Biodiesel is one of the most popular prospective alternative fuels and can be obtained from a variety of sources. Waste frying oil is one such source along with the various raw vegetable oils. However, some specific technical treatments are required to improve certain fuel properties such as viscosity and calorific value of the biodiesel being obtained from waste cooking oil methyl ester (WCOME). Various treatments are applied depending on the source and therefore the composition of the cooking oil. This research investigated the performance of WCOME as an alternative biofuel in a four-stroke direct injection diesel engine. An 8-mode test was undertaken with diesel fuel and five WCOME blends. The best compromise blend in terms of performance and emissions was identified. Results showed that energy utilization factors of the blends were similar within the range of the operational parameters (speed, load and WCOME content). Increasing biodiesel content produced slightly more smoke and NOx for a great majority of test points, while the CO and THC emissions were lower.

Irrigation plays a crucial role in maize cultivation, as watering is essential for optimizing crop yield and quality, particularly given maize’s sensitivity to soil moisture variations. In the current study, a hybrid Long Short-Term Memory (LSTM) approach is presented aiming to predict irrigation scheduling in maize fields in Bursa, Turkey. A critical aspect of the study was the use of the Aquacrop 7.0 model to simulate soil moisture content (MC) data due to data limitations in the investigated fields. This simulation model, developed by the Food and Agriculture Organization (FAO), helped overcome gaps in soil sensor data, enhancing the LSTM model’s predictions. The LSTM model was trained and tuned using a combination of soil, weather, and satellite-based plant vegetation data in order to predict soil moisture content (MC) reductions. The study’s results indicated that the LSTM model, supported by Aquacrop 7.0 simulations, was effective in predicting MC reduction across various time phases of the maize growing season, attaining R² values ranging from 0.8163 to 0.9181 for Field 1 and from 0.7602 to 0.8417 for Field 2, demonstrating the potential of this approach for precise and efficient agricultural irrigation practices.