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The editorial in the Frontiers in Pharmacology journal explores the potential of probiotics and their metabolites in cancer therapy, emphasizing their role in modulating immune responses and enhancing innate immunity. The research highlights the anticancer properties of probiotics and calls for further human trials and molecular mechanism studies to fully establish their effectiveness. Additionally, the document provides information on various plant species used in Brazilian folk medicine, detailing their traditional names, growth forms, parts used, preparation methods, and applications for treating ailments like headaches, stomachaches, malaria, and skin conditions, showcasing the diverse medicinal practices of different cultures. [Extracted from the article]

Societal Impact Statement Summary Despite strong historical declines, Guadeloupe and Haiti's coffee sectors remain important to rural communities' livelihood and resilience. Coffee also holds value as part of the islands' historical legacy and cultural identities. Furthermore, it is often grown in agroforestry systems providing important ecosystem services, which will become more important as these vulnerable islands work to adapt to a changing climate. Current efforts to revitalize coffee farms and target strategically important specialty markets would benefit from understanding existing genetic resources and the historical factors that shaped them. Our study reveals the rich history reflected in current coffee stands on the islands. The West Indies, particularly former French colonies like Haiti and Guadeloupe, were central to the spread of coffee in the Americas. The histories of these Islands are shared until the 19th century, where they diverged significantly. Still, both Islands experienced a strong decline in their coffee sector. Characterizing the genetic and varietal diversity of their coffee resources and understanding historical factors shaping them can help support revitalization efforts. To that end, we performed Kompetitve Allele‐Specific PCR (KASP) genotyping of 80 informative single nucleotide polymorphism (SNP) markers on field samples from across main coffee‐growing region of Guadeloupe, and two historically important ones in Haiti, as well as 146 reference accessions from international collections. We also compared bioclimatic variables from sampled geographic areas and searched for historical determinants of present coffee resources. At least five Coffea arabica varietal groups were found in Haiti, versus two in Guadeloupe, with admixed individuals in both. The traditional Typica variety is still present in both islands, growing across a variety of climatic environments. We also found Coffea canephora on both islands, with multiple likely origins, and identified C. liberica var. liberica in Guadeloupe. These differences are explained by the Islands' respective histories. Overall, Guadeloupe experienced fewer, but older introductions of non‐Typica coffee. By contrast, several recent introductions have taken place in Haiti, driven by local and global factors and reflecting the history of Arabica varietal development and spread. Diversity on these islands is dynamic, and our results reveal opportunities and limits to the future of Guadeloupean and Haitian coffee. [ABSTRACT FROM AUTHOR]

The Gedeo zone agroforestry systems are the main source of Ethiopia's coffee beans. However, land-use and suitability analyses are not well documented due to complex topography, heterogeneous agroforestry, and lack of information. This research aimed to map the coffee coverage and identify land suitability for coffee plantations using remote sensing, Geographic Information Systems (GIS), and the Analytical Hierarchy Process (AHP) in the Gedeo zone, Southern Ethiopia. Remote sensing classifiers often confuse agroforestry and plantations like coffee cover with forest cover because of their similar spectral signatures. Mapping shaded coffee in Gedeo agroforestry using optical or multispectral remote sensing is challenging. To address this, the study identified and mapped coffee coverage from Sentinel-1 data with a decibel (dB) value matched to actual coffee coverage. The actual field data were overlaid on Sentinel-1, which was used to extract the raster value. Pre-processing, classification, standardization, and reclassification of thematic layers were performed to find potential areas for coffee plantation. Hierarchy levels of the main criteria were formed based on climatological, edaphological, physiographic, and socioeconomic factors. These criteria were divided into 14 sub-criteria, reclassified based on their impact on coffee growing, with their relative weights derived using AHP. From the total study area of 1356.2 km2, the mapped coffee coverage is 583 km2. The outcome of the final computed factor weight indicated that average annual temperature and mean annual rainfall are the primary factors, followed by annual mean maximum temperature, elevation, annual mean minimum temperature, soil pH, Land Use/Land Cover (LULC), soil texture, Cation Exchange Capacity (CEC), slope, Soil Organic Matter (SOM), aspect, distance to roads, and distance to water, respectively. The identified coffee plantation potential land suitability reveals unsuitable (413 km2), sub-suitable (596.1 km2), and suitable (347.1 km2) areas. This study provides comprehensive spatial details for Ethiopian cultivators, government officials, and agricultural extension specialists to select optimal coffee farming locations, enhancing food security and economic prosperity. [ABSTRACT FROM AUTHOR]

An accurate assessment of frost damage in coffee plantations can help develop effective agronomic practices to cope with extreme weather events. Remotely piloted aircrafts (RPA) have emerged as promising tools to evaluate the impacts caused by frost on coffee production. The objective was to evaluate the impact of frost on coffee plants, using vegetation indices, in plantations of different ages and areas of climatic risks. We evaluated two coffee plantations located in Brazil, aged one and two years on the date of frost occurrence. Multispectral images were collected by a remotely piloted aircraft, three days after the occurrence of frost in July 2021. The relationship between frost damage and these vegetation indices was estimated by Pearson's correlation using simple and multiple linear regression. The results showed that variations in frost damage were observed based on planting age and topography conditions. The use of PRA was efficient in evaluating frost damage in both young and adult plants, indicating its potential and application in different situations. The vegetation index MSR and MCARI2 indices were effective in assessing damage in one-year-old coffee plantations, whereas the SAVI, MCARI1, and MCARI2 indices were more suitable for visualizing frost damage in two-year-old coffee plantations. [ABSTRACT FROM AUTHOR]

Copyright of Umsatzsteuer-Rundschau is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Agriculture, which is spreading rapidly, is one of the major effectors on biodiversity - generally contributing to its decline. In the past few decades, most research efforts have focused on the impact of industrial agriculture on the environment and biodiversity. However, less attention has been paid on examining the impact of sustainable agricultural management practices on biodiversity. Challenges include the disruptive nature of some practices (e.g., agrochemical application) and the timing of others (e.g., tree pruning). Here, we highlight the value of passive acoustic monitoring in assessing the impact of agricultural management practices on biodiversity, using birds as indicators. We outline key considerations, including bird ecology and behavior, ARU sampling protocols, and data management. To demonstrate our approach, we present a case study from a coffee landscape in Costa Rica, where we analyzed the effects of pruning and pesticide application over two years. By focusing on selected focal species and using a subsample of the total hours recorded in combination with a mobile app for annotations, we found that pruning negatively impacted most species, while pesticide application adversely affected all species studied. Our methodology leverages technology to evaluate the impacts of agricultural management practices, offering insights to guide and assess sustainable agricultural strategies aimed at balancing biodiversity conservation with human well-being. [ABSTRACT FROM AUTHOR]

The sustainability of coffee production is a concern for producers around the world. To be sustainable, it is necessary to achieve satisfactory levels of coffee productivity and quality. Pests and diseases cause reduced productivity and can affect the quality of coffee beans. To ensure sustainability, producers need to monitor pests that can lead to substantial crop losses, such as the coffee leaf miner, Leucoptera coffeella (Lepidoptera: Lyonetiidae), which belongs to the Lepidoptera order and the Lyonetiidae family. This research aimed to use machine learning techniques and vegetation indices to remotely identify infestations of the coffee leaf miner in coffee-growing regions. Field assessments of coffee leaf miner infestation were conducted in September 2023. Aerial images were taken using remotely piloted aircraft to determine 13 vegetative indices with RGB (red, green, blue) images. The vegetation indices were calculated using ArcGis 10.8 software. A comprehensive database encompassing details of coffee leaf miner infestation, vegetation indices, and crop data. The dataset was divided into training and testing subsets. A set of four machine learning algorithms was utilized: Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD). Following hyperparameter tuning, the test subset was employed for model validation. Remarkably, both the SVM and SGD models demonstrated superior performance in estimating coffee leaf miner infestations, with kappa indices of 0.6 and 0.67, respectively. The combined use of vegetation indices and crop data increased the accuracy of coffee leaf miner detection. The RF model performed poorly, while the SVM and SGD models performed better. This situation highlights the challenges of tracking coffee leaf miner infestations in fields with varying ages of coffee plants, different cultivars, and other environmental variables. [ABSTRACT FROM AUTHOR]

Coffee cultivation facilitates foreign trade, which is important to the Mexican economy, particularly to the coffee growers of Jilotepec, Veracruz. However, in this region, the soil in which the coffee plants are grown is acidic and has low nutrient availability, making plants susceptible to pests and diseases. In this context, the use of mycorrhizal fungi has gained importance, due to the benefits that they provide in terms of the transport of nutrients and the development of plants, contributing to a reduction in the use of chemical fertilizers. This work aimed to determine the dominant Arbuscular mycorrhizal fungi (AMF) in the soil of coffee farms and evaluate the potential of sorghum as a trap plant for these organisms. As a result, ten morphotypes of AMF were detected in the coffee soil, with Glomus and Acaulospora being the dominant genera. It was found that their presence was related to the pH, clay, organic matter, and total carbon of the soil from the farms. The abundance of spores increased significantly (p < 0.05) between the initial count in the soil and the final count after propagation in the sorghum trap plants. The characteristic structures of mycorrhizal colonization and a high percentage of mycorrhizal colonization of the roots of the trap plants (Sorghum vulgare) were observed at 120 days after sowing. It is concluded that Glomus sp1, Glomus sp2, Glomus sp3, Glomus sp4, Rhizophagus clarus, and Acaulospora scrobiculata are the dominant morphotypes in the considered coffee plantation soils and that sorghum has high potential for favoring the propagation of native AMF through increasing their abundance and favoring high mycorrhizal colonization. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Development Studies is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Research on the food sources used by bees in agricultural landscapes is crucial to promote pollinator conservation measures in and around cultivated areas. This investigation aims to identify and quantify the pollen resources exploited by Schwarziana quadripunctata (Lepeletier 1836), assessing the trophic niche of this bee in agricultural areas with coffee plantations. Pollen analysis was conducted based on the pollen load of the corbiculae of 70 bees, sampled during the flowering period of two species of coffee trees in commercial plantations located in Rio de Janeiro, Minas Gerais and Espírito Santo states, Brazil, in 2019 and 2021. A total of 78 pollen types from 23 botanical families were identified, with Coffea arabica and Coffea canephora comprising 92% of the samples. Cestrum sp. (2.3% – Solanaceae), Fabaceae sp. 1 (0.9%), Solanum sp. (0.75% – Solanaceae) and Chamaecrista sp. (0.71% – Fabaceae) were the next most prevalent. The dominance of the coffee tree pollen confirms the floral constancy of S. quadripunctata during periods of intense flowering. Excluding coffee pollen, the most represented families were Solanaceae (46.6% of the samples), Fabaceae (27.5%), Rubiaceae (8.51%), and Meliaceae (2.53%). The findings reveal that S. quadripunctata actively forages from sources other than coffee, even during the intense flowering of these plants, highlighting the importance of floral resources in the proximity of plantations. The use of pollen sources beyond the coffee tree highlights the importance of conserving nearby forest fragments and maintaining a diverse array of plants surrounding coffee trees even during coffee flowering. [ABSTRACT FROM AUTHOR]

Ochratoxin A (OTA) is a mycotoxin mainly produced by Aspergillus section Circumdati and section Nigri across the coffee chain. OTA is nephrotoxic and is a threat to human health. This review summarizes current knowledge on how to reduce OTA concentration in coffee from farm to cup. After a brief introduction to the OTA occurrence in coffee, current good management practices are introduced. The core of this review focuses on biocontrol and microbial decontamination by lactic acid bacteria, yeasts and fungi, and their associated enzymes currently reported in the literature. Special attention is given to publications closest to in vivo applications of biocontrol agents and microbial OTA adsorption or degradation agents. Finally, this review provides an opinion on which future techniques to promote within the coffee supply chain. [ABSTRACT FROM AUTHOR]

The objective of this paper is to mainstream gender in agroecology, using VIDA's coffee systems as a case study. Data were collected through a mixed, participatory approach, combining qualitative (participant observation, interviews, workshops) and quantitative methods (a census of 24 men and 26 women). Results reveal gender differences across environmental, economic, social, and political dimensions. Women prioritize plant diversity, while men focus on coffee varieties and farm conditions. Both sexes emphasize economic and social sustainability, with women advocating for greater access to resources and benefits. VIDA has a gender-parity leadership promoting territorial defense and youth visibility to mitigate outmigration. [ABSTRACT FROM AUTHOR]

The coffee industry holds importance, providing livelihoods for millions of farmers globally and playing a vital role in the economies of coffee-producing countries. Environmental conditions such as drought and temperature fluctuations can adversely affect the quality and yield of coffee crops.Carotenoid cleavage oxygenases (CCO) enzymes are essential for coffee plants as they help break down carotenoids contributing to growth and stress resistance. However, knowledge about the CCO gene family in Coffee arabica was limited. In this study identified 21 CCO genes in Coffee arabica (C. arabica) revealing two subfamilies carotenoid cleavage dioxygenases (CCDs) and 9-cis-epoxy carotenoid dioxygenases (NCED) through phylogenic analysis. These subfamilies exhibited distribution patterns in terms of gene structure, domains, and motifs. The 21 CaCCO genes, comprising 5 NCED and 16 CCD genes were found across chromosomes. Promoter sequencing analysis revealed cis-elements that likely interact with plant stress-responsive, growth-related, and phytohormones, like auxin and abscisic acid. A comprehensive genome-wide comparison, between C. arabica and A. thaliana was conducted to understand the characteristics of CCO genes. RTqPCR data indicated that CaNCED5, CaNCED6, CaNCED12, and CaNCED20 are target genes involved in the growth of drought coffee plants leading to increased crop yield, in a conditions, with limited water availability. This reveals the role of coffee CCOs in responding to abiotic stress and identifies potential genes useful for breeding stress-resistant coffee varieties. [ABSTRACT FROM AUTHOR]

The agricultural sector of Colombia supports the national economy and food security due to the rich lands for cultivation. Although Colombia has a vast hydrological basin, climate change can impact agricultural productivity, generating economic and social adverse effects. For this, we evaluated the impact of some environmental variables on the production of the most sold crops using production, climatic, and hydrological data of the 1121 municipalities from 2007 to 2020. We modeled the production of coffee, rice, palm oil, sugarcane, and corn, adopting a Bayesian spatio-temporal model that involved a set of environmental variables: average temperature, minimum temperature, maximum temperature, evapotranspiration, precipitation, runoff, soil moisture, vapor pressure, radiation, and wind speed. We found that increases in the average temperatures can affect coffee (-0.2% per °C), rice (-3.76% per °C), and sugarcane (-0.19% per °C) production, meanwhile, these increases can boost palm oil (+2.55% per °C) and corn (+1.28% per °C) production in Colombia. This statement implies that the agricultural sector needs to substitute land use, promoting the production of palm oil and corn. Although our results did not find a significant effect of hydrological variables in any crop, suggesting that the abundance of water in Colombia might balance the impact of these variables. The increases in vapor pressure impact all the crops negatively (between -11.2% to -0.43% per kPa), except rice, evidencing that dry air conditions affect agricultural production. Colombia must manage the production location of the traditional products and implement agro-industrial technologies to avoid the climate change impact on crops. [ABSTRACT FROM AUTHOR]

With a global footprint of 10 million hectares across 12.5 million farms, coffee is among the world's most traded commodities. The coffee industry has launched a variety of initiatives designed to reduce coffee's contribution to climate change and biodiversity loss and enhance the socio-economic conditions of coffee producers. We systematically reviewed the literature on the sustainability and governance of coffee production and developed a typology of eleven sustainability initiatives. Our review shows that coffee sustainability research has focused primarily on the economic outcomes of certification schemes. The typology expands our knowledge of novel sustainability initiatives being led by coffee farming communities themselves, allowing for an improved consideration of power dynamics in sustainability governance. Sustainability initiatives governed by local actors can improve sustainability outcomes by empowering local decision makers to assess direct risks and benefits of sustainable practices to the local environment, economy, and culture. [ABSTRACT FROM AUTHOR]

Increasing temperatures and shifting precipitation patterns have major consequences for smallholder farmers, especially in the Global South. Our study examined spatial patterns and climatic drivers of farmers' perceptions of climate change, and how these perceptions translated into adaptation actions. We interviewed 56 farmers in southwestern Ethiopia and analyzed ERA5-Land reanalysis climate data from 1971 to 2020. The majority of farmers perceived the recorded temperature increase as well as a decrease and shift in the timing of rainfall. Perceived climate change varied with local climate factors and not with the rate of climate change itself. Farmers' adaptation practices showed associations with local temperature, but not with farmers' perceptions of climate change. Our findings highlight that even if farmers perceive climate change, perceptions are most common in areas where climate action is already urgent, and perceptions may not translate into adaptation. Thus, targeted and timely information and extension programs are crucial. [ABSTRACT FROM AUTHOR]

This study focuses on a nonlinear deterministic mathematical model for coffee berry borer (Hypothenemus hampei) with temperature and rainfall variability. In the model analysis, CBB free and coexistence equilibria are computed. The basic reproduction numbers at a minimum and maximum temperature and rainfall are derived. The qualitative analysis of the model revealed the scenario for equilibria together with basic reproduction numbers. The local stability of equilibria is established through the Jacobian matrix and the Routh–Hurwitz criteria, while the global stability of equilibria is demonstrated using an appropriate Lyapunov function. The normalized sensitivity analysis has also been performed to observe the impact of different parameters on basic reproduction numbers. The proposed model is extended into an optimal control problem by incorporating two control variables, namely, the preventive measure variable based on the separation of susceptible coffee berries from contacting the pests based on biological control and an increase in the death rate of colonizing females of CBB based on chemical control. Optimal disease control analysis is examined using Pontryagin's minimum principle. Finally, the numerical simulations are performed based on analytical results and are discussed quantitatively. Furthermore, the cost-effectiveness of control strategies to determine the best approach to minimize the CBB burden was studied. The study is significant in providing reliable information on how one can use mathematical modeling to improve the roles of control strategies and prevention in CBB transmission in a coffee farm. The outcome of the study may guide public agriculture policymakers on optimal control strategies to control the pests. In particular, using chemical pesticides is very effective to combat pests with minimum costs. [ABSTRACT FROM AUTHOR]

Regional development is one of the efforts to improve socioeconomic development, reduce regional disparities and preserve the environment. The Gross Regional Domestic Product (GRDP) of Banyumas Regency has increased over the past 5 years, with the largest contributor to the Gross Value Added category being the Agriculture and Forestry sector. Arabica coffee varieties are one of the mainstay commodities in the region and a source of income for the people of Kabupaten Banyumas. Arabica coffee is a plantation commodity that has been determined to be developed in Kabupaten Banyumas in accordance with the plantation commodity development plan in the RTRW Kabupaten Banyumas 2012-2032. The main objective of this research is to develop a strategy in planning the development of arabica coffee plantation area in Kabupaten Banyumas. The research area covers all 29 subdistricts starting from January to April 2024. In looking at the actual distribution of arabica coffee plantations, overlay analysis techniques were used using data from land use maps, elevation maps. Land availability was analyzed through overlay and matching techniques with ArcGIS software and direct measurement. Arabica coffee agribusiness system was analyzed through R/C ratio descriptively. The development strategy of Arabica coffee plantation area in Banyumas Regency was conducted using AWOT analysis. The results showed that the actual distribution of arabica coffee plantations in the cultivation area in Banyumas Regency covers several sub-districts and the area reaches 1,214 ha. Available and suitable land for the development of arabica coffee plantation in the cultivation area is indicated to reach an area of 20,471 ha, of which the largest area is located in Lumbir Sub-district with an area of 3,726 ha or 18.09% of the total available land area. [ABSTRACT FROM AUTHOR]

BACKGROUND: Coffee farming constitutes a substantial economic resource, representing a source of income for several countries due to the high consumption of coffee worldwide. Precise management of coffee crops involves collecting crop attributes (characteristics of the soil and the plant), mapping, and applying inputs according to the plants' needs. This differentiated management is precision coffee growing and it stands out for its increased yield and sustainability. RESULTS: This research aimed to predict yield in coffee plantations by applying machine learning methodologies to soil and plant attributes. The data were obtained in a field of 54.6 ha during two consecutive seasons, applying varied fertilization rates in accordance with the recommendations of soil attribute maps. Leaf analysis maps also were monitored with the aim of establishing a correlation between input parameters and yield prediction. The machine‐learning models obtained from these data predicted coffee yield efficiently. The best model demonstrated predictive fit results with a Pearson correlation of 0.86. Soil chemical attributes did not interfere with the prediction models, indicating that this analysis can be dispensed with when applying these models. CONCLUSION: These findings have important implications for optimizing coffee management and cultivation, providing valuable insights for producers and researchers interested in maximizing yield using precision agriculture. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Background: Climate influences the interaction between pathogens and their hosts significantly. This is particularly evident in the coffee industry, where fungal diseases like Cercospora coffeicola, causing brown‐eye spot, can reduce yields drastically. This study focuses on forecasting coffee brown‐eye spot using various models that incorporate agrometeorological data, allowing for predictions at least 1 week prior to the occurrence of disease. Data were gathered from eight locations across São Paulo and Minas Gerais, encompassing the South and Cerrado regions of Minas Gerais state. In the initial phase, various machine learning (ML) models and topologies were calibrated to forecast brown‐eye spot, identifying one with potential for advanced decision‐making. The top‐performing models were then employed in the next stage to forecast and spatially project the severity of brown‐eye spot across 2681 key Brazilian coffee‐producing municipalities. Meteorological data were sourced from NASA's Prediction of Worldwide Energy Resources platform, and the Penman–Monteith method was used to estimate reference evapotranspiration, leading to a Thornthwaite and Mather water‐balance calculation. Six ML models – K‐nearest neighbors (KNN), artificial neural network multilayer perceptron (MLP), support vector machine (SVM), random forests (RF), extreme gradient boosting (XGBoost), and gradient boosting regression (GradBOOSTING) – were employed, considering disease latency to time define input variables. Results: These models utilized climatic elements such as average air temperature, relative humidity, leaf wetness duration, rainfall, evapotranspiration, water deficit, and surplus. The XGBoost model proved most effective in high‐yielding conditions, demonstrating high precision and accuracy. Conversely, the SVM model excelled in low‐yielding scenarios. The incidence of brown‐eye spot varied noticeably between high‐ and low‐yield conditions, with significant regional differences observed. The accuracy of predicting brown‐eye spot severity in coffee plantations depended on the biennial production cycle. High‐yielding trees showed superior results with the XGBoost model (R2 = 0.77, root mean squared error, RMSE = 10.53), whereas the SVM model performed better under low‐yielding conditions (precision 0.76, RMSE = 12.82). Conclusion: The study's application of agrometeorological variables and ML models successfully predicted the incidence of brown‐eye spot in coffee plantations with a 7 day lead time, illustrating that they were valuable tools for managing this significant agricultural challenge. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Civet coffee is produced with coffee beans that have passed through the digestive tract of civets which are then processed for drinking. Outlets, known as civet coffee tourism plantations are popular tourist attractions in Bali, Indonesia. These outlets keep caged civets for public viewing and sell civet coffee. We assessed civet welfare in 29 civet coffee tourism plantations to assess husbandry factors, the five freedoms and body condition scores. We also assessed civet welfare in eight wildlife markets where civets are sourced for civet coffee tourism and calculated turnover of civets. We found 99 civets in civet coffee tourism plantations and 136 in markets, where. Annually between 400 and 800 civets are sold. Welfare standards do not meet the Indonesian laws and regulations. Diet, hygiene, presence of water and mobility affected body condition scores and no civet met all of the five freedoms. Enforcement of welfare and trade laws is needed to improve civet welfare, and to curb the illegal civet trade. Tourists frequenting civet coffee tourism plantations should be made aware of the low welfare standards to inform their choice about supporting this industry. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Adapting agriculture to climate change requires an understanding of the long‐term relationship between climate, disease dynamics, and yield. While some countries have monitored major crop diseases for decades or centuries, comparable data is scarce or non‐existent for many countries that are most vulnerable to climate change. For this, a novel approach was developed to reconstruct climate‐mediated changes in disease dynamics and yield. Here, a case study on Arabica coffee in its area of origin demonstrates how to combine local knowledge, climate data, and spatial field surveys to reconstruct disease and yield time series and to postulate and test hypotheses for climate–disease–yield relationships. Summary: While some countries have monitored crop diseases for several decades or centuries, other countries have very limited historical time series. In such areas, we lack data on long‐term patterns and drivers of disease dynamics, which is important for developing climate‐resilient disease management strategies.We adopted a novel approach, combining local knowledge, climate data, and spatial field surveys to understand long‐term climate‐mediated changes in disease dynamics in coffee agroforestry systems. For this, we worked with 58 smallholder farmers in southwestern Ethiopia, the area of origin of Arabica coffee.The majority of farmers perceived an increase in coffee leaf rust and a decrease in coffee berry disease, whereas perceptions of changes in coffee wilt disease and Armillaria root rot were highly variable among farmers. Climate data supported farmers' understanding of the climatic drivers (increased temperature, less rainy days) of these changes. Temporal disease‐climate relationships were matched by spatial disease‐climate relationships, as expected with space‐for‐time substitution.Understanding long‐term disease dynamics and yield is crucial to adapt disease management to climate change. Our study demonstrates how to combine local knowledge, climate data and spatial field surveys to reconstruct disease time series and postulate hypotheses for disease‐climate relationships in areas where few long‐term time series exist. [ABSTRACT FROM AUTHOR]

Coffee (Coffea arabica) cultivation is vital to the global economic, social and cultural life of farmers. However, senescent and disease-susceptible plantations affect coffee productivity. Therefore, it is crucial to improve biotechnological strategies such as micropropagation to increase the number of plants for replanting. In this study, the dark condition (T1) and different light qualities (T0-white light 400–700 nm; T2-red light 660 nm and T3-blue light 460 nm) were evaluated to optimize the in vitro propagation of 4 and 9 month-old coffee seeds. The results showed that red light had the highest percentage, an outstanding germination rate index, which may suggest that in the case of coffee seeds could be involved phytochromes that promote germination in a red light quality. In summary, the ideal conditions for in vitro micropropagation of coffee are under white and red light condition. [ABSTRACT FROM AUTHOR]

Geographical scholarship has advocated the importance of endogenous and place-sensitive development to levelling up left-behind places, by means of reactivating untapped potentials and recuperating a sense of belonging. Drawing on the approaches of global value chain (GVC), and to a lesser extent, global production network (GPN), this paper rethinks how GVC/GPN participation articulates with endogenous assets and enhances local actors' capacities to achieve economic and social upgrading. We present a case study of the coffee economy in Lujiang Township, Yunnan Province, China. We find that local villagers are able to tap into opportunities of learning and upgrading, but these processes are mediated by institutions and moral economies. Ultimately, economic empowerment translates into the revival of a sense of belonging. [ABSTRACT FROM AUTHOR]

Purpose: This study intends to investigate drivers and consequences of supply chain coordination (SCC) towards green to highlight some convincing evidence for an emerging country's exporters to promote sustainable coffee development. Design/methodology/approach: Data were gathered from surveying 189 managers of coffee exporters in Vietnam and then applied PLS-SEM for analysis. Findings: This study demonstrates that top management sensitivity, along with institutional forces of regulation, market and competition, strongly stimulate exporters' supply chain coordination towards green. Additionally, that coordination boosts the export financial and market performance. Research limitations/implications: The findings may not be generalizable because the current study only included data from Vietnamese coffee exporters. Originality/value: This study contributes to the current literature by looking from the perspective of coffee exporters – leading players in supply chains for export. The research findings represent the first solid argument for Vietnam coffee exporters to encourage SCC towards green and reveal several implications for managers and policymakers to support sustainable development in an emerging country. [ABSTRACT FROM AUTHOR]

The coffee industry in Indonesia, particularly in the Sumatran landscape, emerges as a vital contributor to the nation's economy, impacting regional growth. Nevertheless, this landscape faces ecological threats from rapid deforestation, resulting in a substantial loss of primary forest cover. This historical deforestation along with climate crisis presents challenges for coffee plantations. The study employs geospatial analysis to comprehensively outline challenges and opportunities for smallholder coffee farmers in Sumatra, particularly in the Arabica (Central Aceh) and Robusta (Tanggamus) landscapes. The study shows non-shade coffee plantations covered approximately 23,453 ha in Central Aceh and 43,991 ha in Tanggamus. Additionally, mixed agroforestry areas were prevalent, comprising about 132,569 ha in Tanggamus and 19,450 ha in Central Aceh. Tanggamus and Central Aceh have become favorable areas for Robusta coffee and Arabica coffee, respectively. One significant opportunity identified for coffee development in Central Aceh is that 86% of existing coffee farms already adhere to EUDR. Furthermore, 94% of existing coffee farms in Tanggamus meet EUDR standards, opening doors for more farmers to access the European market. [ABSTRACT FROM AUTHOR]

Impact of rainfall and slopes on soil organic carbon (SOC) dynamics was assessed under tea and coffee plantations, land covers, in Western Ghats Mountain (WGM). Severe water erosion in the western side of WGM by heavy rainfall and land sloppiness recorded less SOC (3.07%) compared to the eastern side (4.03%) in tea plantations. Similar trend in SOC was observed in coffee plantations, with 1.98% in western side and 3.25% in eastern side. Loss of soil organic carbon stock under tea plantations in western sides was 0.346 million tonnes and in coffee plantations it was 0.190 million tonnes. Hence, the total organic carbon loss was 0.536 million tonnes. Highest SOC content and stocks were recorded in steep slopes in tea and coffee plantations due to dense biomass cover and adoption of soil and water conservation measures. [ABSTRACT FROM AUTHOR]

The application of pesticides using unmanned aerial vehicles (UAVs) has grown, but there is a lack of information to support more efficient applications. Using a DJI AGRAS-MG-1P octocopter equipped with different spray tips, this study sought to explore spray deposition (leaves and fruit) and efficacy of chlorpyrifos on control of coffee berry borer at different spray volumes and flight heights. The study was conducted in an Arabica coffee plantation. The study consisted of eight treatments and four replications in a 2 × 2 × 2 factorial scheme: two flight heights (1.5 and 3.0 m), two spray tips (hollow cone and flat fan), and two spray volumes (10 and 15 L ha−1). Deposition was assessed by detecting a tracer in the coffee leaves and fruit using spectrophotometry. The coffee berry borer-control efficacy trial was conducted in two areas by evaluating the percentage of damaged fruit 60 days after two insecticide applications. The flight height of 1.5 m promoted higher spray deposition on leaves and fruit and a lower incidence of damaged fruit. Flat fan spray tips resulted in higher spray deposition on the leaves, not interfering with the deposition on fruit or the coffee berry borer control. Increasing the spray volume from 10 to 15 L ha−1 did not increase spray deposition on coffee leaves and fruit. Chlorpyrifos applied via UAVs reduced the incidence of coffee berry borer. [ABSTRACT FROM AUTHOR]

Coffee stands as a vital pillar of Colombia's economic prosperity, constituting approximately 7% of the nation's agricultural GDP. Moreover, it serves as a significant contributor to national agricultural employment, with direct jobs stemming from coffee cultivation comprising 26% of the total agricultural workforce. This underscores the pivotal role coffee plays in shaping Colombia's social and economic landscape, solidifying its position as the primary origin of mildly washed coffees for global consumers. However, Colombia's coffee production grapples with the challenge of operating amidst persistently rainy conditions, fostering an environment conducive to fungal diseases. This, compounded by environmental, economic, commercial, and safety constraints for disease control, creates a multifaceted scenario that continuously tests disease management strategies. Addressing this complex dynamic demands a crop protection framework that seamlessly integrates efficient and sustainable methodologies. Such methodologies should prioritize outbreak prevention, cost-effectiveness, adherence to national and international regulations, and the preservation of environmental and human health. Integrated disease management emerges as a solution capable of optimizing productivity tailored to the unique conditions of each plot. By mitigating the impact of pathogens while responsibly utilizing and conserving natural resources, this approach safeguards the well-being of both producers and consumers alike. [ABSTRACT FROM AUTHOR]

The root-knot nematode Meloidogyne paranaensis is one of the main problems for coffee production in Latin American countries. In Mexico, this nematode is found damaging shaded coffee plantations, with a wide variety of associated vegetation. The plant species present in these agroecosystems could serve as nematode alternative hosts, helping to maintain and disperse the population of M. paranaensis even when control measures are carried out for coffee trees. The aim of this work was to evaluate the ability of M. paranaensis to reproduce in 13 plant species commonly associated with shade-grown coffee plantations. The plants were inoculated with eggs and J2 of M. paranaensis, 10 months later, the host susceptibility index and the resistance level were calculated based on the nematode population density. Meloidogyne paranaensis reproduced in 11 of the evaluated plants which presented different resistance levels. Citrus aurantium, Citrus reticulata, Inga jinicuil, Inga vera and Musa AA, were highly susceptible compared to Coffea arabica and Coffea canephora. On the other hand, Macadamia integrifolia and Psidium guajava are considered resistant to moderately resistant with a reproduction rate less than one and a susceptibility index less than 10 with respect to C. arabica and less than 25 with respect to C. canephora. Persea schiedeana and Syzygium jambos did not allow M. paranaensis reproduction, so they are considered highly resistant. The results of this study provide important information for the M. paranaensis management in infested shade-grown coffee plantations. It is necessary to evaluate other woody and herbaceous plant species to improve control measures for this nematode. [ABSTRACT FROM AUTHOR]

Coffee is the foundation of Ethiopia’s economy with a quarter of the population dependent on coffee production and exports for livelihood. However, most empirical research in coffee production focuses on the productivity factors like yields rather than socio-economic factors that can significantly influence the level of coffee production. Thus, this essay explores the determinants of smallholders’ coffee production in Wolaita zone, Ethiopia by applying the ordered logistic regression model. This model estimates the coffee production status of smallholders by combining the effect of multiple productivity related biophysical and socio-economic factors. Using a multistage sample procedure, two farmers associations from each district were chosen for the research. Overall sample sizes of 250 households were interviewed door-to-door to generate quantitative data. Data was analyzed by using SPSS software and descriptive statistical techniques were applied in order to determine the coffee production status of the farm households. The results indicated that about 88.8% of the smallholder farm households fell under the yield category of ‘low producer’, which is an indicator that numerous variables provide challenges to the smallholder coffee production in the studied area. The results of the regression study showed that of the eighteen variables in the model, seven variables including irrigation access, pruning practice, household farm land size, training access, pesticide utilization, manure application, and cultivated land allocation were discovered to be the important predictors of farm families' coffee production status in the research region. It can be recommended that establishment of government sponsored irrigation systems, empowerment on utilization of appropriate coffee farm technologies and inputs for the areas, enhancing extension services to improve farmers’ skill and knowledge on coffee production system and risk alleviating mechanisms, developing soil fertility mechanisms, establishment of farmers training centers in the vicinities of producers, building capacity of institutions are vital to motivate coffee producers and increase productivity and coffee output in the research area and areas with similar situations. [ABSTRACT FROM AUTHOR]

Epidemiological cohort studies are a central research design in public health which appeal to, and can reinforce, specific ideas of the nation, sociality and the 'good' citizen. The concept of publics, the sociology of expectations and a co-productionist framework provide the theoretical frame to investigate how popular representations of two cohort studies, German National Cohort and UK Biobank, attempt to enrol a concerned public. By constructing promissory publics, cohort studies produce morally charged visions of health research and civic engagement as normative social practices. Promissory publics straddle the population and the citizen, the nation and the region, the future and the past, thus adding nuance to existing conceptual approaches. The publics of cohort studies are bolstered by the care practices of predominantly female staff, functioning as a performance of social recognition in lieu of an immediate beneficiary of research participation. Through these processes, popular representations of cohort studies intervene into much broacher visions of society and its anticipated futures, co-producing socially dominant and morally charged projections of sociality as well as health. The production of such publics thereby draws boundaries between members of the public and those practices enacted as endangering civic values. As such, cohort studies may have much broader socio-cultural ramifications that could reinforce old or reintroduce new lines of inclusion or exclusion. [ABSTRACT FROM AUTHOR]

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

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

Soils provide essential ecosystem services for the existence of ecosystems and biodiversity. It is crucial to understand their quality through the evaluation of ecological processes. However, only some studies estimate the effectiveness of ecosystem restoration based on evaluating soil quality (SQ) indicators. This research evaluated the five most common land-use scenarios in Andean ecosystems within the Natural Reserve of the Civil Society (RNSC) "La Montaña Mágica" under natural forest, coffee plantation, badlands, and active and passive restoration. The main objective was to analyze the physical, chemical, and biological characteristics concerning land use, establish the baseline for SQ indicators in different land use activities, and determine the status of restoration systems for other land uses in the study site. ANOVA and Dunnett's test evaluated SQ parameters. In passive and active restoration, soil bulk density, porosity, and the number of individuals and families of macroinvertebrates were improved. The latter presented low pH and aluminum values but increased potassium compared to other soil uses. The restoration strategies favored changes in SQ indicators due to the contribution of organic carbon, a developed root system, and the recirculation of nutrients in the edaphic system. This study provided information on changes in SQ with soil usage as a practical tool to evaluate ecological restoration methods in natural areas of the eastern Colombian Andes. [ABSTRACT FROM AUTHOR]

As a significant crop growing all across the world, coffee is mostly produced in the bean belt of our global atlas. Worldwide variations in environmental conditions are causing a decline in the yield and quality of coffee varieties. Coffee production is the main emphasis of several traditional breeding techniques. But conventional breeding methods are not sufficient to tackle the problems related to coffee. The field of genomics, which includes transcriptomics, proteomics, and metabolomics, has made great paces in the last ten years. Proteomics is a well-known technique used to enhance the growth, yield, breeding, and quality of different plants under stable and shifting environments. The regulation of specific enzymes, genes, protein expression, modification, translation, and other features played an important role in the enhancement of important plants. However, relatively less research on the proteomics approach for coffee has been published in the last few years. For this reason, some of the most important aspects of proteome profiling for coffee plants have been covered in this review, including growth, the somatic embryo technique, altitude, environmental adoption, drought, and the role that proteins and important enzymes play in the flavor and taste of coffee. This review can aid in the breeding of new cultivars and improve coffee attributes. Furthermore, the present literature can pave the way for proteomics research on coffee. [ABSTRACT FROM AUTHOR]

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Background: The coffee industry is one of the most important world supply chains, with an estimated consumption of two billion cups daily, making it the most consumed beverage worldwide. Coffee beans are primarily grown in tropical countries, with Brazil accounting for almost 50% of the production. The objective of this study is to examine the Brazilian trade between 2018 and 2022, focusing on state producers, logistical corridors, and importer countries. Methods: The methodology approach revolves around a quantitative method using Social Network Analysis measures. Results: The results reveal a massive concentration in local production (99.5%—Minas Gerais), port movements (99.9%—Santos, Itaguai, and Rio de Janeiro), and country buyers (80.9%—the United States, United Kingdon, and Japan). Conclusions: The study concludes that the Brazilian green coffee supply chain relies on a fragile and overloaded logistical network. Due to that, this study indicates that the stakeholders and decision-makers involved must consider this high concentration of production in some areas and companies. They must also address the bottlenecks in logistical corridors and the fierce competition involved in acquiring and processing Brazilian coffee production because these factors can drastically affect the revenue of the companies operating in this sector. [ABSTRACT FROM AUTHOR]

This paper explores the dynamics of mild coffee trade during the term of the International Coffee Agreement, focusing on Costa Rica as a case study. We aimed to verify the influence of the agreement on coffee exports and understand its impact on the exports of high-quality coffee. To compare the influence of the coffee agreement on the trade performance of high-quality coffee producers with that of producers specializing in coffee of similar – or lower – quality, we also included exports of Brazilian coffee (low quality) and Colombian coffee (high quality) in the sample. We focused on analysing commodity trade agreements in the second half of the twentieth century and, simultaneously, on the drivers of coffee exports based on a gravity equation consistent with international trade models. Our findings allowed us to conclude that the International Coffee Agreement gave rise to few benefits for 'Other Milds' countries such as Costa Rica and greater benefits for 'Colombian Milds' countries such as Colombia, at least in its early versions. [ABSTRACT FROM AUTHOR]

In Colombia, coffee futures contracts represent essential financial agreements that allow producers and buyers to establish prices, quality, and conditions for future transactions in the coffee market. Despite the evident benefits of stability and predictability, this practice faces significant sustainability challenges that threaten its long-term viability. One of the reasons is the significant lack of transparency in the supply chain. Farmers, affected by abrupt price fluctuations and adverse weather conditions such as the El Niño phenomenon, experience an increase in market prices, leading to the non-delivery of the final product, and contract breaches as they find better prices in the local market. In this context, smart contracts emerge as a promising technological solution to address these problems. These contracts enable the verification of each step in the process, from harvest to final sale, within a blockchain. Therefore, this research designs a smart contract managed through a platform called SmartBeanFutures, which records the clauses of futures contracts using the IERC721 framework, allowing the generation of a unique and non-repeatable asset. It aims to sell, promote, and manage coffee sale prices during the agreement's signing, creating a transparent environment for chain actors. This proposal undergoes evaluation in a test environment, providing farmers access to the designed platform. Following the validation of the proposal, it was identified that over 74% would use this type of contract in their agricultural processes, highlighting that implementing this technology contributes to eliminating intermediaries in the chain and gives farmers more control over their participation in the market. [ABSTRACT FROM AUTHOR]

In this case study, the current situation faced by coffee growers attempting to control coffee leaf rust (Hemileia vastatrix) in Hawaii is reported. CLR is considered the most devastating disease affecting coffee crops worldwide and was detected in Hawaii in 2020. Three small coffee farms from the South Kona district of Hawaii Island were selected. The goals of this case study were to: (1) assist coffee growers in the early detection of CLR incidence, and consequently support farmers with recommendations for control, (2) record agronomic information and management practices, and (3) estimate the cost to control CLR during 2021 and 2022 seasons. Low CLR incidence (<4%) was initially observed at all farms (January–June 2021), but increased as the harvest began, ending the season (December 2021) at 77%, 21% and 6% incidence at farms 1, 2 and 3, respectively. At the end of 2022 season (December), CLR incidence reached 43%, 20% and 3% at farms 1, 2 and 3, respectively. The number of sprays per season (5–10), the type of fungicides applied (preventive, curative), the timing of sprays, the efficacy of applications and weather conditions all played a role in determining the infection rates at each farm. Effective control of CLR is possible in Hawaii if the sprays of fungicides are carried out with the right products, appropriate timing and good coverage. [ABSTRACT FROM AUTHOR]

This paper presents a novel decomposition approach for measuring deterrence motives in dynamic oligopoly games. Our approach yields a formalized, scale-free, and interpretable measure of deterrence motives that informs researchers about the proportion for which deterrence motives account of all entry motives. In addition, the decomposition leads to a set of conditions for counterfactual analysis where hypothetical scenarios with deterrence motives eliminated can be explored. We illustrate the use of our measure and counterfactual by conducting an empirical case study about the dynamics of coffee chain stores in Toronto, Canada. The inferred deterrence motives suggest that a noticeable proportion of entry motives can be attributed to deterrence; it can be as high as 43% for the increasingly dominant coffee chain, Starbucks, in certain types of markets. Finally, counterfactual analysis confirms that deterrence motives are indeed associated with Starbucks' aggressive presence as the number of its outlets and its market share are markedly lower once these motives are eliminated. This paper was accepted by Matthew Shum, marketing. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4864. [ABSTRACT FROM AUTHOR]

Organic carbon performs essential functions in soils, which act as sources or sinks of atmospheric organic carbon. Agricultural management affects the carbon cycle in the soil, with effects on climate change. One of the crops most vulnerable to climate change is coffee. Brazil is the world’s largest coffee producer, with a predominance of management under a conventional system, with sloping terrain and the absence of conservationist practices. The absence of conservationist practices increases in soil loss rates due to water management and carbon emissions, as well as a reduction in coffee production. This paper intended to estimate soil and organic carbon losses by RUSLE in coffee farms in southern Minas Gerais, south-eastern Brazil. Data were obtained from fieldwork, laboratory analysis, and cartographic products. The results indicated, exclusively for coffee crops, soil and carbon losses between 7 and 32 Mg ha−1 year−1 and 87 and 460kg ha−1 year−1, respectively. However, the highest soil losses occurred on sloping terrains with eucalyptus plantations located downhill, and the lowest losses occurred on flat land with native forests. Organic carbon losses were linked directly to soil losses, as a result from the land practices, slope and agricultural management adopted. These results can be used for the planning and priority definition of areas needing conservationist practices, such as green manuring, planting in contour and maintaining of vegetation between coffee rows, which are already used in some sites of the study area. [ABSTRACT FROM AUTHOR]