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.

The inherent complexity of cellulose, hemicellulose, and lignin contributes to the recalcitrance of lignocellulosic biomass, resulting in a low conversion efficiency and high cost of bioethanol conversion. Pretreatment methods that disrupt the plant cell structure of lignocellulose, such as straw, can significantly enhance the conversion efficiency. In this study, we utilized an acid-assisted mechanocatalytic depolymerization technique to pretreat rice straw, and the results demonstrated a significant disruption of the cellulose structure of the straw. Compared to the untreated straw, the particle size of pretreated straw reduced from 279 μm to 11.8 μm, the crystallinity of cellulose decreased from 43.05% to 22.71%, the specific surface area increased by 177%, and the surface oxygen-to-carbon ratio (O/C) ratio was enhanced by 75%. The changes in microstructure enabled the pretreated straw to achieve a total sugar yield of over 95% within 12 h of enzymatic hydrolysis, significantly superior to the 36.24% yield from untreated straw, the 45.20% yield from acid impregnated straw, and the 73.25% yield from ball milled straw. Consequently, acid-assisted mechanocatalytic depolymerization emerges as a highly effective pretreatment strategy to enhance both the enzymatic hydrolysis and the overall conversion efficiency of rice straw.

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.

Antibiotic contaminants such as tetracycline (TC) from agricultural production have become widely distributed and persistently accumulated in aquatic environments (rivers, lakes, and oceans), posing severe threats to ecological security and human health. This study developed a modified rice-straw-derived biochar through NaOH activation and ball-milling-assisted Fe₃O₄ loading, which simultaneously enhanced TC adsorption capacity and enabled magnetic recovery. The Box–Behnken design (BBD) response surface methodology was employed to optimize three key preparation parameters: ball-milling time (A, 39.95 min), frequency (B, 57.23 Hz), and Fe₃O₄/biochar mass ratio (C, 2.85:1), with TC adsorption capacity as the response value. The modified biochar was systematically characterized using SEM, BET, FTIR, XRD, and XPS, while adsorption mechanisms were elucidated through kinetic studies, isotherm analyses, and pH-dependent experiments. The results demonstrate that modification via ball-milling with Fe₃O₄ loading significantly enhanced the biochar’s tetracycline adsorption capacity. The maximum adsorption capacity of the modified biochar reached 102.875 mg/g, representing a 114.85% increase from the initial value of 47.882 mg/g observed for the pristine biochar. Furthermore, the modified biochar exhibited excellent stability, maintaining robust adsorption performance across a wide pH range. The primary adsorption mechanisms involved metal coordination complexation, supplemented by hydrogen bonding, π-π interactions, and pore filling.

Abaca fibres that have excellent mechanical properties are widely applied in the production and preparation of eco-friendly polymer composites as reinforcement materials. However, the weak interfacial bonding property of the abaca fibre and composite matrix limits the further extended application of abaca fibre-reinforced polymer composites. In this research, the findings demonstrate that, compared to raw abaca fibres, the interfacial shear strength (IFSS) value between the treated fibre and matrix is improved by 32% to 86%. Moreover, chemically treated abaca fibres could not only improve the wear resistance of the polymer composites, but also could promote the formation of primary and secondary plateaus. The best wear resistance behaviour was demonstrated by the sample with abaca fibres treated with 3% NaOH and 5% silane solutions, which had a maximum reduction in the sum wear rate of 28.44%. This research will provide detail on theoretical guidance and technical support for the development of eco-friendly natural fibre-reinforced polymer composites.