Synergistic effects of ferulic acid esterase-producing lactic acid bacteria, cellulase and xylanase on the fermentation characteristics, fibre and nitrogen components and microbial community structure of Broussonetia papyrifera during ensiling.

BACKGROUND: The high fibre content of whole plants of Broussonetia papyrifera limits its efficient utilization. Ferulic acid esterase (FAE), in combination with xylanase, can effectively cleave the lignin-carbohydrate complex, promoting the function of cellulase. However, little is known about the impact of these additives on silage. To effectively utilize natural woody plant resources, FAE-producing Lactiplantibacillus plantarum RO395, xylanase (XY) and cellulase (CE) were used to investigate the dynamic fermentation characteristics, fibre and nitrogen components and microbial community structure during B. papyrifera ensiling. RESULTS: Broussonetia papyrifera was either not treated (CK) or treated with FAE-producing lactic acid bacteria (LP), CE, XY, LP + CE, LP + XY or LP + CE + XY for 3, 7, 15, 30 or 60 days, respectively. In comparison with those in the CK treatment, the L. plantarum and enzyme treatments (LP + CE, LP + XY and LP + XY + CE), especially the LP + XY + CE treatment, significantly increased the lactic acid concentration and decreased the pH and the contents of acid detergent insoluble protein and NH3 -N (P < 0.05). Enzyme addition improved the degradation efficiency of lignocellulose, and a synergistic effect was observed after enzyme treatment in combination with LP; in addition, the lowest acid detergent fibre, neutral detergent fibre, hemicellulose and cellulose contents were detected after the LP + CE + XY treatment (P < 0.05). Moreover, CE, XY and LP additions significantly improved the microbial community structure, increased the relative abundance of Lactiplantibacillus and Firmicutes, and effectively inhibited undesirable bacterial (Enterobacter) growth during ensiling. CONCLUSION: FAE-producing L. plantarum and the two tested enzymes exhibited synergistic effects on improving the quality of silage, which indicates that this combination can serve as an efficient method for improved B. papyrifera silage utilization. © 2023 Society of Chemical Industry.

Real-time terrain storage generation from multiple sensors towards mobile robot operation interface.

A mobile robot mounted with multiple sensors is used to rapidly collect 3D point clouds and video images so as to allow accurate terrain modeling. In this study, we develop a real-time terrain storage generation and representation system including a nonground point database (PDB), ground mesh database (MDB), and texture database (TDB). A voxel-based flag map is proposed for incrementally registering large-scale point clouds in a terrain model in real time. We quantize the 3D point clouds into 3D grids of the flag map as a comparative table in order to remove the redundant points. We integrate the large-scale 3D point clouds into a nonground PDB and a node-based terrain mesh using the CPU. Subsequently, we program a graphics processing unit (GPU) to generate the TDB by mapping the triangles in the terrain mesh onto the captured video images. Finally, we produce a nonground voxel map and a ground textured mesh as a terrain reconstruction result. Our proposed methods were tested in an outdoor environment. Our results show that the proposed system was able to rapidly generate terrain storage and provide high resolution terrain representation for mobile mapping services and a graphical user interface between remote operators and mobile robots.

Optimization of carton recycling site selection using particle swarm optimization algorithm considering residents' recycling willingness.

With the development of the express delivery industry, how to increase the recycling rate of waste cartons has become a problem that needs to be solved. Recycling enterprises began to provide the new recycling mode, door-to-door recycling services, to residents with waste cartons. In this article, we constructed a site selection model for a carton recycling site with the aim of maximizing total profits. Considering the residents' recycling willingness and the government subsidy earned through the contribution to carbon emission reduction, this model achieves the task of site selection and unit price fixation for carton recycling. We used the particle swarm optimization (PSO) algorithm to solve the model and compared it with the genetic algorithm (GA) for validity testing. PSO algorithm was also used to carry out sensitivity analysis in this model. The proposed model and the results of the sensitivity analysis can be used for decision-making in recycling enterprises as well as for further research on waste recycling and reverse logistics.