The precise detection of volatile organic compounds plays a pivotal role in addressing environmental concerns, industrial safety, and medical diagnostics. The accurate identification and quantification of these compounds because of their ubiquity and potential health hazards has fueled the development of advanced sensing technologies. This work presents a sensing system in the realm of long-wavelength infrared spectroscopy for achieving enhanced selectivity and sensitivity of benzene, toluene, and propane detection through quartz-enhanced photoacoustic spectroscopy. High-resolution gas spectroscopy is made possible by the use of specially designed InAs/AlSb-based quantum cascade lasers, emitting in the wavelength range 13–15 μm, and quartz tuning forks. The sensor system, characterized by its robustness and precision, demonstrates exceptional capabilities in benzene, toluene, and propane detection. The system's capacity for practical applications in environmental monitoring and medical diagnostics is demonstrated by its ability to distinguish these volatile organic compounds with a minimum detection limit of 113 ppb, 3 ppb, and 3 ppm for toluene, benzene, and propane at an integration time of 10 s, even in complex gas matrices. This work advances gas sensing technology while also offering insightful information on spectral interferences, a persistent problem in the field. The results usher in a new era of sophisticated and reliable gas sensing techniques meeting the growing demand for precise volatile organic compounds detectors for environmental monitoring purposes.

Agricultural tractors are highly fuel-consuming and soil/air polluting machines; thus, the introduction of new sustainable technologies, such as hybridization, can be very impactful for the development of electric hybrid agricultural tractors. These vehicles combine the classic internal combustion engine with an electric machine. This paper reports the modeling and simulation, conducted using a simulation software typically used for on-road vehicles, of a two-wheel-drive agricultural tractor in three different configurations: the conventional one, and the series and parallel electric-hybrid powertrains. The simulated task is the trailing of a “big square baler” during the process of straw wrapping and baling. The evaluation and the comparison of the fuel consumption, CO₂ emissions and the depth of discharge of the different configurations have been carried out to determine if it is possible to downsize the ICE while maintaining the same performance levels. This study highlights the fact that both the fuel consumption and the CO₂ emissions of series and parallel electric-hybrid agricultural tractors are ten times lower and five times lower than those of a traditional tractor, respectively. Furthermore, the presence of an electric machine allows a more precise speed profile tracking. This study points out that the hybridization of agricultural tractor powertrains is one of the most promising approaches for reducing pollutant emissions and fuel consumption.

Agricultural tractors are high fuel-consuming and polluting machines, thus the introduction of new sustainable technologies, as hybridization, can be very impactful for the development of electric hybrid agricultural tractors. These vehicles combine the classic internal combustion engine with an electric machine, to reduce the environmental impact and improve the efficiency. This paper reports the modeling and the simulation conducted, using a simulation software typically used for on-road vehicles, of a two wheel-drive agricultural tractor in three different configurations: the conventional one, the series and the parallel electric hybrid powertrain. The simulated task is the trailing of a big square baler during the process of straw wrapping and baling. The evaluation and the comparison of the fuel consumption, CO2 emissions and the depth of discharge of the different configurations has been carried out to determine if it is possible to downsize the ICE, maintaining the same performances. This study points out that the hybridization of agricultural tractors powertrains is one of the most promising approaches to reduce pollutant emissions and fuel consumption.

Thermal cameras are becoming popular in several applications of precision agriculture, including crop and soil monitoring, for efficient irrigation scheduling, crop maturity, and yield mapping. Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, to deeply understand the variability of crop and soil conditions. However, few commercial software programs, such as PIX4D Mapper, can process thermal images, and their functionalities are very limited. This paper reports on the implementation of a custom MATLAB^® R2024a script to extract agronomic information from thermal orthomosaics obtained from images acquired by the DJI Mavic 3T drone. This approach enables us to evaluate the temperature at each point of an orthomosaic, create regions of interest, calculate basic statistics of spatial temperature distribution, and compute the Crop Water Stress Index. In the authors’ opinion, the reported approach can be easily replicated and can serve as a valuable tool for scientists who work with thermal images in the agricultural sector.

One of the most delicate operations in the sugar beet harvesting process is removing the tops from the heads of the root crops without any mechanical damages. The aim of this study is to improve the design of the conveying and unloading system of the sugar beet topper machine. In this paper, a mathematical model of the motion of a cut beet tops particle M, along the conveying and unloading system, has been developed to support the evaluation of kinematic and design parameters, depending on the rotational speed of the thrower blade, the air flow speed, the required ejection speed of particle M, and the position of the trailer that moves alongside the harvester. It has been established that increasing the speed Va of the top particle M, which has left the end of the blade of the thrower, leads to an increase in the arc coordinate S(t) of its movement along the cylindrical section of the casing. Within the range of the speed change from 4 m·s^–1 to 8 m·s^–1, the value of the arc coordinate S(t) increases by 1.4 times during time t = 0.006 s. Moreover, a rapid decrease in speed V is observed with an increase in the length x of the discharge chute.