A novel series of biocomposites was prepared through the utilisation of hot-pressing and blending methods, utilising bamboo particles of varying sizes and a zein solution. The influence of particle size and the parameters of hot pressing on the mechanical properties of the composites was investigated through the application of an alkali solution to pre-treat the bamboo particles and the employment of ultra-high pressure to pre-handle the zein solution. Four response surface models were established to optimise the processing parameters based on mechanical testing experiments and quadratic regression analysis. The influencing factors were moisture content, press temperature, and press time, and the responses were modulus of rupture (MOR), modulus of elasticity (MOE), tensile strength (TS) and 2 h thickness swelling rate (2h-TSR). The findings indicated that the TS of composites reached a maximum value of 17.5 MPa with a bamboo particle size of 40 mesh; the MOR and MOE of composites reached a maximum value of 28.72 MPa and 2669.75 MPa when the bamboo particle size was 60 mesh; regarding the 2h-TSR of composites the lowest value of 5.8% was obtained for 80-mesh bamboo particle size. The optimum moulding process parameters were obtained with moisture content ranging from 14% to 16%, press temperature ranging from 170 °C to 175 °C, and press time ranging from 12 min to 15 min, respectively.

Introduction: Accurate crop–weed segmentation is critical for precision weed management in pepper fields. However, reliable pixel-level discrimination remains challenging because pepper plants and weeds often share similar green textures under conditions of occlusion, illumination variation, and scale changes, while weed regions are frequently small, fragmented, and spatially dispersed. Methods: This study proposes an improved DeepLabV3+-based semantic segmentation framework for pepper–weed segmentation. MobileNetV3 was employed as an efficiency-oriented backbone, while Adaptive Activation Fusion and Efficient Channel Attention were integrated to enhance nonlinear feature representation and channel-wise recalibration. A customized atrous spatial pyramid pooling module was designed to capture multiscale contextual information, and an OS = 16 hierarchical decoder was developed to fuse high-, mid-, and low-level features with residual refinement for improved boundary recovery. During training, focal cross-entropy loss and Dice loss were combined with weighted sampling, class-aware cropping, and data augmentation to strengthen the learning of difficult weed regions and improve robustness under complex field conditions. Results: On the independent pepper-field weed test set, the proposed model achieved an mIoU of 95.87%, recall of 97.98%, a boundary F1-score of 95.88%, a boundary IoU of 92.13%, and an inference speed of 46.86 FPS. Discussion: The results demonstrate that the proposed framework improves region-level segmentation accuracy, boundary quality, and inference efficiency. These advantages indicate its potential for practical precision weeding applications in pepper fields.

It is imperative to investigate the behavior of the droplet superimposed condensation of deltamethrin reagent on strawberry leaf surface, as well as the dynamic variation rule of its contact angle. A microinjector was utilized to conduct the experiment of droplet superposition and condensation. The surface tension of deltamethrin droplets was measured by means of an optical contact angle meter, and the wetting parameters, such as contact angle, volume, and spreading diameter, were obtained by observing the leaf surfaces of various parts of strawberries during the dynamic process of superimposed condensation. A model was constructed by establishing the relationship between the contact angle and the coordinates of the observation point and time through the spatial fitting interpolation method. This model is a three-dimensional dynamic trend surface model of contact angle for droplet superposition and condensation. The findings indicated that the surface tension of the deltamethrin drop was 28.92 ± 0.2 mN·m⁻¹. The interval between the superposition of two droplets and the subsequent condensation of a new droplet was found to be within 0.5 s. The time taken for a new droplet to form was found to be between 0.0356 and 0.0476 s. The change in contact angle during the processes of superposition and coalescence can be broadly categorized into three distinct stages: namely, sharp oscillation, slight decrease, and gentle stabilization. The volume of the new droplet formed by the superposition and condensation was found to be 1.05 to 1.93 times that of a lying droplet. The maximum increase in the spreading diameter of the superimposed and condensed droplets was 40.29%. The three-dimensional dynamic trend surface model can reflect the overall spatial–temporal change trend of the contact angle in the process of superposition and coalescence. The model successfully passed the overall significance F-test and each coefficient of the statistical t-test, and demonstrated a satisfactory time interpolation effect. The experimental verification demonstrates that the predicted contact angle value of the model is consistent with the measured value.

It is imperative to investigate the behaviour of droplet superimposed condensation of deltamethrin reagent on the strawberry leaf surface, and the dynamic variation rule of its contact angle. The microinjector was utilised to conduct the experiment of droplet superposition and condensation. The surface tension of deltamethrin droplets was measured by means of an optical contact angle meter, and the wetting parameters such as contact angle, volume and spreading diameter were obtained by observing the leaf surfaces of various parts of strawberries during the dynamic process of superimposed condensation. A model was constructed by establishing the relationship between the contact angle and the coordinates of the observation point and time through the spatial fitting interpolation method. This model is a three-dimensional dynamic trend surface model of contact angle for droplet superposition and condensation. The findings indicated that the surface tension of the deltamethrin drop was 28.92 ± 0.2 mN·m-1. The interval between the superposition of two droplets and the subsequent condensation of a new droplet was found to be within 0.5 seconds. The time taken for a new droplet to form was found to be between 0.0356 and 0.0476 seconds.The change of contact angle during the processes of superposition and coalescence can be broadly categorised into three distinct stages: namely, sharp oscillation, slight decrease and gentle stabilisation. The volume of the new droplet formed by the superposition and condensation was found to be 1.05 to 1.93 times that of a lying droplet. 1.93 times that of a lying droplet. The maximum increase in the spreading diameter of the superimposed and condensed droplets was 40.29%.The three-dimensional dynamic trend surface model can reflect the overall spatial-temporal change trend of the contact angle in the process of superposition and coalescence. The model successfully passed the overall significance F test and each coefficient of statistical T test, and demonstrated a satisfactory time interpolation effect. The experimental verification demonstrates that the predicted contact angle value of the model is consistent with the measured value.