first used image processing and data augmentation technologies to deal with the data. We then used deep learning of the convolutional neural network to analyze the image information. Finally, we applied the training model to connect a webcam for video streaming recognition. We successfully divided the good and bad beans. The false positive rate was 0.1007, and the overall coffee bean recognition rate was 93%.

Specialty coffee is one of high quality coffees which have grown faster these past years. As a possible consequence of this fast growth, it is still difficult to understand the dynamic of this coffee segment with respect to its different definitions, market trends and its impact on producers' and consumers' decisions. As a main objective of this work, Spanish and Colombian consumers' preferences toward the origin and some specialty coffee attributes such as: Fair Trade, sustainable, organic, and gourmet were studied. It was used a choice experiment method as a quantitative technique to carry out this study. It has been found that Spanish and Colombian consumers are ethical consumers; they highly value Fair Trade coffee. However, Spanish consumers prefer organic coffee than Rainforest certified coffee in comparison with Colombian consumers. In both countries, the consumer preference for Colombian origin coffee was recorded.

The production of specialty coffees is the main criterion to add value to the product. However, there is a lack of information regarding genetic variability of C. arabica for quality improvement. The aim of this study was to analyze the genetic divergence among Coffee arabica genotypes regarding the potential cup quality, possible limitations and their potential use in breeding programs to improve quality. We evaluated 101 coffee genotypes from the Germplasm Active Bank of Empresa de Pesquisa Agropecuaria de Minas Gerais, covering different groups of genealogical origin. A randomized block design was used with two replications. Sensory analysis of the beverage was performed by two tasters per sample (repetition), using the Cup of Excellence methodology enhanced by the Brazilian Specialty Coffee Association. The attributes assessed were clean cup, sweetness, acidity, body, flavor, aftertaste, balance, overall and final score. K-means and Ward clustering methods were used to study the genotypes divergence. Based on sensory scores, the formed clusters differed with regards to all sensory characteristics (P ? 0.01). Three K-means clusters were formed among 40, 45 and 16 genotypes, with final average scores of 80.11, 83.17 and 87.56 points, respectively. Ninety percent of the genotypes evaluated have the genetic potential to produce specialty coffees. The observed divergence indicates the potential of genetic gains for quality and the Hibrido de Timor germplasm can be used for this purpose.

Research has been conducted to determine the Minang domain arabica coffee sensory quality profile, which can be used as a reference for specialty coffee. Seed processing is carried out at the research location (Solok Regency, South Solok Regency, Pasaman, Agam, and Fifty Cities) until the grain stage is wet (washed). Fianda Coffee Roastery carries out the coffee roasting process. Coffee uses W600i Roaster with a long roast method with two treatments, namely temperature 1800C for 15 minutes, temperature B 2000C for 10 minutes. The taste test was conducted at a two-door cafe and the Indonesian Coffee and Cocoa Research Institute Laboratory, Jember, East Java, following the SCAA. The test results showed that dry coffee beans' moisture content for all treatments was

Arabica coffee is Aceh’s leading commodity, apart from being an export product, it also plays an important role in the income of coffee farmers. Besides known as specialty coffee, Arabica coffee of Aceh has received international acknowledgment through several certifications, such as Fair Trade, Organic, or both, and other certificates. This study was conducted to develop sustainable development strategies for Arabica coffee of Aceh in the two largest coffee-producing districts, namely Bener Meriah and Aceh Tengah. Field study had been conducted from 1 December 2019 to 15 March 2020. Data were analysed by following the basic structure of the strengths, weaknesses, opportunities, and threats (SWOT) analysis. Sustainable arabica coffee can be carried out through implementing, monitoring, and evaluating policies related to coffee sustainability, increasing coffee productivity through climate-smart coffee practices, such as shade of coffee plantation, soil and water conservation, pest and disease control, development of new clones adapting to climate change, maintaining consistency of farmer’s coffee quality, increasing coffee production by social forestry patterns mainly for coffee farmers who are currently in protected areas, and encouraging millennials to enter the coffee business (particularly in the upstream area).

Carbon neutral labeling of food products is a market-based approach to reduce carbon footprints in the agri-food sector. To better understand consumers’ preferences and attitudes towards a carbon neutral label on globally traded agri-food products, the willingness to pay (WTP) of German consumers for a carbon neutral label on specialty coffee was examined. A discrete choice experiment was conducted in Germany, where coffee is often sold with multiple labels or claims, in order to examine the WTP for alternative combinations of a carbon neutral label with either a Fair Trade label or a claim of direct trade coffee sourcing. Choice data were analyzed using random parameter logit models which determined a positive WTP for the carbon neutral label. This estimate exceeds the corresponding marginal costs of certification and the marginal social cost of carbon, yet it is relatively lower than the estimated WTP for the Fair Trade label and the direct trade claim. A positive synergy effect on utility was also determined for the combination of a carbon neutral label and a direct trade claim. If no additional information was provided, consumers often perceived coffee as a “natural product” that does not generate any greenhouse gas emissions. Thus, awareness-building policies are needed to make carbon neutral labels an effective market-based tool to reduce greenhouse gas emissions in the agri-food sector.

This study proposed a classification model for 125 agricultural productive units (APUs) in Tolima, Colombia, to establish whether they are related to the quality of coffee produced. The model considered two aspects related to farmer profile and farm profile. The following proposed categories resulted from the coordinate obtained in relation to the two aspects: Low-Low, High-Low, Low-High, and High-High. The variables for each aspect were prioritized using the analysis hierarchical process (AHP). The coffee&rsquo, s quality, sensory profile by attribute, and specific descriptors for each category were determined employing the Specialty Coffee Association (SCA) protocol. The sensory attributes were analyzed by way of one-way analysis of variance (ANOVA), and the Bonferroni test was used to compare by category, both with a significance level of &alpha, = 0.05. The model grouped the APUs by category and cup quality, with the High-High category achieving the best scores in the sensory analysis. The variables with the greatest relative weight within the AHP model constituted farmer stance regarding the use of good agricultural practices (44.5%) and farmer attitude toward excellence (40.6%) in the farmer&rsquo, s profile. As part of the farm&rsquo, s profile, environmental commitment level (38.0%) and international certifications (29.1%) were the greatest relative weights. Coffee in the High-High category was characterized by its notes of cinnamon, cocoa, chocolate, and dried vegetables.

PGI Doi chaang coffee is one of well-known Thai Specialty Arabica coffee grown in the Northern plateau. Doi Chang village, which is located in Mae Suai district, is the largest Arabica coffee producing in Chiang Rai province. The total coffee growing area of Doi chaang coffee is around 3040 ha with a total production of roasted coffee bean over 700 tons per year. Doi chaang coffee is also certified by various quality standards such as USDA Organic Coffee, EU Organic Farming, Fairtrade, Member of Specialty Coffee Association of America and Europe, and Geographical Indication (GI) Thailand. A total of 70% of annual production goes to domestic market, while the rests export to international market including Asia, America, and Europe under organic, PGI, and fair trade label. The uniqueness of quality attributes of Kafae Doi Chaang causes of climate and topography, cultivation practices, and processing practices. The keys of sustainability performance of PGI Doi chaang coffee chain are strong relationship among coffee growers and supports from the stakeholders, especially the manufacturer, to develop the local economy and strengthen Kafae Doi Chaang’s positioning in the market.

This article examines how smallholders in Oaxaca, Mexico, experienced and responded to the recent coffee rust disaster, asking whether fair trade coffee producer organizations helped smallholders develop coping mechanisms to offset their vulnerability. It demonstrates how Oaxacan coffee producers were especially vulnerable during the recent rust outbreak due to long-term trends including a decline in governmental support for the sector dating back to the 1990s which resulted in a decline in producer incomes and a concomitant rise in the number of aging and poorly managed coffee plots that were more susceptible to coffee rust. The ongoing price volatility within coffee commodity markets and the continued restructuring of the specialty coffee market also increases the uncertainty producers face when determining how to best respond to the rust disaster. The article details the concrete ways in which fair trade coffee producer organizations help bolster the adaptive capacity of their members, while also noting areas for improvement.

The ecological settings in the Himalayan hills provide a unique opportunity to the resource-poor farmers in Nepal to sell their organically produced coffee as specialty coffee in the global market. However, there is little research about the cultivation methods and adoption of profitable technological upgrading in coffee cultivation in the country. Against such a back drop, this paper seeks to explore the factors that influence the small-scale coffee farmers’ decision to adopt technological upgrading such as wet processing in the farming process. Semi-structured interviews as well as focus group discussions were conducted in selected coffee-growing rural regions of Nepal. The cost-benefit analysis of different modes of coffee processing shows that the adoption of wet processing has a large potential of increasing the profit margins of farmers. Results from an adoption model identify education, book keeping on coffee activities, training, and access to credit and household location as the key determining factors for the adoption of technology upgrading.

Recent reports on caffeine intakes in the United States have highlighted the importance of obtaining accurate and valid measures of caffeine exposure. The objective of this study is to compare two methods of assigning caffeine values to beverages: brand-specific values versus an aggregate single value representing a broader range of products within a beverage category (i.e., category-specific). The two methods yielded some small, but statistically significant differences in the estimation of caffeine intake from coffee, tea, and carbonated soft drinks (CSDs) for all ages combined and within several of the adult age groups (i.e., 35-49, 50-64, and ≥65 years). These differences, while small, suggest that detailed brand-specific data, particularly for CSDs, commercially pre-packaged or bottled teas, coffee, and specialty coffee drinks, provide more accurate estimates of caffeine exposure for some age groups. Despite these differences, these data provide some assurance that studies using a single aggregate caffeine value provide reasonable measures of caffeine exposure, particularly for studies conducted over a decade ago when there were fewer caffeinated products and brand-specific data available. As the caffeinated beverage marketplace continues to evolve, the use of more detailed, brand-specific data will likely strengthen the assessment of caffeine exposure in the United States.

This paper presents a site suitability model for growing coffee in the island of Jamaica and how it can be used to assist the development of the Jamaican coffee industry as it seeks to regain the presence it once had in the specialty coffee market. Home to the Jamaica Blue Mountain coffee – one of the world's most exotic and expensive coffees, the industry has struggled in face of increased competition in the specialty coffee market and increasing costs of production. This decline in competitive advantage has forced stakeholders to seek innovative means to remain viable. This suitability model integrated the perspectives of local coffee stakeholders using the analytic hierarchy process to determine the weights for the biophysical and infrastructure criteria used in the suitability analysis. The results indicated that the most suitable locations for growing coffee in the island were in the mountainous core of central and eastern Jamaica, especially in and around the Jamaica Blue Mountain coffee region and the hills of south-central Jamaica. The results also highlighted areas with limited coffee production potential across the island. This model lays the groundwork for potential applications of the model such as its use in policy making decisions and scenario planning as the industry contemplates the possible impacts of climate change on coffee growing regions across the island. This suitability model promises to be a stepping stone in the creation of novel applications of geospatial technology in agriculture within small islands.

Land-use/land-cover change (LUCC) is a major cause of environmental transformation. Distant drivers, often associated with emerging markets for specific products, are now being considered one of the main factors of LUCC and are gaining attention in land change science. Consumers show an increasing interest in local and quality food, certified for its origin and its environmental production standards. A kind of agricultural product certification, Geographic Indication, identifies a product as originating from a specific region where a given quality, reputation or characteristic is attributed to its geographical origin. Sustainable land use is potentially an indirect effect of Geographic Indication, as it requires better land management in order to preserve the natural resources associated with the unique characteristics of the certified product. Located in the southern region of the state of Minas Gerais in Brazil is the region of Mantiqueira de Minas, considered one of the most important regions for the production of specialty coffees in Brazil. In 2011, the region’s tradition and reputation were recognized with a Geographic Indication, the second given for coffee regions in the country. To explore the full potential of this area for producing coffees with higher quality and meet the growing demand of this new international market, which aggregates value at specialty coffees, it became fundamental to understand the coffee environments of the region, the “terroirs” where these coffees are obtained. Geotechnology can give a significant contribution in filling this gap. This work is part of a research project that made a detailed characterization of the region’s coffee agroecosystems. Geotechnologies were employed to map the areas occupied by coffee plantations by using RapidEye satellite images and SPRING and ArcGIS software. All the segments of the environment were characterized and mapped in detail and the relations with coffee quality were evaluated. The results showed that coffee occupies approximately 8% of the region’s total area and is mostly distributed in the hilly areas with higher elevations. They also proved that specialty coffees are more likely to be obtained in altitudes above 1100 m, also being correlated to genotype and to the post-harvest methods employed. These results provide information that allows a better understanding of the factors involved in the expression of coffee quality. They also provide the scientific basis required for obtaining a new Geographic Indication for the Mantiqueira de Minas region, this time a Denomination of Origin (DO), which will certainly aggregate value to the specialty coffees produced in this unique region.

Classification green coffee beans is one of the main tasks during the quality grading process. This evaluation is normally carried out by specialist doing a visual inspection or using traditional instruments which have some limitations. This work is focused on the implementation of a computer vision system combining a hardware prototype and a software module. The hardware was made to guarantee the controlled conditions to capture the images of green coffee beans, the software is based on computer vision algorithms in order to detect defects of the coffee beans. The novelty of our proposal is the combination of algorithms to enhance the accuracy and the high number of defects detected. We applied a White Patch algorithm as an image enhancement procedure, color histograms as feature extractor and Support Vector Machine (SVM) for the classification task. It was constituted an image beans database of 1930 instances, and it was extracted 768 features, finally, the model was applied over 13 categories of defects described by the Specialty Coffee Association of America (SCAA). Results of classification achieved a 98.8% of overall accuracy detection, therefore the proposed system proved to be effective in classifying physical defects of green coffee beans. With this work we showed that the grading green coffee process can be automatized, adding a new paradigm in quality evaluation task to enhance the coffee industry.

As Mark Stell waited to board the plane to Bujumbura, the capital city of Burundi in Africa, he contemplated an exciting market opportunity for his coffee roasting company. Within a few short weeks, Portland Roasting Company (PRC) was pitching to Fred Meyer, a major regional grocery retailer, and landing this account could help grow revenues by as much as 25%. Last year, Stell had made significant investments in new roasting and packaging equipment and he knew he had the capacity and infrastructure to supply a large account. PRC would also promote the virtues of the Farm Friendly Direct (FFD) program. From the beginning, PRC had developed trade relationships with individual coffee growers, paid premium prices, and invested additional funds in local projects that directly benefited the lives of coffee farmers and their communities. In 2005, PRC was awarded the prestigious Sustainability Award by the Specialty Coffee Association of America (SCAA). The FFD program is featured on the company website, in marketing materials and on product packaging (Exhibit 1). PRC would have to convince the client that ‘Farm Friendly Direct’ coffee was superior to conventional third-party certifications such as FairStell also realized that the FFD program alone would not be sufficient to secure the account. Grocery retailers were also concerned about price, order fulfillment, marketing support, product quality and customer service, in addition to the sustainability attributes of a product. As the last boarding call rang out over the loudspeaker, Stell picked up his laptop bag and headed for the departure gate.

This study was developed to determine the beverage quality and the sensory profile of Coffea arabica accesses of the Germplasm Collection of Minas Gerais State in two consecutive harvests. Mature coffee fruits from 49 accesses were selectively harvested in the 2015 and 2016 harvests, and after processing and drying they were sensorially evaluated by a team of trained judges in accordance to the protocols of the Specialty Coffee Association. The data were analyzed by Principal Component Analysis, Cluster Hierarchical Analysis, and Content Analysis. The year of harvest influences the scores of the sensory attributes of the beverage of some coffee accesses. The access 27 (Pacamara) stood out with the highest sensory score seen in the first year of harvest. The accesses 36 (Timor Hybrid UFV376-52) and 43 (BE5 WushWush) stood out for the final sensory score in the two years of evaluation. All accesses belonging to the Timor Hybrid Germplasm stood out in the beverage quality in the second year of harvest. A total of 139 sensory attribute descriptors were identified, and the content analysis showed different levels for the frequency of terms in each access group formed as a function of quality. The Germplasm Collection of Minas Gerais has a wide variability for the production of superior quality coffees, and the year of harvest influences to a greater or lesser degree the potential of quality of the accesses.

The main objective of this study was to identify the actors in the coffee value chain in Zambia as well as to identify and assess the opportunities and employment creation potential of the value chain. The study found that the potential for the growth of the coffee sector lies in Zambia's production of the globally competitive Arabica coffee variety; the increasing global demand for specialty coffee in premium niche markets (mainly based on fair trade and organic farming principles); and the existence of institutional arrangements such as the Zambia Coffee Growers Association that promote, regulate and coordinate the development of coffee in Zambia. However, despite this potential, the coffee sector has been experiencing a downward trend in production and export of coffee beans. While a wide range of constraints from production to policy issues limit the growth of the coffee sector, the most noteworthy factors are the long production period of the coffee plant which acts as a disincentive to invest in coffee production; the lack of research programmes; limited Zambian brand recognition; and the lack of accessible and affordable financing for coffee growers. Sustainable growth and employment creation in the coffee sector can be achieved through coherent strategies such asthe government working with the private sector to come up with innovative ways of availing affordable financing mechanisms for farmers. The government should also facilitate the development of technologies and marketing strategies to ensure that Zambian coffee fetches premium prices on the world market.

To date, there has been little empirical focus on how different online mediums affect the branding practices of retailers. In this working paper, I compare how specialty coffee retailers of different sizes use webpages and Twitter. I examine over 2800 unique images from 86 retailers using a quantitative content analysis that enumerates visual elements within pictures. I find that there are significant differences in the use of these two mediums in terms of retailer scale, and that based on their size, retailers display different types of images at much different proportions.

Since the early days of the specialty coffee movement, freshness has been one of its central pillars. Freshness is best defined as having original unimpaired qualities. In coffee, it is most often seen as freshly roasted, ground within a few days, immediately extracted, and consumed. But despite this pivotal role of freshness for high quality coffee, the objective and scientific measurement of freshness have often been vague and elusive. How can one measure the level of freshness of coffee? In this chapter we will outline two approaches. One is based on the degassing of the freshly roasted coffee and the other on the evolution of its aroma profile during storage. In terms of the evolution of the aroma profile, we will introduce one particular freshness index: the ratio of dimethyl disulfide to methanethiol, suited to assess the evolution of freshness of roasted coffee during storage. Although this ratio has been shown to increase during storage, the speed at which this freshness index increases depends on the packaging and storage temperature. This has opened the possibility to use this index to assess the freshness of roasted coffee and compare the quality of different packaging materials for preserving the freshness of the coffee inside.

StarbucksTMCoffee Company has more than 25,000 retail stores in 75 countries and is the premier roaster and retailer of specialty coffee in the world. Starbucks’ mission is „to inspire and nurture the human spirit – one person, one cup and one neighborhood at a time” and its slogan has been to bring their customers exceptional experiences. McDonald'sTM, in turn, is one of the world's largest fast-food restaurant chains, serving approximately 69 million customers daily in over 120 countries across approximately 36,900 outlets. McDonald’s doesn’t mention any real mission in their company profile, but the strong slogan “I am loving it” describes well the company’s mission as well as the customer experience they hope to give their customers. The new trend in large international companies is that it is no longer customer satisfaction that is important, but customer experience, which along with products or services carries a lot of weight in customers’ final decision making. The purpose of this research was to examine the formation of and to measure customers’ conscious experience of products and services in the business to consumer environment with two student groups in Poznan, Poland. The research was carried out in a Starbucks coffee shop as well as in a McDonald’s fast food restaurant in Poznan, Poland with a fuzzy logic based customer experience application. The research clearly shows the possibilities to monitor, develop and improve the degree of conscious as well as unconscious areas of customer experience. Furthermore, the test results were used to verify and validate the usability and structure of the ontology and the used application. The application operated well, and the test groups were satisfied with both the operation of the application as well as the collective results, which are presented in this article. Finally, some possible future actions related to the customers’ conscious and unconscious experiences are suggested.

The quality and flavor of a coffee cup are a result of the variety, the environmental offer, the agricultural practices, as well as the process followed to obtain the green beans that are finally roasted and ground. Coffee has many opportunities to vary both dry and wet processes, and the combination of the two emphasize some attributes that satisfy customers regarding new flavors and tastes. This chapter describes the processes used to obtain a stable product, some variations discovered by scientists and growers to achieve some special characteristics and well-known types of coffee, and the tools and methodologies to produce them in a consistent way. This chapter also has as an objective to encourage the creativity of scientists and growers to continue to investigate original ways to process coffee in a qualitative and sustainable manner. The socioeconomical aspect is implicit as specialty coffee has better prices in the market.

Development of specialty coffee product needs to be done by producing a product that has a good flavor, unique, and different from the axisting specialty coffee products. One of the varieties of Arabica coffee that has good potential to be developed into a specialty coffee is Maragogype coffee. This paper discusses the results of selection and characterization of physical and flavor quality of Arabica coffee varieties Maragogype in East Java. Selection was done in PTPN XII at Pancur/Angkrek and Kayumas Estate. It was obtained two superior genotypes those have high productivity and good taste, they are MP3 and MP4 with of productivity of 7,985.3 and 5,985.3 g cherries/tree, respectively. Maragogipe varieties showed good physical quality, in which 99% of bean belong to the large been category, whiches the highest of 1,000 beens, and good bulk density and apparent swelling. MP3 genotype had a floral, citrus acidity, mild, and very good sweetness characteristics. MP mix had the showed same characteristics, but its intensity was not as high as MP3. MP4 has herbal and flora characteristics with bitter after taste.Key words : Coffea arabica, maragogype, specialty coffee, characterization, selection, flavor, variety.

The purpose of this study was to analyze the general characteristics of coffee house consumers as well as the importance and satisfaction of selection attributes of specialty coffee houses according to length of coffee education period. Applicants in the Gwangju and Jeonnam area who had finished their Barista 2 grade certificate examination participated in a survey on March 12, 2011. Further, university students living in Gwangju participated as subjects who had never experienced coffee education from March 15 to March 31, 2011. Two-hundred and one subjects participated in the survey, and 184 questionnaires were used for analysis. Regardless of coffee education experience, quality of coffee was important, but higher educated subjects showed the lowest satisfaction of coffee from a coffee house (p

Efforts to implement an integrated pest management (IPM) program for coffee berry borer Hypothenemus hampei (Ferrari) in a 110-ha coffee plantation in the Huila region of Colombia are discussed. Hands-on training was provided for farm staff and harvest workers managing production in >80 coffee lots. Participants attended workshops describing pest management strategies, based on prior research and recommendations of the National Coffee Research Center in Colombia (Cenicafe). The training program focused on cultural practices, i.e., efficient harvesting of mature berries to eliminate coffee berry borer habitats, along with establishing a comprehensive monitoring program to reduce chemical insecticides and encouraging use of a biological-based insecticide. Participants implemented postharvest techniques by screening harvested berries and pulp pits to physically exclude adult coffee berry borers. The rationale was that adopting new practices would enable growers to transition away from chemical insecticides. Results over 3 yr showed widespread adoption of cultural, physical, and biological control methods. Overall, the IPM program was considered successful because problems associated with insect damage on the coffee crop decreased, despite reductions in endosulfan/chlorpyrifos use, which declined from 250 liters in 2002 to 75 liters in 2003, and 0 liters in 2004. Concurrently, Beauveria bassiana increased from 20 kg in 2002 to 80 kg in 2004. Harvest workers improved their efficiency at removing potential coffee berry borer breeding sites (leaving only 6.5 mature berries per tree in 2004, down from 22.2 in 2002). The quality of parchment coffee beans increased (insect damage was 2.3% in 2002, 1.7% in 2003, and 0.7% in 2004) whereas the proportion of the harvest sold as high quality ‘specialty’ coffee increased from 50% to 86% over the same period.