Plutella xylostella is a typical phototactic pest. LW-opsin contributes to the phototaxis of P. xylostella, but the expression changes of other genes in the phototransduction pathway caused by the mutation of LW-opsin remain unknown. In the study, the head transcriptomes of male G88 and LW-opsin mutants were compared. A GO-function annotation showed that DEGs mainly belonged to the categories of molecular functions, biological processes, and cell composition. Additionally, a KEGG-pathway analysis suggested that DEGs were significantly enriched in some classical pathways, such as the phototransduction-fly and vitamin digestion and absorption pathways. The mRNA expressions of genes in the phototransduction-fly pathway, such as Gq, ninaC, and rdgC were significantly up-regulated, and trp, trpl, inaD, cry1, ninaA and arr1 were significantly down-regulated. The expression trends of nine DEGs in the phototransduction pathway confirmed by a RT-qPCR were consistent with transcriptomic data. In addition, the influence of a cry1 mutation on the phototaxis of P. xylostella was examined, and the results showed that the male cry1 mutant exhibited higher phototactic rates to UV and blue lights than the male G88. Our results indicated that the LW-opsin mutation changed the expression of genes in the phototransduction pathway, and the mutation of cry1 enhanced the phototaxis of a P. xylostella male, providing a basis for further investigation on the phototransduction pathway in P. xylostella.

Bactrocera dorsalis (Hendel, 1912) is a highly destructive pest affecting fruits and vegetables, making population monitoring essential for farmers to implement timely control measures. In recent years, although automatic monitoring systems for B. dorsalis have been introduced, challenges such as limited accuracy, difficulty in accurately identifying the target pest using infrared interruption sensors alone, and high labor requirements persist. This study presents an automatic monitoring system consisting of intelligent bait equipment (IBE), an advanced detection model based on YOLOv8, and an online monitoring platform. The developed IBE is equipped with cameras, attractant-based lures, and an automatic removal mechanism for B. dorsalis. Field tests demonstrated the IBE exhibited an attractiveness to B. dorsalis comparable to conventional traps, achieved a near-perfect cleaning efficiency (~100%), and maintained a reliable wireless transmission system. The YOLOv8l-based automatic pest detection model outperformed other YOLOv8 variants (n, s, m, x), achieving the highest precision (95.17%), recall (94.15%) and F1 score (94.66%), underscoring its effectiveness in pest detection. Further analysis of the impact of B. dorsalis density on YOLOv8l’s detection performance revealed a decline in accuracy as density increased; however, even at high densities, the model maintained a strong F1 score of 93.36%, demonstrating robustness. Finally, the automatic pest detection model was integrated into ‘YunShanPu’, an online platform for real-time pest monitoring. The proposed method has demonstrated promising performance in the automatic identification and counting of B. dorsalis and has potential for monitoring B. dorsalis populations continuously, providing early warning and forecasting for integrated pest management.

Precise monitoring of Matsumurasca onukii is essential for data-driven integrated pest management (IPM), yet existing automated monitoring systems are often limited by unstable outdoor illumination, morphological degradation of trapped insects, and target occlusions, resulting in reduced detection accuracy. To address these challenges, an automated Internet of Things (IoT)-based tea pest monitoring system was developed through the coordinated design of an intelligent monitoring device and an enhanced detection model. The monitoring device employed an active mechanical decoupling mechanism to acquire images in a standardized optical chamber, while the detection model was designed to address detection difficulties associated with post-capture morphological degradation. In addition, a spatiotemporal correction procedure was introduced to improve counting reliability. Field trapping comparisons showed higher observed capture density for the IMD than for the standard and resized controls, with mean paired differences of 0.225 (95% CI, 0.109–0.380) and 0.275 (95% CI, 0.169–0.412) individuals/cm⁻², respectively, while RVBE-YOLO achieved an F1 score of 92.90%. Year-round deployment of three IMDs at one research site in 2025 showed close correspondence between system-generated and expert-derived daily counts (R² > 0.99; RMSE = 0.17–0.63) and captured clear seasonal variation in daily M. onukii trap captures. These results indicate that the proposed system can provide reliable and continuous records of M. onukii captures under the evaluated field conditions, supporting long-term automated pest monitoring in tea plantations.

Opsin plays a regulatory role in phototaxis of Diaphorina citri, functioning as the initial station in the phototransduction cascade. Our study aimed to explore the D. citri phototransduction pathway to identify elicitors that may enhance D. citri phototaxis in the future. The RNAi technique was employed to inhibit LW-opsin gene expression, followed by RNA-Seq analysis to identify phototransduction genes. Finally, RT-qPCR was performed to validate whether genes in the phototransduction pathway were affected by the inhibition of LW-opsin expression. A total of 87 genes were identified within the transcriptome as involved in phototransduction based on KEGG functional annotation. Of these, 71 genes were identified as enriched in the phototransduction-fly pathway. These genes encode key proteins in this process, including Gqα, Gqβ, Gqγ, phospholipase C β (PLCβ), the cation channel transient receptor potential (TRP), and TRP-like (TRPL), among others. Moreover, the LOC103513214 (Gqβ) and LOC103518375 (ninaC) genes exhibited reduced expression when LW-opsin gene expression was suppressed. Our results provide a basis for further investigation of phototransduction in D. citri.