One of primary issues in the coffee manufacturing industry is the production of large amounts of undesirable residues, which include the pericarp (outer skin), pulp (outer mesocarp), parchment (endocarp), silver-skin (epidermis) and mucilage (inner mesocarp) that cause environmental problems due to toxic molecules contained therein. This study evaluated the optimal hydrogen production from coffee mucilage combined with organic wastes (wholesale market garbage) in a dark fermentation process. The supplementation of organic wastes offered appropriate carbon and nitrogen sources with further nutrients; it was positively effective in achieving cumulative hydrogen production. Three different ratios of coffee mucilage and organic wastes (8:2, 5:5, and 2:8) were tested in 30 L bioreactors using two-level factorial design experiments. The highest cumulative hydrogen volume of 25.9 L was gained for an 8:2 ratio (coffee mucilage: organic wastes) after 72 h, which corresponded to 1.295 L hydrogen/L substrates (0.248 mol hydrogen/mol hexose). Biochemical identification of microorganisms found that seven microorganisms were involved in the hydrogen metabolism. Further studies of anaerobic fermentative digestion with each isolated pure bacterium under similar experimental conditions reached a lower final hydrogen yield (up to 9.3 L) than the result from the non-isolated sample (25.9 L). Interestingly, however, co-cultivation of two identified microorganisms (Kocuria kristinae and Brevibacillus laterosporus), who were relatively highly associated with hydrogen production, gave a higher yield (14.7 L) than single bacterium inoculum but lower than that of the non-isolated tests. This work confirms that the re-utilization of coffee mucilage combined with organic wastes is practical for hydrogen fermentation in anaerobic conditions, and it would be influenced by the bacterial consortium involved.

No abstract

This study presents the analysis and estimation of the hydrogen production from coffee mucilage mixed with organic wastes by dark anaerobic fermentation in a co-digestion system using an artificial neural network and fuzzy logic model. Different ratios of organic wastes (vegetal and fruit garbage) were added and combined with coffee mucilage, which led to an increase of the total hydrogen yield by providing proper sources of carbon, nitrogen, mineral, and other nutrients. A two-level factorial experiment was designed and conducted with independent variables of mucilage/organic wastes ratio, chemical oxygen demand (COD), acidification time, pH, and temperature in a 20-L bioreactor in order to demonstrate the predictive capability of two analytical modeling approaches. An artificial neural network configuration of three layers with 5-10-1 neurons was developed. The trapezoidal fuzzy functions and an inference system in the IF-THEN format were applied for the fuzzy logic model. The quality fit between experimental hydrogen productions and analytical predictions exhibited a predictive performance on the accumulative hydrogen yield with the correlation coefficient (R2) for the artificial neural network (> 0.7866) and fuzzy logic model (> 0.8485), respectively. Further tests of anaerobic dark fermentation with predefined factors at given experimental conditions showed that fuzzy logic model predictions had a higher quality of fit (R2 > 0.9508) than those from the artificial neural network model (R2 > 0.8369). The findings of this study confirm that coffee mucilage is a potential resource as the renewable energy carrier, and the fuzzy-logic-based model is able to predict hydrogen production with a satisfactory correlation coefficient, which is more sensitive than the predictive capacity of the artificial neural network model.

The harvest is one of the most important activities in coffee crops; on the one hand, it provides employment opportunities for a large group of rural workers and on the other, it supplies mature fruits for the production of high quality coffee. In the present study, a device was designed and evaluated to assist in manual coffee harvesting, called Alfa, which employs a three-toothed blade beater, a DC motor powered by dry batteries and a system for receiving detached fruits. The research proceeded in two phases; in the first, the device was designed and built; in the second, an evaluation was carried out by using traditional manual collection as a comparison. The evaluations were developed in four locations: three experimental stations of Cenicafé and one private property. The variables studied were: number of fruits left on the ground after harvest, percentage of immature coffee in the harvested mass and yield. The device presented an operating time of four days without recharging, a weight less than four kg and an absence of technical failures; the operators had no problems with its use; and, in addition, it was possible to increase the yield of the operators by almost 70%; the percentage of immature coffee was between 4.5% and 3% and losses were between one and 19 fruits per site.