Credit risk assessment of small and micro enterprise based on machine learning.

Small and micro enterprises are pivotal in national economic and social development. To foster their growth, managing their credit risks scientifically is crucial. This study starts by examining the credit information of these enterprises. We use imbalanced sample processing algorithms to ensure a balanced representation of minority-class samples. Then, a machine learning classifier is employed to identify key factors contributing to these enterprises' low credibility. Based on these factors, an XGBoost scoring card model is developed. The study reveals: firstly, the integration of the SMOTE algorithm with the XGBoost model exhibits certain performance advantages in handling imbalanced datasets; secondly, trustworthy financial information remains at the heart of crucial risk determinants; thirdly, the XGBoost scoring card model based on significant features effectively enhances the accuracy of credit risk assessment. These insights provide both theoretical references and practical tools for enhancing the robustness of small and micro enterprises, facilitating early warnings on credit risks, and refining financing efficiency.

Microbial regulation of plant secondary metabolites: Impact, mechanisms and prospects.

Plant secondary metabolites possess a wide range of pharmacological activities and play crucial biological roles. They serve as both a defense response during pathogen attack and a valuable drug resource. The role of microorganisms in the regulation of plant secondary metabolism has been widely recognized. The addition of specific microorganisms can increase the synthesis of secondary metabolites, and their beneficial effects depend on environmental factors and plant-related microorganisms. This article summarizes the impact and regulatory mechanisms of different microorganisms on the main secondary metabolic products of plants. We emphasize the mechanisms by which microorganisms regulate hormone levels, nutrient absorption, the supply of precursor substances, and enzyme and gene expression to promote the accumulation of plant secondary metabolites. In addition, the possible negative feedback regulation of microorganisms is discussed. The identification of additional unknown microbes and other driving factors affecting plant secondary metabolism is essential. The prospects for further analysis of medicinal plant genomes and the establishment of a genetic operation system for plant secondary metabolism research are proposed. This study provides new ideas for the use of microbial resources for biological synthesis research and the improvement of crop anti-inverse traits for the use of microbial resources.

Difference in the Effect of Applying Bacillus to Control Tomato Verticillium Wilt in Black and Red Soil.

In practical applications, the effectiveness of biological control agents such as Bacillus is often unstable due to different soil environments. Herein, we aimed to explore the control effect and intrinsic mechanism of Bacillus in black soil and red soil in combination with tomato Verticillium wilt. Bacillus application effectively controlled the occurrence of Verticillium wilt in red soil, reducing the incidence by 19.83%, but played a limited role in black soil. Bacillus colonized red soil more efficiently. The Verticillium pathogen decreased by 71.13% and 76.09% after the application of Bacillus combinations in the rhizosphere and bulk of the red soil, respectively, while there was no significant difference in the black soil. Additionally, Bacillus application to red soil significantly promoted phosphorus absorption. Furthermore, it significantly altered the bacterial community in red soil and enriched genes related to pathogen antagonism and phosphorus activation, which jointly participated in soil nutrient activation and disease prevention, promoting tomato plant growth in red soil. This study revealed that the shaping of the bacterial community by native soil may be the key factor affecting the colonization and function of exogenous Bacillus.

Host genotype and age shape the microbial community in the rhizosphere soils of Camellia forests.

Microbiota living in the rhizosphere influences plant growth and fitness, from the opposite perspective; whether host genotypes control its root microbiota is of great interest to forest breeders and microbiologists. To improve low-yield plantations and promote sustainable management of Camellia oleifera, high-throughput sequencing was used to study the chemical properties and microbiome in rhizosphere soil of Camellia forests under three genotypes (common C. oleifera, local C. gauchowensis, and C. chekiangoleosa) and three growth stages (sapling stage at 4-year-old, primary fruit stage at 7-year-old, and full fruiting stage at 11-year-old). The results showed that the rhizosphere soil organic matter (OM), nutrient concentrations, diversity, and community composition of the microbiome were significantly varied among different Camellia genotypes. The relative abundance of symbiotic and pathotrophic fungi in the rhizosphere soil of C. chekiangoleosa was significantly higher than that of C. gauchowensis. Concentrations of OM, available phosphorus (AP), and bacterial alpha diversity increased with tree age. Fungi of Saitozyma, Mortierella, and Glomeromycota and bacteria of Burkholderia-Caballeronia-Paraburkholderia and Vicinamibacterales had potential for fertilizer development for Camellia plantation. Camellia genotypes and growth stages were significantly correlated with the rhizosphere soil pH, OM, and available potassium (AK). Soil pH and OM were key factors that affected the microbiome in the Camellia rhizosphere soils. In conclusion, tree genotypes and growth stages shaped microbial communities in Camellia rhizosphere soils, and some plant growth-promoting rhizobacteria were identified as preliminary candidates for improving Camellia plantation growth.