Coffee Production Research Articles

Fractional order for the transmission dynamics of coffee berry diseases (CBD)

Abstract Coffee berry diseases (CBD) pose significant threats to coffee production worldwide, affecting the livelihoods of millions of farmers and the global coffee market. Fractional calculus provides a powerful framework for describing non-local and memory-dependent phenomena, making it suitable for modelling the long-range interactions inherent in CBD spread. This study aims to formulate and analyse fractional order model for CBD transmission dynamics in the sense of Atangana–Baleanu–Caputo. Fixed point theorems were utilised to test the existence and uniqueness of the model’s solutions using fractional order. The basic reproduction number was calculated utilising the next-generation matrix. The model has locally asymptotically stable equilibrium positions (disease-free and endemic). Furthermore, the Lyapunov function was used to conduct a global stability analysis of the equilibrium locations. A numerical simulation of the CBD model was created using the fractional Adam–Bashforth–Moulton approach to validate the analytical findings. Our findings contribute to the development of more accurate predictive models and inform the design of targeted interventions to mitigate the impact of CBD on coffee production systems.

Inovasi Produk Kopicek (Kopine Wong Picek) Sebagai Upaya Pemberdayaan Kelompok Difabel Tunanetra Mata Hati

Coffee is an important commodity with significant global demand. In Indonesia, East Java Province contributed 85.15% of the national coffee production in the Large Estate sector in 2022, supporting the growth of the local coffee industry such as coffeeshops. In Surabaya, the Mata Hati Community, consisting of people with disabilities, launched a coffee brand called "Kopicek" as an effort to empower disabled individuals, especially the blind. However, they face challenges in terms of quality control, manual production processes, and limited promotion. To carry out and create innovations in empowering the visually impaired or the blind, our team provides mentoring and training to improve the quality and efficiency of Kopicek's production. Through a community service program, the social service team designed solutions to improve the quality and efficiency of Kopicek's production. These solutions include quality control training, provision of automated coffee machines and custom packaging press machines that are accessible to blind baristas, as well as digital marketing training. The results of this program are expected to help the Mata Hati Community maintain coffee product consistency, expand marketing through digital media, and enhance Kopicek's branding in the local market.

Producción de café biodiverso en México: calidad, beneficios y controversia sobre el cambio de variedades por la roya

Intervention in any territory requires a careful assessment of environmental and cultural aspects, especially in the framework of territorial development. The objective of this study was to highlight the importance of conserving biological and cultural biodiversity in the main coffee growing of Mexico, and to analyze the challenges facing biodiverse coffee production. An updated regional typology was used to analyze the socio-economic dynamics of four states that will account for 90 % of national coffee production in 2020. The study examines the biological and cultural diversity of these areas in the context of public policies implemented between 2012 and 2016, which promoted varietal conversion as a phytosanitary measure to combat coffee rust (Hemileia vastatrix Berk & Br., 1869). This policy has generated an ongoing debate among producers, markets and specialists, who discuss the dilemma between maximizing production and preserving the quality and biodiversity of the territories. Finally, arguments are presented in favour of biodiverse coffee production driven by local communities, and the available legal framework for its protection, highlighting the right to be consulted in the implementation of future projects and policies.

Respuesta morfométrica de seis variedades de café (Coffea arabica L.) durante las épocas lluviosa y seca

The research emphasizes the need to improve coffee production and sustainability. The study of the agronomic response of six coffee varieties (Coffea arabica) during the rainy and dry seasons under different climatic conditions in Guasaganda, with the aim of analyzing how factors intervene in growth and identifying the most suitable variety to optimize production. . The research was carried out at the "Sacha Wiwa" Experimental Center at an altitude of 510 meters, with an average annual temperature of 23ºC and sandy loam soil. The study used a completely randomized block design to evaluate six coffee varieties during the rainy and dry seasons. Variables measured included plant height, stem diameter, and number of branches. The results indicated that the Sarchimor variety had the highest plant height with 165.58cm in the rainy season and 188.07cm in the dry season, followed by Bourbon with 126.99cm in the rainy season and 141.54cm in the rainy season. The Geisha variety showed the best production in stem diameter with 3.02cm in the rainy season and 3.35cm in the dry season. Regarding the number of branches, Sarchimor with 30, 93, Catimor with 28.70 and Geisha with 30.30 had the best performance during the dry season, while Sarchimor with 35.64 and Geisha with 35.70 led during the season. rainy The study concludes that the Sarchimor and Geisha varieties demonstrated superior agronomic results, being suitable under the climatic conditions of Guasaganda.

Interacción entre la densidad poblacional y fertilización para café robusta en Isidro Ayora, Guayas

The objective of the research was to establish the influence of population density in robusta coffee in relation to chemical and organic fertilization, conducted in the locality of Isidro Ayora, Guayas Province, characterized by a tropical very dry forest life zone over a period of 48 months. The study evaluated the factors of population density (1,333; 1,666; 2,222, and 2,500 plants per hectare) and fertilization plan (chemical and organic) in robusta coffee. The experiment was set up using a Randomized Complete Block Design in a 4 x 2 factorial arrangement (densities x fertilization plan), in a Split-Plot layout, with 8 replications. The results defined that a density of 1,666 plants per hectare, combined with adequate chemical fertilization, proved to be the most efficient factors in terms of robusta coffee production, considering both agronomic and health variables. It is also indicated that the study recommends that higher densities require a more rigorous resource management and more intensive agronomic management in areas similar to the study site.

An Examination of Ethiopian Data on the Coffee Value Chain from a Systemic Perspective

Ethiopia's principal export crop is coffee. Currently, one of the most profitable exports for nations in East Africa, including Ethiopia, Uganda, Kenya, and Tanzania, is coffee. Ethiopia is recognized as the source and major hub of Arabica coffee varietal. Global coffee production is insignificant, with over 70 nations and approximately 25 million growers producing coffee. Seventeen percent of coffee producers worldwide are from Ethiopia. Ethiopia, which produces 4.46 percent of the world's coffee, is the world's fifth-largest producer, behind only Brazil, Vietnam, Colombia, and Indonesia. the biggest and most prolific grower in Africa, making up around 43.15% of the continent. Ethiopian coffee varieties vary greatly in terms of genetic variety. The nation has also captured the attention of the world because of its inherent. More than 60% of the world's coffee is produced by the top three countries—Brazil, Vietnam, and Colombia together. Ethiopia is the eighth-largest supplier of coffee to the world market, accounting for 3–3.7 percent. Sixty countries import coffee from Ethiopia. The top 10 countries to import Ethiopian coffee, in terms of value, were Italy, Germany, Saudi Arabia, Japan, Belgium, South Korea, China, the United Arab Emirates, and Taiwan. They make up 84% of the whole. Japan moved up from sixth place in 2020–2021 to fourth place in the world for coffee imports in 2021–2022.

Machine learning techniques for coffee classification: a comprehensive review of scientific research

In the realm of agribusiness, transformative shifts are underway, propelled by the growing demands and expanding scales of grain production. This evolution calls for a critical reevaluation of the existing paradigms in coffee production and marketing paradigms, with a specific focus on integrating Artificial Intelligence (AI). This work aims to review, synthesize, and summarize the available data regarding how Machine Learning (ML) has been used to detect and classify characteristics in coffee beans and leaves. For this purpose, a comprehensive literature review of the most significant research contributions describing the application of AI for advanced classification techniques in coffee agriculture has been carried out. Our analysis suggests that implementing AI technologies allows the classification of coffee, encompassing various attributes such as maturity, roast intensity, disease identification, flavor profiles, and overall quality. More largely, this technological advancement holds the potential to revolutionize coffee farming by providing producers and agricultural specialists with sophisticated tools to enhance production efficiency, minimize costs, and improve the accuracy and confidence of their decision-making processes. The motivation for the literature review is to address the increasing global demands and evolving scales of grain production, particularly in coffee farming, by critically reevaluating existing paradigms and integrating AI techniques. This review aims to synthesize and summarize how ML has been utilized to detect and classify various characteristics of coffee beans and leaves, thereby highlighting the potential of AI to revolutionize coffee farming by enhancing production efficiency, minimizing costs, and improving decision-making accuracy. This article presents the latest studies in ML in the coffee area, observes the methodology used, and allows researchers to develop new solutions that cover gaps in the literature, open problems, challenges, and future trends, bringing a real contribution to the scientific field. Finally, this article gathers and presents the databases used in many studies, which may be useful for future ML projects.

ANALISIS DESKRIPTIF KUALITATIF IMPLEMENTASI WORD OF MOUTH DALAM KOMUNIKASI PEMASARAN PRODUK BROOKLAND COFFEE

This research aims to explore and describe exactly how the application of word of mouth marketing communication in Brookland Coffee's product marketing strategy. The research method uses a descriptive qualitative approach by conducting direct observations and in-depth interviews with key informants consisting of the owner, baristas, and consumers of Brookland Coffee. The results showed that Brookland Coffee consistently implements a word of mouth strategy by prioritizing aspects of trust and consumer confidence. This strategy is implemented through a family approach, networking, and community building, especially the bicycle community. The research conclusion revealed that the effectiveness of word of mouth succeeded in strengthening Brookland Coffee's marketing communications, supported by consistent product quality, good service (hospitality), and the use of Instagram social media as a supporting platform for marketing strategies. Brookland Coffee succeeded in building a strong brand identity through a combination of offline and online word of mouth communication.

Impact of FTC's Allegation on Amazon's Marketplace: Evidence From Coffee Products

ABSTRACTHow do firms respond to regulatory allegations? The monopolist lawsuit by the Federal Trade Commission (FTC) against Amazon provides an avenue to answer this question. Applying difference‐in‐differences to panel data of ground coffee products from Amazon's marketplace in the United States and Canada, we find that Fulfillment by Amazon (FBA) fees were reduced by $0.27–$0.29 per product in the United States due to the FTC's monopolist allegation. We also find that the allegation led to price reductions of $0.79–$0.92 per product in the country. Since 42% of the 7.5 billion products sold on Amazon United States in 2023 were by FBA sellers, we estimate that the allegation led to an annual savings of $0.85 billion to $0.91 billion for the FBA sellers and $5.92 billion to $6.85 billion for Amazon's customers on average. These results suggest that the FTC's allegation had sizeable and positive welfare impacts on Amazon's third‐party sellers and customers, making it a significant win for the regulatory agency. Moreover, our study provides insights into the implications of the FTC allegation for agribusiness stakeholders and the future of grocery shopping.

Huir, regresar y volver a empezar. Familias cafeteras y conflicto armado en Ciénaga, Magdalena

Although issues around coffee production have been extensively studied in Colombia, there are few studies on the relationship between coffee cultivation and armed conflict. This article is the product of a qualitative study with coffee growers —mainly women— from the municipality of Ciénaga (Magdalena), and contributes to analyzing the relationship between coffee and armed conflict in a local context. It shows how the latter has impacted the former as well as family incomes and wellbeing by breaking community and organizational ties and changing daily life. Additionally, it helps to understand the role of families and women in coffee production, and how they help to mitigate the armed conflict. It also shows how migrations, peasant traditions and knowledge, families, and the empowerment of women have allowed them to survive in territories affected by those dynamics and violent actors.

A Combined TG–FTIR Study on the Pyrolysis of Waste Generated in the Coffee Production Chain

A Combined TG–FTIR Study on the Pyrolysis of Waste Generated in the Coffee Production Chain

Application of Spectral Imaging and Vegetation Index in Latin American Coffee Production: A Systematic Mapping

ABSTRACTCoffee production is a crucial economic, social, and cultural pillar in Latin America, facing numerous challenges, including integrating technological advancements such as multispectral imaging. This approach offers multiple advantages for coffee production; however, a knowledge gap in the domain is the need to methodologically review the available empirical evidence to delineate the field and the study region. Therefore, this systematic mapping aims to map the scientific corpus of multispectral imagery and vegetation index implemented in coffee production in the Latin American region. The study followed the PRISMA protocol; 42 primary studies were analyzed to identify key trends and research gaps. The main result of this research is that NDVI emerged as the most widely used spectral index, with applications in estimating critical biophysical parameters such as biomass and chlorophyll content. Other indices such as GNDVI, NDRE, and SAVI also proved valuable in assessing coffee plant health and development. There was an emerging trend to integrate multispectral imaging with machine learning techniques, promising greater accuracy in data interpretation. The study also revealed a concentration of research efforts in selected Latin American countries, particularly Brazil, indicating opportunities to expand research in other coffee‐producing regions. The study's main conclusion is that multispectral imaging, mainly through vegetation index, has emerged as a valuable tool for phenological monitoring and management of coffee production, offering several advantages over traditional methods. Finally, this review contributes to the existing knowledge base and identifies future research directions for applying multispectral imagery to sustainable coffee production in Latin America.

Estimating coffee crop parameters through multispectral imaging and machine learning algorithms

Abstract. Brazil plays a crucial role in the global economy due to its significant contribution to the agricultural sector, particularly in coffee production, where it stands out as the largest producer and exporter of processed coffee. Various disturbances can influence coffee plants, causing abnormalities that can hinder their successful growth. Parameters such as plant height and canopy diameter play an essential role in assessing the health and productivity of the plants, reflecting their growth, development, and ability to capture sunlight. Additionally, height is also related to the balanced distribution of nutrients and water, providing valuable information about overall performance and the capacity for healthy production. In this regard, the application of methodologies involving remote sensing and machine learning algorithms has shown promising results in the rapid and safe acquisition of information about agricultural systems. This study evaluates different machine learning algorithms, using radiometric values from multispectral images obtained by remote sensing platforms as input datasets for estimating plant height and canopy diameter in coffee cultivation. The best performance was observed for architectures that showed lower RMSE and RMSE% values. For the plant height parameter (m), the RGB sensor exhibited the best performance using the Random Tree algorithm, with an RMSE (0.27) and RMSE% (8.80). For the canopy diameter (m), the sensor showed the best performance using the Random Forest algorithm, with an RMSE (0.15) and RMSE% (8.16).

UAV imaging for spectral characterization of Coffee Leaf Miner (Leucoptera coffeella) infestation in the Cerrado Mineiro region

Abstract. Brazil, the world's largest coffee producer, faces challenges managing the coffee leaf miner (Leucoptera coffeella), a significant pest. This study suggests remote sensing for pest control decisions. Two experimental areas in the Cerrado region of Minas Gerais State were analyzed to spectrally characterize infested plants and estimate the number of mines per plant. Results show the ability to differentiate infested plants with greater reflectance variance in the near infrared at 850nm. The performances of the three machine learning algorithms were compared. Determining the number of mines in the group of most infested plants demonstrated slightly higher precision, achieving an RMSE of 22.69% using the Support Vector Machine algorithm. Conversely, the group of least-infested plants obtained the best result with the Random Forest algorithm, achieving an RMSE of 32.47%. These promising results indicated that CLM can be detected using aerial multispectral imaging data.

Analisis Pengembangan Strategi Bersaing Limasan Cafe Karawang

Limasan Karawang Coffee Shop, as one of the micro, small and medium enterprise (MSME) units in Karawang, has become a popular destination for young people and teenagers to enjoy the cafe atmosphere and the various coffee products on offer. This research aims to identify and analyze the competitive strategies that have been implemented by the Limasan Karawang Coffee Shop. This research uses qualitative descriptive analysis. Business Model Canvas (BMC) analysis is used to do this. Primary and secondary data were used in this research. Primary data was obtained from observations and in-depth interviews related to creating competitive strategies for the Limasan Karawang Coffee Shop which was the subject of the research. The results of research conducted by researchers in a study entitled "Analysis of the Competitive Strategy Development of Limasan Cafe" using the Business Model Canvas Approach confirm that the Business Model Canvas is an effective method as a foundation for generating strategic alternatives and establishing new strategies for the company. To help define, analyze, Designing a business model, the Business Model Canvas (BMC), consists of nine elements that represent all aspects of the business. This concept can serve as an effective tool for describing business models and developing new strategies

Study of decaffeination and business risk feasibility: Arabica and Robusta Arjuno coffee beans by anaerobic fermentation using Rhizopus oligosporus

Indonesia is the fourth largest coffee producer in the world. However, coffee is generally sold in its original form, even though the diversification products of coffee, such as decaffeinated coffee, have a higher selling price. One of the coffee-producing areas in Indonesia is Malang-East Java which has superior coffee commodities and does not yet have diversified products, such as Arjuno coffee (Arabica and Robusta) originating from the Mount Arjuno area. In this work, the decaffeination of Arabica and Robusta Arjuno coffee was conducted through anaerobic fermentation by Rhizopus oligosporus. An analysis of the business feasibility and production risk was also carried out. The results showed that caffeine content in the coffee significantly decreased with fermentation time. The caffeine content in Arabica and Robusta Arjuno coffee beans after 72 hrs of fermentation declined by 19.9% and 57.8% to 2.3% and 1.7%, respectively. Fermentation did not significantly change the physical of the beans but enriched the taste of coffee, where the flavor was strongly affected by the fermentation time. The analysis of the business feasibility and production risk showed that the decaffeinated Arabica and Robusta Arjuno coffee business provides a profit seven times higher than the existing coffee business.

Economic Viability of Coffee Plants Cultivated in Agroforestry Systems in Southwest Goiás

Brazil is the world's leading coffee producer. Increased productivity has been observed in recent harvests due to new management and automation technologies. Even with the expectation of a reduction in national production, the state of Goiás has shown an increasing share in coffee production. The municipality of Rio Verde, in Goiás, is among the eight largest coffee producers in the state and is where the Fazenda da Mata enterprise, the main object of this research, is located. The objective of the research is to evaluate the performance of the production of Arabica coffee grown in an agroforestry system through studies on economic feasibility comparing the implementation costs plus the estimated costs and revenues of AFS with the conventional cultivation system. Coffee growing in AFS is a production system that requires research that presents results on economic analysis, thus the aim was to research the economic feasibility of growing coffee in AFS as a sustainable alternative for agribusiness, whose information can contribute to the decision-making of rural managers when comparing a conventional cultivation enterprise to AFS cultivation. Furthermore, AFS can contribute to increased agricultural productivity with less impact on the environment, revealing several possibilities of subsystems that can be applied to large, medium and small rural properties, considering the financial advantages and also the motivating values ​​that direct the farmer towards this agricultural activity. The economic analysis showed that the conventional cultivation system is more advantageous financially, however AFS also presented excellent results. Therefore, it is important to highlight other relevant factors that can be considered when deciding which cultivation system to use in coffee production. Although AFS presented lower financial results than the conventional system, it is a cultivation system that can provide a second source of income for the producer, such as the use of tree species.

Effect of Processed Coffee Husk on Feed Intake, Nutrient Digestibility, Body Weight Changes and Economic Feasibility of Bonga Sheep Fed on Natural Pasture Hay as a Basal Diet.

Ethiopia is one of the world's coffee producers, generating about 192,000 metric tonnes of coffee husks annually as by-products. The material can be used for ruminant diets to improve the nutrient utilisation of animals. However, coffee husk has toxic compounds, which can be minimised through different processing methods. Though the above techniques can minimise the toxicity level of coffee husk and increase the bioavailability of nutrients, there is scanty information on the comparative efficacy of these techniques, especially in ruminant nutrition. The study was conducted to examine the effect of processed coffee husk on feed intake, nutrient digestibility, body weight changes and profitability of Bonga rams based on natural pasture hay. In the experiment, 24 rams were used, and the rams were grouped into six blocks based on initial body weight (mean BW 21.5 ± 1.01kg). The rams were quarantined for 21 days, and each ram was randomly assigned to one of the experimental feed treatments in a randomised complete block design (RCBD). The experimental treatment feeds include 400g conventional concentrate mix (CM) containing Noug seed cake and wheat bran (T1); 200g boiled coffee husk + 200g CM (T2); 200g roasted coffee husk + 200g CM (T3) and 200g raw coffee husk + 200g CM (T4). The CM was made in the ratio of 1:1. The data collected from the 90-day experimental period were: dry matter and nutrient intakes, initial body weight, final body weight and body weight changes. After the growth experiment, a 7-day digestibility trial was followed by collecting faeces using a harness bag. The data were managed using Microsoft (MS) Excel 2010 and analysed using R software (v. 4.3.2). The chemical compositions of the CM had maximum crude protein (22%), followed by boiled coffee husk (14.74%), which was higher than natural pasture hay (6.91%) and raw coffee husk (12.4%). The total dry matter intake (p < 0.05), metabolisable energy, and total nutrient intakes of rams were significantly (p < 0.001) maximised when rams fed on boiled coffee husk (T2) than raw (T4) and roasted (T4) coffee husk, except for NDF and organic matter intakes. The apparent digestibility of nutrients and feed conversion efficiency were maximised for rams assigned to T2. There was maximum daily body weight gain (p < 0.001) when rams were supplemented with boiled coffee husk (T2). Also, body weight changes of rams were significantly (p < 0.001) higher for rams supplementation with boiled coffee husk. Therefore, the boiled coffee husk as an alternative feed resource can be replaced by about half of the commercial CM without adverse effects of anti-nutritional factors and enhance the income of smallholder farmers in the coffee crop-livestock production system.

Local Coffee Product Development Strategy

Kopi Kali Place is one of the popular coffee shops in the North Jakarta area that has been established since 2019. The purpose of this study is to determine the market penetration and development of local coffee products of Coffe shop Kopi Kali. This study uses a descriptive qualitative approach to understand the development of local coffee products in Kopi Kali Coffee shop. The research methods used include in-depth interviews, participatory observation, documentation, and data triangulation. The results of the research show that Kopi Kali Coffee shop, since its establishment in 2019 until 2024, has undergone an impressive evolution in facing challenges and changes in the coffee industry. With strong adaptability and a high commitment to innovation, Kopi Kali has successfully developed an effective market penetration strategy. The main focus on innovative product development such as the transformation of "Kopi Belies" into a non-alcoholic version and the introduction of a variety of excellent coffee menus demonstrates a dedication to maintaining quality and creating a variety of flavors that appeal to customers. Smart marketing strategies, including the use of social media and partnerships with influencers, have been successful in increasing brand awareness and reaching a wider market segment.

Economical-epidemiological analysis of the coffee trees rust pandemic.

Coffee leaf rust is a prevalent botanical disease that causes a worldwide reduction in coffee supply and its quality, leading to immense economic losses. While several pandemic intervention policies (PIPs) for tackling this rust pandemic are commercially available, they seem to provide only partial epidemiological relief for farmers. In this work, we develop a high-resolution spatiotemporal economical-epidemiological model, extending the Susceptible-Infected-Removed model, that captures the rust pandemic's spread in coffee tree farms and its associated economic impact. Through extensive simulations for the case of Colombia, a country that consists mostly of small-size coffee farms and is the second-largest coffee producer in the world, our results show that it is economically impractical to sustain any profit without directly tackling the rust pandemic. Furthermore, even in the hypothetical case where farmers perfectly know their farm's epidemiological state and the weather in advance, any rust pandemic-related efforts can only amount to a limited profit of roughly 4% on investment. In the more realistic case, any rust pandemic-related efforts are expected to result in economic losses, indicating that major disturbances in the coffee market are anticipated.