Potato late blight is a severe and highly epidemic disease caused by Phytophthora infestans that can affect all parts of the plant. This study mainly screened antagonistic strains for good control of potato late blight and identified strain SDTB038 as Bacillus velezensis according to its morphological and chemical properties and the 16S rRNA, gyrA, and gyrB gene sequences. This antagonistic strain achieved good control of potato late blight in greenhouses and fields and promoted potato plant growth. Two-year field trials (2018 and 2019) showed that B. velezensis SDTB038 can be used to reduce food losses caused by late blight, achieving late blight reductions of 40.79% (2018) and 37.67% (2019). In two-year field trials, the control effects of the highest concentrations of fluopimomide and B. velezensis SDTB038 were better than those of the other treatments. The control effect of 85 g ha⁻¹ fluopimomide and B. velezensis SDTB038 and that of 170 g ha⁻¹ fluopimomide alone showed no significant differences. These field results indicate that a low concentration of fungicide and a high concentration of SDTB038 can be effective in controlling potato late blight. Foliar detection showed that lipopeptides have an inhibitory effect on P. infestans. The amplification of lipopeptide genes revealed surfactin (srfAB and srfAC) and fengycin (fenB) genes in SDTB038, but only surfactin production by B. velezensis SDTB038 was observed by ultra-high-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry analysis. Therefore, the strain B. velezensis SDTB038 can produce secondary metabolites that help potato plants resist late blight development, can effectively inhibit the infection of potato leaves by P. infestans, and has potential value for development as a biological pesticide against potato late blight.

Silkworm Bombyx mori (L.) (Lepidoptera: Bombycidae) is a critical insect for silk producers, but the inappropriate application of insecticides negatively affects the physiology and behavior of silkworms. This study found that the effects of neonicotinoid insecticides applied using two spraying methods on the growth and development of silkworms were different: the median lethal concentration (LC₅₀) values of two pesticides applied using the leaf-dipping method were 0.33 and 0.83 mg L⁻¹ and those of two pesticides applied using the quantitative spraying method were 0.91 and 1.23 mg kg⁻¹. The concentration of pesticides on the mulberry leaves did not decrease after their application using the quantitative spraying method, and a uniform spraying density was observed after the mulberry leaves were air-dried (no liquid) under realistic conditions. We then treated silkworms with the quantitative spraying method and leaf-dipping method. The treatment of silkworm larvae with imidacloprid and thiamethoxam at sublethal concentrations significantly prolonged the development time and significantly decreased the weight and pupation rate, as well as economic indicators of enamel layers and sputum production. Thiamethoxam treatment significantly increased the activities of carboxylesterase (CarE) and glutathione-S-transferase (GST). The activity of CarE and GST increased, decreased, and then increased, and the highest activity was detected on the 10th and 12th days. Thiamethoxam exposure significantly elevated the transcription levels of CarE-11, GSTe3 and GSTz2 and induced DNA damage in hemocytes. This study confirmed that the quantitative spray method is more stable than the leaf-dipping method. Moreover, imidacloprid and thiamethoxam treatment affected the economy and indexes of silkworms and induced changes in detoxification enzymes and DNA damage in silkworms. These results provide a basis for understanding the mechanism of the sublethal effects of insecticides on silkworms.

The external appearance of strawberry fruits serves as a critical criterion for their commercial value and grading standards. However, current research primarily emphasizes ripeness and surface defects, with limited attention given to the quantitative analysis of geometric characteristics such as deformity and symmetry. To address this gap, this study proposes a comprehensive evaluation framework that integrates deep learning-based segmentation with geometric analysis for strawberry appearance quality assessment. First, an enhanced YOLOv11 segmentation model incorporating a Squeeze-and-Excitation attention mechanism was developed to enable high-precision extraction of individual fruits, achieving Precision, Recall, AP₅₀, and F1 scores of 91.11%, 87.46%, 92.90%, and 88.45%, respectively. Second, a deformity quantification method was designed based on the number of deformity points (N_d), deformity rate (R_d), and spatial distance metrics (G_min and G_max). Experimental results demonstrated significant differences in R_d and G_max between deformed and normal strawberries, indicating strong classification capability. Finally, principal component analysis (PCA) was employed to extract the primary axis direction, and morphological symmetry was quantitatively evaluated using Intersection over Union (IoU) and Area Difference Ratio (AreaD_Ratio). The results revealed that most samples fell within an IoU range of 0.6–0.8 and AreaD_Ratio below 0.4, indicating noticeable inter-individual differences in fruit symmetry. This study aims to establish a three-stage analytical framework—segmentation, deformity quantification, and symmetry evaluation—for assessing strawberry appearance quality, with the goal of supporting key applications in automated grading and precision quality inspection.

Blue honeysuckle (Lonicera caerulea L.) is a perennial plant of the Caprifoliaceae family and Lonicera genus, the largest genus in the plant kingdom. Between September 2021 and September 2022, a le...