Specialty coffee beans are those produced, processed, and characterized following the highest quality standards, toward delivering a superior final product. Environmental, climatic, genetic, and processing factors greatly influence the green beans' chemical profile, which reflects on the quality and pricing. The present study focuses on the assessment of eight major health-beneficial bioactive compounds in green coffee beans aiming to underscore the influence of the geographical origin and post-harvesting processing on the quality of the final beverage. For that, we examined the non-volatile chemical profile of specialty Coffea arabica beans from Minas Gerais state, Brazil. It included samples from Cerrado (Savannah), and Matas de Minas and Sul de Minas (Atlantic Forest) regions, produced by two post-harvesting processing practices. Trigonelline, theobromine, theophylline, chlorogenic acid derivatives, caffeine, caffeic acid, ferulic acid, and p-coumaric acid were quantified in the green beans by high-performance liquid chromatography with diode array detection. Additionally, all samples were roasted and subjected to sensory analysis for coffee grading. Principal component analysis suggested that Cerrado samples tended to set apart from the other geographical locations. Those samples also exhibited higher levels of trigonelline as confirmed by two-way ANOVA analysis. Samples subjected to de-pulping processing showed improved chemical composition and sensory score. Those pulped coffees displayed 5.8% more chlorogenic acid derivatives, with an enhancement of 1.5% in the sensory score compared to unprocessed counterparts. Multivariate logistic regression analysis pointed out altitude, ferulic acid, p-coumaric acid, sweetness, and acidity as predictors distinguishing specialty coffee beans obtained by the two post-harvest processing. These findings demonstrate the influence of regional growth conditions and post-harvest treatments on the chemical and sensory quality of coffee. In summary, the present study underscores the value of integrating target metabolite analysis with statistical tools to augment the characterization of specialty coffee beans, offering novel insights for quality assessment with a focus on their bioactive compounds.

The Cantareira System is one of the largest water supply systems in the world, supplying about half of the water consumed by 22 million inhabitants in the Metropolitan Region of São Paulo, in southeastern Brazil. In this scenario, in view of climate change, silting is a serious environmental threat and a major challenge to the sustainability of water reservoirs. Therefore, identifying the provenance of sediments is an essential tool to support soil conservation policies, slowing erosion processes and mitigating the deposition of sediments in water reservoirs. Thus, this study aimed to model soil losses—sediment production, by water erosion in the Cantareira System, based on the RUSLE model—Revised Universal Soil Loss Equation, GIS—Geographic Information System and SR—Remote Sensing. The work was conducted on data obtained from online platforms of Brazilian public institutions. The results indicate an average rate of soil loss of 13 Mg ha⁻¹ yr⁻¹, which corresponds to an annual loss of 3 million tons, of which 22% reaches water bodies. The data also show that: (1) in 66 % of the Cantareira System, soil losses are below the soil loss tolerance limits, and, in 34% of the region, water erosion is compromising the sustainability of water and soil resources; (2) the areas with the greatest soil losses are predominantly located in planted forests, agricultural crops and non-vegetated areas; and (3) sectors with high rates of soil loss require the adoption of conservationist practices aimed at reducing sediment production rates and thereby increasing supply and improving water quality.

Water erosion is one of the most important soil degradation processes and it can be intensified by land use and vegetal covering changes. Thus, water erosion modeling studies associated to multi temporal analyses of land use are effective in assessing how changes in land cover affects sediment yield. Therefore, considering the modifications in the land use from 1986 to 2011, the aim of this study ranged to estimate water erosion rates and compare them to the soil loss tolerance (SLT) limit in the Latosols (Oxisols) at Ribeirão Caçús sub-basin, in the South of Minas Gerais State, Southeast Brazil, by means of the Revised Universal Soil Loss Equation (RUSLE) in association with the geographic information system (GIS), and geostatistical techniques. So, for each year mapped, soil loss averages were compared by t test at 5% significance to assess the soil degradation stage. The results indicated that, in the period, the soil loss average rate was from 2.4 to 2.6 Mg ha^-1 year^-1 and the areas with soil loss above the limit of SLT were around 8.0%. The t test demonstrated there was no considerable difference among the soil loss averages (p = 0.18). In consequence, the area of degraded soils did not increase. Thus, the RUSLE model in GIS is a simple and useful tool to estimate the soil loss and help define soil conservation and recovery measures.

Soil losses due to water erosion threaten the sustainability of agriculture and the food security of current and future generations. This study estimated potential soil losses and sediment production under different types of land uses in a subbasin in the Municipality of Alfenas, southern Minas Gerais, southeastern Brazil. The objective of this research was to evaluate the application of the Potential Erosion Method by the Intensity of Erosion and Drainage program and correlate the findings with the results obtained by the Revised Universal Soil Loss Equation as well as geoprocessing techniques and statistical analyses. In the Potential Erosion Method, the coefficient indicating the mean erosion intensity was 0.37, which corresponded to erosion category IV and indicated weak laminar erosion processes, and the total soil loss was 649.31 Mg year-1 and the mean was 1.46 Mg ha-1 year-1. These results were consistent in magnitude with those obtained in the Revised Universal Soil Loss Equation, which estimated a mean soil loss of 1.52 Mg ha-1 year-1 and a total soil loss of 668.26 Mg year-1. The Potential Erosion Method suggests that 1.5% of the area presents potential soil losses above the soil loss tolerance limit, which ranged from 5.19 to 5.90 Mg ha-1 year-1, while the Revised Universal Soil Loss Equation indicated that 7.3% of the area has potential soil losses above the limit. The maximum sediment discharge was 60 Mg year-1, meaning that 9.3% of the total soil loss reached the depositional areas of the river plains or watercourses. The Potential Erosion Method was efficient in the evaluation of water erosion in tropical soils, and the results were consistent with models widely employed in the estimation of soil losses. Thus, the model can support the evaluation of soil losses in Brazil and is a robust tool for evaluating the sustainability of agricultural activities.

Water erosion is one of the main problems faced in coffee cultivation, as it promotes environmental degradation and crop yield decrease. Erosion estimates support the planning of conservation management practices and allowing determining the rates of soil losses. Thus, the objective of this paper was to estimate the soil loss by water erosion using the Erosion Potential Method in a sub-basin predominantly covered by coffee cultivation and then to compare the results with the Soil Loss Tolerance limits. The study area is the Coroado Stream Sub-basin, located at Alfenas Municipality, south of Minas Gerais, Brazil. The sub-basin presented an Erosion Coefficient of 0.272, indicating a predominance of low-intensity erosion. The total soil loss estimate was 1,772.01 Mg year^-1 with an estimated average of 1.74 Mg ha^-1 year^-1. Soil Loss Tolerance limits range from 4.75 to 7.26 Mg ha^-1 year^-1 and, according to the Erosion Potential Method, only 1.0% of the sub-basin presented losses above the limits. The areas with the highest slopes and bare soil concentrated the highest losses rates and should be prioritized in the adoption of mitigation measures. The Erosion Potential Method estimated soil losses in tropical edaphoclimatic conditions in a fast, efficiently and at low cost, supporting the adoption of conservation management practices.

Water erosion is one of the main environmental impacts of land use. When soil and water losses occur, nutrients essential for the growth and maintenance of plants are removed, with harmful outcomes on the sustainability of agriculture and the environment. In addition, they lead to other deleterious effects, such as sedimentation and eutrophication of water bodies. Estimation of soil losses due to water erosion in sub-basins is essential for prediction of soil degradation, especially in areas of semi-intensive cultivation, such as coffee fields. Thus, the aim of this study was to estimate soil losses in relation to the limit of soil loss tolerance in Oxisols (Latossolos Vermelhos Distróficos) under coffee cultivation. This study was conducted from March 2015 to January 2017 in the Córrego da Laje Hydrographic Sub-basin in the municipality of Alfenas in the southern region of Minas Gerais, southeastern Brazil. Soil losses due to water erosion were estimated from the revised universal soil loss equation and compared to soil loss tolerance. Morphological, physical, and chemical properties of the soil were used, as well as geoprocessing techniques, remote-sensing images, and data from the literature. The results show potential soil losses from 0.01 to 18.77 Mg ha^-1 yr^-1, with an average of 1.52 Mg ha^-1 yr^-1. The soil loss tolerance ranged from 5.19 to 5.90 Mg ha^-1 yr^-1, with 7.35 % of the area having larger losses. Areas with steeper slopes and no sustainable practices have soil losses above the tolerance level and are thus a priority for adoption of measures to mitigate erosive effects. The revised universal soil loss equation enabled water erosion modeling and identification of areas with the highest rates of potential soil loss in watersheds.