Abstract The environmental aspect of combustion can be considered one of the main factors in achieving sustainable power production. While various studies emphasised the positive aspect of propylene glycol as an additive for diesel-biodiesel fuel composition on emission and performance metrics of a diesel engine, an unknown element of the role of this additive in sustainable power generation cycles is still not achieved. The role of this additive in the sustainable power generation cycle is unclear, and this is considered a research gap. In this study, an environmental assessment of engine performance and emission specifications was conducted in the propylene glycol, diesel, and biodiesel fuel combination. Propylene glycol was mixed with B2 and B5 fuels at 3, 5, and 7% ratios. Fuel samples were examined in a diesel engine. Environmental assessment was conducted using life cycle assessment according to IMPACT2002+ life cycle inventory analysis instruction. According to the results, the lowest midpoint and endpoint indicators of environmental impacts were related to B5PG7, i.e., 18% lower than the control. Accordingly, B5PG7 was selected as the best fuel sample from an environmental and efficiency point of view.

Abstract A two-row upland seeder for cabbage was designed, developed, and tested to improve sowing efficiency and crop establishment in small-scale farming. It featured precision seeding and was evaluated with and without press wheels. Seed delivery rates decreased as ground speed increased, with the highest rate of 0.267 kg·ha −1 achieved at 0.6 m·s −1 ; faster speeds lowered accuracy. Slippage tests at 10 RPM showed stable traction with an average slippage of 3.92%. Field trials revealed that press wheels significantly enhanced seeding performance, providing more consistent sowing depths (mean 6.6 mm), higher germination rates (61%), and fewer missing hills than without press wheels. Statistical analysis (ANOVA, Tukey’s HSD) confirmed that press wheels had significant effects on sowing depth, germination rate, and seedling count ( p <0.05). Despite some issues like seed clogging and hopper damage, the seeder was user-friendly and effective. The study highlights the need for optimal speeds and press wheels to improve planting precision and crop establishment.

Abstract Digital agriculture is essential for enhancing crop yields by integrating modern digital methods to prevent and manage crop diseases. To address this, a deep learning-based Confidence-Aware Multi-Model Image Classification (CAMIC) framework has been developed. CAMIC incorporates FD-Net (Foliar Disease Network) to enable early detection and identification of various plant foliar diseases. Performance testing on the public PlantVillage dataset demonstrated that CAMIC can achieve a high accuracy of up to 97.91%, outperforming existing transfer learning models like ResNet, Inception, Xception, MobileNet, and EfficientNet. This solution has also been implemented as an Android application following the client-server model paradigm.

Abstract The study focuses on measuring the boiling point of brake fluid. The research is based on a qualitative analysis of brake fluid samples taken from randomly selected vehicles. A total of 100 different vehicles with varying ages and mileage were included in the examination process. Using a device designed to measure the boiling point of brake fluid, indicators that directly reflect the quality of the brake fluid were evaluated, as it is one of the main factors affecting vehicle safety in road traffic. In further sections, the research focuses on how the boiling point changes depending on the vehicle’s age and mileage. The results showed that the boiling point of glycol-based fluids significantly decreases with moisture absorption, with older vehicles and vehicles with higher mileage tending to have a lower brake fluid boiling point. Comparing different sampling locations also revealed that brake fluid in the reservoir often has a higher boiling point than fluid at the brake calliper, indicating a higher level of contamination at the brake calliper. In comparison, brake fluid samples from reservoirs exhibited higher boiling points than those from brake callipers, with differences of up to 20 °C in some cases. Of the 39 vehicles sampled from both locations, 59% of the samples were satisfactory at all points, 13% met the standard only in the reservoir, and 28% were unsatisfactory at any sampling point. The results emphasise the necessity of regular inspections and highlight that boiling point checks at the brake calliper could reveal risks otherwise undetectable from reservoir-only testing.

Abstract The presented paper focuses on comparing the capabilities for monitoring agricultural areas sown with winter wheat using satellite data and data obtained from UAVs. The NDVI vegetation index derived from both methodologies has been compared. The results show similar trends in the index variation for both methods. Although the absolute values differ, the variation curves and the zones of index deterioration are identical. The results obtained from the satellite, with a much lower resolution than that of the drone is 3.82 cm per pixel. Satellite monitoring is easily applicable and suitable for large areas, providing information every two days. However, a drawback is that cloud cover can hinder imaging, leading to extended periods without information. The drone flies below the cloud cover but is dependent on wind speed. The obtained results can help farmers to reduce the time of direct observation of winter wheat crops by performing direct observations only on the areas with reduced index.

Abstract The procedures of tribological diagnostics use oil filling as a resource for multidimensional and complex information about the phenomena, changes, and modes of wear in systems. The purpose was to investigate the possibilities of evaluating two physicochemical parameters [kinematic viscosity at 40 °C (KV40) and total acid number (TAN)] of 6 natural non-edible oils according to chemical composition by means of two methods in laboratory conditions using a tribometer. Evaluation was based on the hypothesis that the oil is considered relatively good if its changes in selected diagnostic properties remain within permissible limits for at least 1000 operating hours. One of the procedures is the assessment of bio-based hydraulic oils on a reciprocal comparison of properties. The following method is based on the monitoring of suitably chosen diagnostic signals that will indirectly rate the technical condition of the oil filling according to changes in the dependent quantities. Results demonstrated that it is possible to assume the degradation of essential oil parameters to the limit condition, to use these data to determine the technical life of the oil filling, and to obtain the trends of relative operating time. In this way, it is possible to give users information about the quality of the oil used in specific operation conditions.

Abstract Precision agriculture based on differentiated dosing of seeds and mineral fertilisers allows for enhancing soil fertility while simultaneously increasing crop yields and reducing production costs. The purpose of study is to increase the efficiency of differentiated dosing of seeds and mineral fertilisers. By determining the intra-field variability of nutrient elements, it has been revealed that the content of mobile nitrogen (N), phosphorus (P2O5), and carbon (CO2) in the arable layer varies widely within one field. Based on the data obtained, the maps of the distribution of nutrients were constructed. The research tests of the drill seeder with the control and monitoring unit of seed metering device were conducted in this field conditions, and the results were processed using the method of variational statistics. The analysis of the assessment of agrotechnical performance of the seeder shows that the values of the unevenness of sowing between devices and the instability of total sowing (in the coefficients of variations, %) meet agrotechnical requirements. It was revealed that the seeder allows for smooth adjustment, reduces time, and increases the range of seeding rate and dosing of seeding material. The obtained data confirm the effectiveness of the seeder for differentiated dosing of seeding material in precision agriculture.

Abstract Global warming and air pollution have affected the human and animal ecosystem, and a large part of these destructive effects are related to the transportation system. By replacing sustainable vehicles, combustion engines that cause climate change can be eliminated. This study compares five sustainable technologies, namely solar powered vehicles, biofuel vehicles, fuel cell electric vehicles (FCEVs), electric vehicles (EVs), and hybrid vehicles (HEVs) using the analytic hierarchy process (AHP). All criteria and sub-criteria were weighted to determine the best option according to the existing alternatives. According to the results, the solar vehicles had the minimum emission of greenhouse gases in the exhaust outlet, but the disadvantage was challenging problems in the infrastructure. Solar vehicles are dependent on weather conditions which can be encountered with difficulties in terms of distance. Hereupon, before implementing the plan, it is necessary to evaluate the study area. It is recommended to integrate hybrid support systems to overcome the problem. In the view point of criteria, the technical criterion is the most important, and among the sub-criteria, infrastructure and social understanding are the most and least effective sub-criteria, respectively. Solar vehicles require minimal infrastructure. Biofuel vehicles were preferable in terms of distance compared to others. In terms of possible risks, electric vehicles and fuel cell vehicles were the least and most dangerous, respectively. As a conclusion, solar powered vehicles were preferred among the proposed options and considered the best alternative to combustion engine vehicles. The only problem was that the process of making panels and storage batteries leads to the emission of greenhouse gases.

Abstract Evaluating the input and output process of energy in agricultural systems is one of the ways to determine the level of sustainability in these systems. For this reason, the purpose of this study was to investigate and predict the amount of input and output energies and also related indicators in cattle breeding. The information needed to conduct this study was collected by referring to Pars Company and extracting the recorded information regarding the amount of consumed inputs and the value of produced products. Also, part of the information was extracted from the financial reports presented by the company and the reports published in the annual meetings of the shareholders. In addition, the information is related to the financial period from 2011 to 2020. Based on the available data, the value of input and output energies, energy indices were calculated. Also, adaptive network-based fuzzy inference system (ANFIS) was used to predict performance and output energy. According to the results of data analysis, the average energy required for raising cattle during a one-year period was 52,604.52 MJ∙cow−1. Also, produced milk, produced manure, and born calf were considered as the output energies. The energy equivalent of produced milk during a year was 56,821.39 MJ∙cow−1. After examining different models of ANFIS, the best ANFIS model with the input membership function of trimf was selected and the R 2 and MAPE values of 0.98 and 0.42 were obtained, respectively.

Abstract Minimal tillage is becoming increasingly important in arid regions. The purpose of this study is to study the effects of different tillage methods on soil agrophysical parameters and corn yield. The main agrophysical parameters of the soil were density, hardness, and moisture. The field experiment was conducted in the Samarkand region of Uzbekistan from 2020 to 2022. The region is characterised by a continental climate, with hot and dry summers and mild winters. The experiment compared the following tillage methods: deep ploughing, shallow flat-cutting, shallow disc tillage, shallow disc tillage with direct seeding, and no-till. Soil parameters were measured at different depths (0–10 cm, 10–20 cm, 20–30 cm) at three stages of corn growth (before sowing, at the 12–13 leaf stage, and at the stage of full grain maturity). As a result, it was found that soil density with shallow surface tillage remains almost unchanged and is 1.07–1.08 g·cm−3. With deep ploughing, soil density increases from 1.014 g·cm−3 at the depth of 0–10 cm to 1.094 g·cm−3 at the depth of 20–30 cm. Soil hardness with deep ploughing increases from 26.145 kg·cm−2 at the depth of 0–10 cm to 35.445 kg·cm−² at the depth of 20–30 cm. Soil moisture gradually decreases with depth with all types of tillage, with deep ploughing showing a slightly greater decrease in moisture (by 7–8% for every 10 cm of depth) compared to shallow tillage. Deep ploughing results in greater compaction and moisture loss in the deeper soil layers. Shallow disc tillage with direct seeding provided the highest maize yield of 7.10 t·ha−1, while no-till showed the lowest yield of 5.41 t·ha−1.