A screening of several Chinese medicinal herbs for nematicidal properties showed that Arisaema erubescens (Wall.) Schott tubers possessed significant nematicidal activity against the root-knot nematode (Meloidogyne incognita). From the ethanol extract, two nematicidal flavone-C-glycosides were isolated by bioassay-guided fractionation. The compounds were identified as schaftoside and isoschaftoside on the basis of their phytochemical and spectral data. Schaftoside and isoschaftoside possessed strong nematicidal activity against M. incognita (LC₅₀ = 114.66 μg/mL and 323.09 μg/mL, respectively) while the crude extract of A. erubescens exhibited nematicidal activity against the root-knot nematode with a LC₅₀ value of 258.11 μg/mL.

The rice weevil (Sitophilus oryzae) is a major pest in stored wheat, and traditional detection methods face challenges in identifying its hidden life stages within kernels. This study develops a nondestructive method to detect S. oryzae (Sitophilus oryzae) infestation in wheat kernels using hyperspectral imaging, spectral preprocessing, feature extraction, and classification modeling. Hyperspectral data were collected from wheat kernels at different infestation stages (1, 11, 21, and 25 days (d)) and from healthy kernels. Spectral quality was optimized using SG smoothing, multiplicative scatter correction (MSC), and standard normal variate transformation (SNV). Feature extraction algorithms, including Competitive Adaptive Re-weighting Algorithm (CARS), Successive Projection Algorithm (SPA), and Iterative Retention of Information Variables (IRIV), were used to reduce data dimensionality, while classification models like Decision Tree (DT), K-nearest neighbors (KNN), and Support Vector Machine (SVM) were applied. The results show that MSC preprocessing provides the best performance among the models. After feature band selection, the MSC-CARS-SVM model achieved the highest accuracy for the 1 day and 25 d samples (95.48% and 96.61%, respectively). For the 11 d and 21 d samples, the MSC-IRIV-SPA-SVM model achieved the best performance with accuracies of 94.35% and 94.92%, respectively. This study demonstrates that MSC effectively reduces spectral noise and improves classification performance. After feature selection, the model shows significant improvements in both accuracy and stability. The study confirms the feasibility of using hyperspectral technology to identify healthy and S. oryzae-infested wheat kernels, providing theoretical support for early, nondestructive pest detection.

Biological control by releasing a large number of parasitoids has been an effective strategy for coping with stored-product pest insects. Habrobracon hebetor (Say) (Hymenoptera: Braconidae) has strong control capabilities over Lepidoptera pests. Exploring the optimum storage temperature, life stage, and cold storage period of H. hebetor is of great importance for the utilization of parasitoids. In this context, the survival, parasitism, and fecundity of H. hebetor were evaluated after 10, 20, 30, 40, 50, and 60 d of exposure at −5, 0, 5, 10, and 15 °C for H. hebetor eggs, larvae, pupae, and adults, and the survival, parasitism, and fecundity of H. hebetor individuals that had been maintained at normal rearing condition were taken as a control. The cold exposure duration dramatically affected the development and survival of eggs, larvae, and pupae of H. hebetor, regardless of the temperatures tested. Habrobracon hebetor eggs, larvae, and pupae failed to develop into the next life stage at −5, 0, and 5 °C. Habrobracon hebetor eggs, larvae, pupae, and adults failed to survive after 10 d exposure at −5 and 0 °C. The parasitism rate, fecundity and oviposition duration of H. hebetor adults that originated from eggs, larvae, pupae, and adults after different cold storage durations markedly decreased with increasing cold storage duration. The highest parasitism rate of adults was 34.12% after exposure at 5 °C for 10 d, which was not significantly different from the control (31.86%). The maximum level of egg production of H. hebetor adults developed from initial larvae exposed at 15 °C for 10 d and 20 d were 344.67 and 340.67 eggs/female, respectively, which were not significantly different from the control (392.00 eggs/female). When H. hebetor larvae were stored at 15 °C for 10 and 60 d, the oviposition duration of newly emerged adults reached the maximum and minimum levels recorded, with 17.00 and 0.83 d, respectively. These results provide empirical support for the large-scale production and storage of H. hebetor.

Endosymbiotic bacteria are key factors that regulate the biological traits of Liposcelis bostrychophila. This study employed metagenomic methods to analyze the dominant species of symbiotic microorganisms associated with L. bostrychophila. By controlling the environmental temperature, we were able to manipulate the abundance of endosymbionts and establish populations with high, medium, and low levels of these bacteria. This allowed us to examine the fitness parameters of L. bostrychophila under different levels of endosymbiont abundance. The experimental results revealed that L. bostrychophila hosts 51 genera of symbiotic microorganisms, with Rickettsia being the dominant genus, accounting for 84.11% to 98.16% of the total share. Environmental temperature significantly affected the abundance of Rickettsia, with notable differences observed during the adult stage of L. bostrychophila. A temperature gradient of 28 °C, 35 °C, and 37 °C was established, allowing for the classification of populations based on Rickettsia abundance into three categories: high-abundance populations (LBhp), medium-abundance populations (LBmp), and low-abundance populations (LBlp). The abundance of Rickettsia had a significant impact on the fitness of L. bostrychophila. Specifically, a high abundance of Rickettsia contributed positively to population fitness by increasing egg production, prolonging egg hatching time, enhancing lifespan, and improving both survival and reproductive rates. Therefore, the endosymbiont Rickettsia plays a crucial role in the growth and development of L. bostrychophila. In the future, our research will help further uncover the interactions between Rickettsia and its host, providing new perspectives for pest control and offering a better understanding of insect biology and ecology.