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Simple Summary: In this study, we tackled an important issue in modern farming: predicting plant pests and diseases more effectively. Traditional methods are slow and often incorrect. To improve this, we created a new method that combines two advanced techniques, named gene expression programming (GEP) and support vector machines (SVM). Think of it as creating a smart program that can learn from past pest attacks to better predict future ones. We tested our new method with data on wheat pests from Shaanxi Province, recorded from 1933 to 2010. By comparing our method to other traditional ones, we found that ours was more accurate, with a success rate of about 91% in capturing pest attacks. This means our method can help farmers understand and prepare for pest and disease threats more efficiently, saving time and resources. Our work is a step forward in making farming smarter and more prepared for challenges, which is great news for ensuring our food supplies are secure and sustainable. This study addresses the challenges in plant pest and disease prediction within the context of smart agriculture, highlighting the need for efficient data processing techniques. In response to the limitations of existing models, which are characterized by slow training speeds and a low prediction accuracy, we introduce an innovative prediction method that integrates gene expression programming (GEP) with support vector machines (SVM). Our approach, the gene expression programming—support vector machine (GEP-SVM) model, begins with encoding and fitness function determination, progressing through cycles of selection, crossover, mutation, and the application of a convergence criterion. This method uniquely employs individual gene values as parameters for SVM, optimizing them through a grid search technique to refine genetic parameters. We tested this model using historical data on wheat blossom midges in Shaanxi Province, spanning from 1933 to 2010, and compared its performance against traditional methods, such as GEP, SVM, naive Bayes, K-nearest neighbor, and BP neural networks. Our findings reveal that the GEP-SVM model achieves a leading back-generation accuracy rate of 90.83%, demonstrating superior generalization and fitting capabilities. These results not only enhance the computational efficiency of pest and disease prediction in agriculture but also provide a scientific foundation for future predictive endeavors, contributing significantly to the optimization of agricultural production strategies. [ABSTRACT FROM AUTHOR]

Simple Summary: Ophraella communa Lesage is a specific biological control agent of the invasive weed Ambrosia artemisiifolia L. Understanding the molecular mechanism by which O. communa recognizes A. artemisiifolia will help improve its bio-control effect. Odorant-binding proteins (OBPs) play a vital role in insect olfactory perception. In this study, the sequence and expression characteristics of OcomOBP7 were analyzed. We obtained the pure protein of OcomOBP7 by prokaryotic expression and purification, and its binding characteristics were analyzed using a fluorescence competitive binding assay. Finally, we verified the function of OcomOBP7 in vivo using RNAi combined with an electroantennography (EAG) assay. The results showed that the binding ability of OcomOBP7 was broad-spectrum and was involved in the host plant localization of O. communa. The olfactory system plays a key role in various insect behaviors, and odorant-binding proteins participate in the first step of the olfactory process. Ophraella communa Lesage is an oligophagous phytophagous insect that is a specific biological control agent for Ambrosia artemisiifolia L. The leaf beetle must identify and locate A. artemisiifolia through olfaction; however, its odorant-binding protein (OBP) function has not yet been reported. In this study, OcomOBP7 was cloned, and its tissue expression profile and binding ability were analyzed using RT-qPCR and fluorescence binding assays, respectively. Sequence analysis demonstrated that OcomOBP7 belongs to the classical OBP family. The RT-qPCR results showed that OcomOBP7 was specifically expressed in the antennae, indicating that OcomOBP7 may be involved in chemical communication. The fluorescence binding assay showed that OcomOBP7 has an extensive binding ability to alkenes. The electroantennography experiments showed that O. communa antennal response to α-pinene and ocimene decreased significantly after interference because the two odors specifically bound to OcomOBP7. In summary, α-pinene and ocimene are odorant ligands corresponding to OcomOBP7, indicating that OcomOBP7 is involved in the chemical recognition of A. artemisiifolia. Our study lays a theoretical foundation for research into O. communa attractants, which is helpful for the better biological control of A. artemisiifolia by O. communa. [ABSTRACT FROM AUTHOR]

Simple Summary: The bright red color of Erythraeid mites is conspicuous. The Erythraeid larvae are usually ectoparasitic on arthropods and easily observed. Both the genera Charletonia and Leptus are distributed worldwide. Charletonia has 86 species and Leptus has more than 240 species based on larvae, respectively. To date, two species of the genus Charletonia and 11 species of the genus Leptus have been reported from China. Here, four new species, Charletonia rectangia Xu and Jin sp. nov. collected from tropical rainforests in the Guangxi Province and Yunnan Province, Leptus (Leptus) bomiensis Xu and Jin sp. nov. from the Tibet Autonomous Region, where the altitude ranges from 2673 to 3374 m, Leptus (Leptus) longisolenidionus Xu and Jin sp. nov. from jungles in the Hainan Province (Hainan Island), and Leptus (Leptus) striatus Xu and Jin sp. nov. from Xishuangbanna tropical rainforests in the Yunnan Province. We believe that this study will contribute to further research on the taxonomy and phylogeny of the family. Four new species, Charletonia rectangia Xu and Jin sp. nov., Leptus (Leptus) bomiensis Xu and Jin sp. nov., Leptus (Leptus) longisolenidionus Xu and Jin sp. nov., and Leptus (Leptus) striatus Xu and Jin sp. nov. are described and illustrated based on larvae. All four new species are from biodiversity hotspots, L. (L.) bomiensissp. nov. from the Eastern Himalayas biodiversity hotspot, while the other three species from the Indo–Burma biodiversity hotspot. [ABSTRACT FROM AUTHOR]

Simple Summary: Erythraeid mite members are large, larvae usually parasitize other arthropods, whereas the nymphs and adults are free-living predators of a small insect. Free-living adults/nymphs and parasitic larvae vary greatly in morphology, and classification is usually treated independently. To date, more than 850 species of erythraeid mites have been recorded. Among them, more than 580 species were described only as larvae. Eatoniana Cambridge, 1898 is a small genus within Erythraeidae comprising, 10 valid species worldwide, three species of which were only reported based on larvae. Erythraeus Latreille, 1806 includes 123 species distributed worldwide, with 69 species reported based on larvae alone. Here, two new species, Eatoniana nanlingensis Xu and Jin sp. nov. from Guangdong Province and Erythraeus (Erythraeus) kunyuensis Xu and Jin sp. nov. from Shandong Province, are described based on larval stage. We believe that the study will contribute to further studies on the taxonomy and phylogeny of Erythraeidae. The species Eatoniana yangshuonicus (Haitlinger) comb. nov. is transferred from the genus Erythraeus to Eatoniana based on the basifemoral setal formula 2-2-1. Two new species, Eatoniana nanlingensis Xu and Jin sp. nov. and Erythraeus (Erythraeus) kunyuensis Xu and Jin sp. nov. are described and illustrated based on larvae. Eatoniana nanlingensis sp. nov. from the Oriental region (Guangdong Province), Er. (Er.) kunyuensis sp. nov. from the Palaearctic region (Shandong Province). An updated key to larval species of the genus Eatoniana of the world is presented. [ABSTRACT FROM AUTHOR]

Simple Summary: Leaf beetle Ophraella communa is considered an effective biocontrol agent against the common ragweed Ambrosia artemisiifolia. However, there are no studies that assess the antennal sensilla and chemosensory proteins expression profiles of O. communa. In this study, the types and morphology of sensilla on the antennae were examined by scanning electron microscopy (SEM). The results showed that there are six types of sensilla (sensilla trichodea, sensilla chaetica, sensilla basiconica, sensilla styloconica, sensilla coeloconica, and Böhm bristles) distributed on the antennae. We also found that the expression levels of five chemosensory proteins in male and female antennae were higher than those in other tissues by quantitative real-time polymerase chain reaction. Our results lay the foundation for interpreting the olfactory functions of adult O. communa. Ophraella communa is an efficient biocontrol agent used against the invasive weed Ambrosia artemisiifolia. It is an herbivorous insect that feeds on specific plants; the olfactory functions of this insects plays an important role in their search for host plants. There are no reports on O. communa sensilla types, morphology, or chemosensory protein (CSP) genes. In this study, we observed the external structure and distribution of antennal sensilla in adult O. communa antennae by scanning electron microscopy; moreover, we cloned 11 CSPs (CSP1–CSP11) and elucidated their tissue-expression profiles using quantitative real-time polymerase chain reaction. Six types of sensilla were identified: sensilla trichodea (including two subtypes), sensilla chaetica, sensilla basiconica (including two subtypes), sensilla styloconica, sensilla coeloconica, and Böhm bristles. Both male and female antennae had all six types of sensilla, and no sexual dimorphism was noted in sensillar types or distribution. We also found that the expression levels of CSP2, CSP3, CSP4, CSP6, and CSP7 in male and female antennae were higher than those in other tissues, which suggests that these five CSPs may be related to olfactory function in O. communa. Ultimately, our results lay the foundation for interpreting the olfactory functions of adult O. communa. [ABSTRACT FROM AUTHOR]