Aimed at solving the problems of poor stability and easily falling into the local optimal solution in the grey wolf optimizer (GWO) algorithm, an improved GWO algorithm based on the differential evolution (DE) algorithm and the OTSU algorithm is proposed (DE-OTSU-GWO). The multithreshold OTSU, Tsallis entropy, and DE algorithm are combined with the GWO algorithm. The multithreshold OTSU algorithm is used to calculate the fitness of the initial population. The population is updated using the GWO algorithm and the DE algorithm through the Tsallis entropy algorithm for crossover steps. Multithreshold OTSU calculates the fitness in the initial population and makes the initial stage basically stable. Tsallis entropy calculates the fitness quickly. The DE algorithm can solve the local optimal solution of GWO. The performance of the DE-OTSU-GWO algorithm was tested using a CEC2005 benchmark function (23 test functions). Compared with existing particle swarm optimizer (PSO) and GWO algorithms, the experimental results showed that the DE-OTSU-GWO algorithm is more stable and accurate in solving functions. In addition, compared with other algorithms, a convergence behavior analysis proved the high quality of the DE-OTSU-GWO algorithm. In the results of classical agricultural image recognition problems, compared with GWO, PSO, DE-GWO, and 2D-OTSU-FA, the DE-OTSU-GWO algorithm had accuracy in straw image recognition and is applicable to practical problems. The OTSU algorithm improves the accuracy of the overall algorithm while increasing the running time. After adding the DE algorithm, the time complexity will increase, but the solution time can be shortened. Compared with GWO, DE-GWO, PSO, and 2D-OTSU-FA, the DE-OTSU-GWO algorithm has better results in segmentation assessment.

Regulating plant factories is crucial for optimal plant growth and yield. Although LEDs (light-emitting diode) are called cold light sources, more than 80% of the heat is still emitted into the surrounding environment. In high-density vertical agricultural facilities, the crop canopy is positioned close to the light source to maximize light absorption and promote plant growth. LED heat dissipation can cause disturbances in the microclimate of crop canopies, which can lead to tip burn disease in plant crops and result in economic losses for plant factories. CFD (computational fluid dynamics) is used as the main technical tool to simulate and optimize the environment of agricultural facilities. This study utilized Star-ccm+ to simulate the microclimate of plant factories under different light treatments. Uniformity coefficient UI and disturbance coefficient θ were proposed to quantitatively analyze LED heat dissipation’s impact on microclimate. In the T5 treatment group, which had a PPFD of 350 μmol/m²·s in the growth zone and 250 μmol/m²·s in the seedling zone, the relative humidity (RH), airflow, and temperature uniformity coefficients UI were 0.6111, 0.3259, and 0.5354, respectively, with corresponding disturbance coefficients θ of 0.0932, 0.1636, and 0.1533. This study clarifies the degree of perturbation caused by LED heat dissipation on microclimate, providing a theoretical basis for regulating plant factory light and promoting sustainability.

Monitoring anthocyanins is essential for assessing nutritional value and the growth status of plants. This study aimed to utilize hyperspectral technology to non-destructively monitor anthocyanin levels. Spectral data were preprocessed using standard normal variate (SNV) and first-derivative (FD) spectral processing. Feature wavelengths were selected using uninformative variable elimination (UVE) and UVE combined with competitive adaptive reweighted sampling (UVE + CARS). The optimal two-band vegetation index (VI2) and three-band vegetation index (VI3) were then calculated. Finally, dung beetle optimization (DBO), subtraction-average-based optimization (SABO), and the whale optimization algorithm (WOA) optimized the extreme learning machine (ELM) for modeling. The results indicated the following: (1) For the feature band selection methods, the UVE-CARS-SNV-DBO-ELM model achieved an R_m² of 0.8623, an RMSE_m of 0.0098, an R_v² of 0.8617, and an RMSE_v of 0.0095, resulting in an RPD of 2.7192, further demonstrating that UVE-CARS enhances feature band extraction based on UVE and indicating a strong model performance. (2) For the vegetation index, VI3 showed a better predictive accuracy than VI2. The VI3-WOA-ELM model achieved an R_m² of 0.8348, an RMSE_m of 0.0109 mg/g, an R_v² of 0.812, an RMSE_v of 0.011 mg/g, and an RPD of 2.3323, demonstrating good performance. (3) For the optimization algorithms, the DBO, SABO, and WOA all performed well in optimizing the ELM model. The R² of the DBO model increased by 5.8% to 27.82%, that of the SABO model by 2.92% to 26.84%, and that of the WOA model by 3.75% to 27.51%. These findings offer valuable insights for future anthocyanin monitoring using hyperspectral technology, highlighting the effectiveness of feature selection and optimization algorithms for accurate detection.

It is generally believed that stable airflow can effectively reduce tip burn, a common lettuce plant disease in closed plant factories that severely restricts the sustainable development of these factories. This study aims to achieve stable airflow in the cultivator by zoning the seedling and growth stage crops and installing differential fans, while ensuring comprehensive quality. In this study, a three-dimensional simulation plant factory model was created to simulate the airflow inside the cultivator, taking crop shading and heat dissipation from LED light sources into account. Experiments on photosynthetic physiology and airflow were used to determine environmental thresholds for crop growth, which were then used as CFD boundary conditions. After adopting the optimized cultivation model, the comprehensive quality of lettuce increased by 22.28% during the seedling stage, and the tip burn rate decreased to 26.9%; during the growth stage, the comprehensive quality increased by 25.72%, and the tip burn rate decreased to 23.2%. The zoning optimization cultivation method and differential fan arrangement used in this study to improve the airflow field of plant factories provide new ideas and reliable theoretical support for plant factories to combat lettuce tip burn disease.

In this study we design and test a novel solar tracking generation system. Moreover, we show that this system could be successfully used as an advanced solar power source to generate power in greenhouses. The system was developed after taking into consideration the geography, climate, and other environmental factors of northeast China. The experimental design of this study included the following steps: (i) the novel solar tracking generation system was measured, and its performance was analyzed; (ii) the system configuration and operation principles were evaluated; (iii) the performance of this power generation system and the solar irradiance were measured according to local time and conditions; (iv) the main factors affecting system performance were analyzed; and (v) the amount of power generated by the solar tracking system was compared with the power generated by fixed solar panels. The experimental results indicated that compared to the power generated by fixed solar panels, the solar tracking system generated about 20% to 25% more power. In addition, the performance of this novel power generating system was found to be closely associated with solar irradiance. Therefore, the solar tracking system provides a new approach to power generation in greenhouses.

This study proposed a design method for forced-vibration subsoiling to reduce resistance and consumption. The vibration digging parameters of the Antlion larvae were obtained by high-speed camera, and a forced-vibration subsoiling shovel handle and six different shovel tips were designed by the non-smooth resistance-reducing surface design method. The resistance-reducing and consumption-reducing effects were verified in the field subsoiling experiment. The results showed that the resistance of subsoiling gradually decreased with the vibration frequency increasing. This vibration subsoiling method could not only reduce resistance but also reduce the total energy consumption, the resistance reduction rate reached 14.2–21.2%, and the total energy consumption was reduced by 11.2–16.5%. It could achieve the comprehensive subsoiling effect and create the soil conditions with the combination of loose and firmness. The non-smooth surface contributed to the reduction in resistance, and the forward speed had a more negligible effect on the resistance of subsoiling. The results had demonstrated that the combination of high-frequency vibration and non-smooth surfaces helped to reduce the cohesion of the soil, reduce the angle of internal friction in the soil, destroy the water film layer on the contact surface between the soil-touching components and the soil, change the soil flow state, and reduce the adhesion of the interface layer. The design method in this study could not only be applied to the design of vibration resistance reduction in the subsoiler but also had significance for the design of the other soil-contacting components.