Meiqin Wang

Root-knot nematode (RKN) causes severe yield loss in cucumber. Understanding the interactions of biocontrol agent–soil microbiomes and RKNs is essential for enhancing the efficacy of biocontrol agents and nematicides to curb RKN damage to cucumber. The field experiment in this work was conducted to determine the ability of Bacillus velezensis GHt-q6 to colonize cucumber plants, investigate its effect on the control of RKNs, and assess its influence on soil microbiology in the inter-root zone of cucumber plants. After 10 days post-treatment (DPT), GHt-q6-Rif could stably colonize the roots (4.55 × 10⁴ cfu·g⁻¹), stems (3.60 × 10³ cfu·g⁻¹), and leaves (3.60 × 10² cfu·g⁻¹) of cucumber. The high-throughput sequencing results suggested that the bacterial community diversity increased at the late development phase (p > 0.05). The strain GHt-q6 increased the relative abundance of beneficial bacteria (Gemmatimonadaceae, Sphingomonadaceae, Pseudomonadaceae). Throughout the complete cucumber growth period, strain GHt-q6 significantly increased soil urease, sucrase, accessible potassium, and phosphorus (p < 0.05). However, strain GHt-q6 had a minimal effect on catalase activity. At the pulling stage, strain GHt-q6 exhibited 43.35% control effect on cucumber RKNs, which was 7.54% higher than that of Bacillus subtilis. The results highlighted the significant potential of the strain GHt-q6 to manage cucumber RKNs and improve soil microecology. Hence, the applications of B. velezensis GHt-q6 can enhance the nematicidal action to curb RKN infecting cucumber.

Plant diseases can inflict varying degrees of damage on agricultural production. Therefore, identifying a rapid, non-destructive early diagnostic method is crucial for safeguarding plants. Cladosporium fulvum (C. fulvum) is one of the major diseases in tomato growth. This work presents a method of data fusion using two hyperspectral imaging systems of visible/near-infrared (VIS/NIR) and near-infrared (NIR) spectroscopy for the early diagnosis of C. fulvum in greenhouse tomatoes. First, hyperspectral images of samples at health and different times of infection were collected. The average spectral data of the image regions of interest were extracted and preprocessed for subsequent spectral datasets. Then different classification models were established for VIS/NIR and NIR data, optimized through various variable selection and data fusion methods. The principal component analysis-radial basis function neural network (PCA-RBF) model established using low-level data fusion achieved optimal results, achieving accuracies of 100% and 99.3% for calibration and prediction, respectively. Moreover, both the macro-averaged F1 (Macro-F1) values reached 1, and the geometric mean (G-mean) values reached 1 and 1, respectively. The results indicated that it was feasible to establish a PCA-RBF model by using the hyperspectral technique with low-level data fusion for the early detection of C. fulvum in greenhouse tomatoes.

The present study provides a comprehensive overview of the Bacillus velezensis strain Htq6, and its potential applications in plant disease control. Htq6 is an endophytic bacterium derived from walnut, which was found to possess a strong inhibitory effect on a wide range of plant pathogenic microorganisms and was identified as a good plant disease control agent. The entire genome of the Bacillus velezensis Htq6 was sequenced, and a comparative genomic analysis was conducted with various Bacillus species in order to better understand the mechanism of the strain’s biological control. At the same time, a new classification result was presented. Additionally, transcriptome analysis was performed to explore the response mechanism of tomato gray mold fungus after treatment with the fermentation liquid of Bacillus velezensis Htq6. The study analyzed the distribution of various secondary metabolite gene clusters in the Bacillus model strains and employed RNA-Seq technology to obtain transcriptome expression profiles. Furthermore, the cell wall, cell membrane, and antioxidant-related genes of Botrytis cinerea were analyzed, providing insight into the antibacterial mechanism of biocontrol bacteria and the stress response mechanism of Botrytis cinerea. The results of the research are promising, and could potentially lead to the development of an effective biocontrol agent for the prevention and control of various plant diseases.