Camellia oleifera Abel. is one of the world’s four famous woody oil trees and has drawn increasing attention because of its high commercial value. Endophytes are microorganisms inhabiting inside plant tissues, and their functions vary with the change of host status and environmental parameters. To deepen our understanding of the interactions between C. oleifera and their endophytic actinobacteria, the present study investigated the four endophytic actinobacterial composition-residing high-yield C. oleifera trees. A total of 156 endophytic actinobacterial isolates were obtained distributed in 17 genera. Among them, Streptomyces was the dominant endophytic actinobacteria, followed by Nocardia, Amycolatopsis, Microbiospora, Micromonospora and other rare actinobacteria genera. Soil characteristics including soil pH and organic matter were found to play crucial roles in shaping the endophytic actinobacterial community composition. Furthermore, all isolates were studied to determine their plant growth-promotion traits, 86.54% could produce Indole 3-Acetic Acid, 16.03% showed nitrogen-fixing, 21.15% showed phosphorus solubilizing, and 35.26% produced siderophore. Under the glasshouse condition, some isolates exhibited growth promotion effects on C. oleifera seedlings with significant increase in spring shoot length and ground diameter. Altogether, this study demonstrated that C. oleifera plants harbored a high diversity and novelty of culturable endophytic actinobacteria, which represent important potential as natural biofertilizers for the high production of C. oleifera.

Mosaic is one of the oldest known decorative arts, and it is widely used for its small, exquisite and colorful features. However, because of the heavy workload of manual color selection, this article has modeled, solved and analyzed the color selection problem of mosaic tiles. In the actual research process, this project will disassemble it into three directions for separate research. The first direction is mainly to study how to find the closest tile color to each color to calculate and analyze the color difference. In this direction, We have established a LAB color model and an RGB color model for solution and comparison. The second direction mainly studies the optimization problems related to color coverage. In this direction, we establish an RGB color model, use random simulation methods to find the new color points that meet the requirements, and then the center of the point set composed of the original 22 colors The coordinates are always kept at (128,128,128). Considering the abundance of colors locally, a greedy algorithm model is established. Finally, the results of the two models are comprehensively evaluated, and appropriate new colors are selected. The third direction mainly studies how to balance the cost and the performance effect. In this direction, based on the ten new colors obtained in the second question, we evaluate the dispersion degree of the point distribution in the space and conduct a series of analyses in combination with the cost.