ABSTRACT Coffee growers who produce the robusta species (Conilon) have sought to increase productivity and drink quality by improving production techniques. Artificial vision systems can assist in increasing the efficiency of operations associated with crop management. This study aimed to obtain colorimetric characteristics of robusta coffee fruits at different stages of maturity and use them for classifying fruits from digital images. A digital camera with spectral resolution in the visible was used to acquire images from 60 samples of coffee fruits at the green, cherry, and over-ripe stages of maturity. Colorimetric variables were extracted from the RGB, HIS, and L*a*b* color models and correlated with the physicochemical attributes of the fruits. The principal component analysis associated with the k-means technique was applied to the colorimetric variables that showed a significant correlation with the physical-chemical attributes. The colorimetric variables were reduced to a principal component, which presented an explanatory percentage of the variance of 82.33%. The clustering obtained by the application of the k-means technique showed the feasibility of using images for the automatic classification of robusta coffee fruits, with an overall accuracy of 100%.

ABSTRACT In recent years, the coffee has undergone major changes, and in case of transplanting operation, the use of machinery has proved to be a viable alternative to producers. Prior knowledge of the influence of the variables that influence the operational capability of these machines can generate models to estimate precisely these parameters, thus enabling the optimization and management of mechanized operations. One of this tool is the use of the response surface methodology, which allows checking the influence of different independent variables and the response generated to allow a great value. This study aims to verify the use of the response surface method to determine parameters of mechanized operations in coffee plant implantation. The results show that the number of seedlings deposited increases with the increase in operating speed. In contrast, the adoption of higher speeds decreases the efficiency of the evaluated field operations. The response surface methodology was an important tool to check the effect of variables on performance parameters, and the generated models showed high significance allowing the identification of the effects of the operational speed and the average length of the cultivation line.

RESUMO No sistema supermecanizado de colheita do café todas as operações são realizadas de forma mecanizada. Com a finalidade de melhorar a logística das operações agrícolas mecanizadas, o conhecimento das variáveis que influenciam no desempenho operacional pode gerar modelos que permitam estimar, de maneira precisa, esses parâmetros. O uso da metodologia de superfície de resposta (MSR) permite verificar a influência de diferentes variáveis independentes em que resposta gerada permite alcançar um valor ótimo. Este estudo objetivou verificar a influência da velocidade, o comprimento médio de entrelinhas e a declividade das áreas nos parâmetros de desempenho operacional em diferentes operações mecanizadas na cafeicultura, utilizando MSR, como: colheita, varrição e enleiramento. Os resultados mostram que a declividade influencia diretamente no desempenho operacional da colheita mecanizada de café. A MSR mostrou-se como importante ferramenta para verificar o efeito das variáveis nos parâmetros de desempenho enquanto os modelos gerados apresentaram alta significância.

ABSTRACT In super-mechanized coffee harvesting system, all operations are performed mechanically. In order to improve the logistics of mechanized agricultural operations, the knowledge on the variables that affect the operational performance can generate models to accurately estimate these parameters. The use of response surface methodology (RSM) allows to verify the influence of different independent variables and the generated response to allow for a great value. This study aimed to verify, using RSM, the influence of speed, mean length of rows and the slope of the areas on the operational performance parameters in different mechanized operations in coffee production, such as: harvest, sweeping and gathering. The results show that the slope directly influences the operational performance of the mechanical harvesting of coffee. The RSM proved to be an important tool to verify the effect of variables on performance parameters, and the generated models showed high significance.

No cenário atual brasileiro de constantes quedas de energia e iminência de uma crise no setor elétrico, a utilização de grupos geradores tem sido bastante comum no meio rural e os bicombustíveis, como o biodiesel, representam uma opção para diversificação da matriz energética. Este trabalho objetivou avaliar o uso do biodiesel de soja em diferentes concentrações em um motor de ciclo diesel sob diferentes demandas de cargas do motor. Foram utilizadas as concentrações: 5% (B5), 10% (B10), 20% (B20), 50% (B50), 75% (B75) e 100% de biodiesel (B100) em um grupo gerador a diesel, com motor de 5 Hp de quatro tempos, em diferentes condições de operação do motor, por meio de demandas de cargas elétricas: 500, 1.000, 1.500, 2.000 W e desligadas conectadas ao grupo gerador. Foram realizados ensaios para quantificação do consumo horário de combustível e da emissão de gases. As variáveis sofreram influência significativa conforme foram alteradas as cargas elétricas e as misturas de combustível. O uso do biodiesel em concentrações maiores reduz consideravelmente a emissão da maioria dos gases poluentes e se tem praticamente anulada a emissão de enxofre para concentrações acima de 65% de biodiesel.

In the current scenario of constant power drops in Brazil and an imminent crisis in the electricity sector, the use of generators and biofuels such as biodiesel has been quite common in rural areas represents an option for diversification of the energy matrix. This study evaluated the use of soybean biodiesel in different concentrations in a diesel engine cycle under different demands of engine loads. Concentrations used were: 5% (B5), 10% (B10), 20% (B20), 50% (B50), 75% (B75) and 100% biodiesel (B100) in a diesel generator with engine of 5 Hp of four-stroke under different operating conditions of the engine, through the demands of electrical loads: 500, 1.000, 1.500, 2.000 W and off connected to the generator. Tests were conducted to quantify the hourly consumption of fuel and gas emissions. The variables suffered significant influence as the electrical charges and fuel mixtures were changed. The use of biodiesel in higher concentrations considerably reduces the emission of majority of pollutant gases and practically nullified the emission of sulfur in concentrations above 65% biodiesel.