The aim of the study was to analyze the process of roasting coffee beans in a convection–conduction roaster (CC) without a heat exchanger and a convection–conduction–radiation roaster (CCR) with a heat exchanger for determination of the aroma profile. The aroma profile was analyzed using the SPME/GC-MS technique, and an Agrinose electronic nose was used to determine the aroma profile intensity. Arabica coffee beans from five regions of the world, namely, Peru, Costa Rica, Ethiopia, Guatemala, and Brazil, were the research material. The chemometric analyses revealed the dominance of azines, alcohols, aldehydes, hydrazides, and acids in the coffee aroma profile. Their share distinguished the aroma profiles depending on the country of origin of the coffee beans. The high content of pyridine from the azine group was characteristic for the coffee roasting process in the convection–conduction roaster without a heat exchanger, which was shown by the PCA analysis. The increased content of pyridine resulted from the appearance of coal tar, especially in the CC roaster. Pyridine has an unpleasant and bitter plant-like odor, and its excess is detrimental to the human organism. The dominant and elevated content of pyridine is a defect of the coffee roasting process in the CC roaster compared to the process carried out in the CCR machine. The results obtained with the Agrinose showed that the CC roasting method had a significant effect on the sensor responses. The effect of coal tar on the coffee beans resulted in an undesirable aroma profile characterized by increased amounts of aromatic volatile compounds and higher responses of Agrinose sensors.

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This study deals with the optimization of energetic and exergetic parameters of a hybrid-solar dryer to dry basil leaves under determined experimental conditions at three air temperatures (40 °C, 55 °C, and 70 °C) and three bed thickness levels (2, 4, and 6 cm). The optimization of the thermodynamic parameters was performed using the response surface method (RSM) based on the central composite design (CCD) and the desirability function (DF) to maximize the drying rate, exergy efficiency, improvement potential rate and the sustainability index, and to minimize the energy utilization, energy utilization ratio and exergy loss rate. These parameters were calculated on the basis of the first and second laws of thermodynamics as the response variables. Based on the results obtained, it was determined that the optimal conditions for basil drying were at a drying air temperature of 63.8 °C and a bed thickness of 2 cm. At this point, the parameters of the drying rate, energy utilization, energy utilization ratio, exergy efficiency, exergy loss rate, improvement potential rate and sustainability index were obtained with the maximum utility function (D = 0.548) as 0.27, 0.019 (kJ/s), 0.23, 65.75%, 0.016 (kJ/s), 1.10 (kJ/s) and 0.015, respectively.

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Since the supply of basic needs, especially food, is among the strategic priorities of each country and conventional food production methods no longer suffice, food production methods are now transforming into industrial approaches. Industrialization, however, requires higher energy usage. Greater energy demand brings about the issue of energy sustainability. In particular, the depletion of fossil fuels results in serious challenges in food production processes. On the other hand, the utilization of energy carriers is accompanied by environmental contamination. In this regard, evaluating energy consumption and environmental pollution in the production systems can be a proper approach to finding the energy consumption and pollution centers for presenting applicable solutions to decrease pollution. In this study, energy indices of ER, EP, SE, and NEG were assessed to evaluate the energy consumption of lettuce production. The results showed values of 0.4, 17.28 kg/MJ, 0.06 MJ/kg, and 29922 MG/ha for ER, EP, SE, and NEG, respectively. Among the consumption inputs, diesel fuel and nitrogen fertilizer had the highest consumption rate. Pollutants were also explored by the life cycle assessment method. Accordingly, chemicals and agricultural machinery led to the highest contaminating emissions. To reduce environmental contaminants, lowering the application of chemical pesticides, using biological approaches to combat pests, determining the proper amount of chemical fertilizers, using animal fertilizers, and using the proper agricultural machines should be considered.