磷化铝间歇熏蒸防治鱼粉螨类的研究

本研究介绍了饲料鱼粉螨类的有效防治方法．采用11．5g／m2的磷化铝片剂，分两次间歇熏蒸大量孳生螨类和昆虫的棉纱布袋和编织袋包装的鱼粉，达到了有效杀灭鱼粉中大量孳生的粉尘螨、跗蠊螨、齿蠊螨、河野脂螨、食根嗜木螨、马六甲肉食螨、转开肉食螨、特氏肉食螨等8种螨类和烟草甲、白腹皮蠹、拟白腹皮蠹、赤颈郭公虫、赤足郭公虫、黑菌虫的效果。     

Resistance to bifenthrin and resistance mechanisms of different strains of the two-spotted spider mite (Tetranychus urticae) from Turkey

Nine different strains of the two-spotted spider miteTetranychus urticae Koch (Acari: Tetranychidae) were collected on cotton from Adana, Antalya, Izmir, Manisa and Urfa in Turkey. Their responses to bifenthrin were investigated using conventional bioassay and biochemical assays. LC₅₀ and LC₉₀ values of bifenthrin were determined for all strains by using a residual bioassay with a petri dish-spray tower. Resistance ratios were determined by comparing the samples with a standard susceptible strain, GSS. The resistance ratios of the strains ranged from <1 to 669-fold (at LC₅₀). Of the investigated field strains, only three (two from Adana and one from Urfa) were resistant to bifenthrin. There was a correlation between esterase enzyme activity and bifenthrin resistance according to polyacrylamide gel electrophoresis and microtiter plate assays in the three resistant strains. http://www.phytoparasitica.org posting May 17, 2005.     

便携式柑橘虫害实时检测系统的研制与试验

为实现柑橘虫害的快速、准确识别,帮助果农及时掌握果园内虫害的危害程度和分布情况,该研究结合嵌入式图像处理技术设计了一套基于深度卷积神经网络的柑橘虫害实时检测系统。优选MoblieNet作为虫害图像特征提取网络,区域候选网络生成害虫的初步位置候选框,快速区域卷积神经网络(Faster Region Convolutional Neural Networks,Faster R-CNN)实现候选框的分类和定位。检测系统根据目标图像中虫害数量计算危害程度,按照正常、轻度、中度、重度4个等级判定柑橘虫害的严重程度,形成虫害识别与级别定量化测评软件。最后引入北斗模块获取采样点位置信息,进一步处理成可视化的虫害热力图。结果表明,该方法可实现对柑橘红蜘蛛和蚜虫的快速准确检测,识别准确率分别达到91.0%和89.0%,单帧图像平均处理速度低至286ms。该系统实现了柑橘虫害的精准识别与定位,可为农药喷洒作业提供精准信息服务。     

基于K-means聚类的柑橘红蜘蛛图像目标识别

为快速检测红蜘蛛虫害,该研究采用基于Lab颜色模型中a(红/绿)、b(黄/蓝)层信息的K-means聚类法识别彩色图像中的红蜘蛛。试验选取8幅具有不同清晰度的柑橘红蜘蛛图像,采用基于Sobel边缘检测算子的评价函数计算图像清晰度评价值以评价图像清晰度,对比采用灰度法和包含2、3、4或5个聚类中心的K-means聚类法的目标识别效果和识别效率。结果表明,灰度法对8幅图像中红蜘蛛目标识别率平均值为29%,误判率平均值为201%,无法应用于复杂背景图像中的红蜘蛛目标识别。包含5个聚类中心的K-means聚类法对清晰度较高的图像识别率为100%,误判率为0,对清晰度较低的图像识别率为88%,误判率为0;当图像尺寸较小时,包含4个聚类中心的K-means聚类法识别效率与灰度法相当;当图像尺寸较大时,重复计算聚类中心导致识别耗时较长;基于Lab颜色空间的识别算法无法有效识别其他颜色的红蜘蛛,继续研究的方向为引入红蜘蛛形态信息以提高识别准确率和优化聚类中心的选取以降低识别耗时。     

Spatial patterns of the Citrus leprosis virus and its associated mite vector in systems without intervention

Leprosis is caused by the Citrus leprosis virus cytoplasmic type and is vectored by the mite Brevipalpus yothersi. Miticide applications, which cost $54 million annually, are based on inspection for the presence of mites. The aim of the present study was to characterize the spatial patterns of B. yothersi-infested trees and trees with leprosis symptoms for further improvement in sampling and disease control. The presence of mites and the occurrence of leprosis were assessed over two years in 1160 Valencia trees and 720 Natal trees in a commercial sweet orange grove in Sao Paulo State, Brazil. To assess the natural growth and dispersal of mites and leprosis, mite populations were not controlled during the experimental period. Maps of mite-infested trees and trees with leprosis symptoms were analysed at three different levels of spatial hierarchy using complementary methods, i.e. among adjacent trees within and across rows, within quadrats, and the strength and orientation of aggregation among quadrats. The study showed that the spatial patterns of virus-infected and mite-infested trees were different, with a strong aggregation pattern of trees with leprosis symptoms that increased over time. Conversely, the spatial pattern of B. yothersi showed randomness or weak aggregation at all three spatial hierarchical levels. Disease incidence increased steadily in plots of both cultivars, unlike in mite-infested trees where incidence fluctuated over time. These results have important implications for the development of better management strategies for leprosis. Sampling methods and action thresholds for mite control should consider primary disease inoculum in addition to the incidence of mites.     

钢板仓储粮害虫陷阱诱捕技术研究

采用ＧＪ８９型良虫陷阱检测器对钢板仓害虫物种分布组成及主要害虫书虱和螨类在不同储藏期各部位的分布进行了调查研究。结果表明：３～４月仓库昆虫物种组成简单,为书虱和长角谷盗两种,分别占捕获总虫量的９９．５％及０．５％;８月份仓库昆虫７种,主要种类是书虱和螨类,分别占捕儿总量的６１．９％和３８％,次要害虫种类有赤拟谷盗、长角谷盗、玉米象、谷蠹及花斑皮蠹。不同储藏期、不同粮层、不同方向害虫分布存在差异。调     

臭氧水防治草莓二斑叶螨的效果评价

臭氧水具有强氧化性,能有效杀灭环境中的病菌和害虫。本研究采用草莓上的二斑叶螨体表观察和田间防效试验评价了臭氧水对二斑叶螨的防治效果。试验结果显示,4.0-4.5 mg·L-1和1.0-1.5 mg·L-1的臭氧水均能够显著降低二斑叶螨的虫口密度,防效高达95.46%和91.28%,且显著提升二斑叶螨的死亡率,但臭氧水浓度过高会抑制草莓植株的生长,破坏草莓的叶片。通过对二斑叶螨体表的观察发现,利用臭氧水的强氧化性,有效破坏了二斑叶螨的体表组织,因此在二斑叶螨发生期连续使用臭氧水可以有效控制螨的为害。本研究综合防效和安全性评价表明,1.0-1.5 mg·L-1的臭氧水对二斑叶螨具有良好的防效,对草莓和授粉的蜜蜂也具有安全性,为二斑叶螨的防治提供了一种理想的方式,具有较高推广价值。     

Understanding the Enemy: A Review of the Genetics,Behavior and Chemical Ecology of Varroa destructor,the Parasitic Mite of Apis mellifera

Varroa destructor (Mesostigmata: Varroidae) is arguably the most damaging parasitic mite that attacks honey bees worldwide. Since its initial host switch from the Asian honey bee (Apis cerana) (Hymenoptera: Apidae) to the Western honey bee (Apis mellifera) (Hymenoptera: Apidae), Varroa has become a widely successful invasive species, attacking honey bees on almost every continent where apiculture is practiced. Two haplotypes of V. destructor (Japanese and Korean) parasitize A. mellifera, both of which vector various honey bee-associated viruses. As the population of Varroa grows within a colony in the spring and summer, so do the levels of viral infections. Not surprisingly, high Varroa parasitization impacts bees at the individual level, causing bees to exhibit lower weight, decreased learning capacity, and shorter lifespan. High levels of Varroa infestation can lead to colony-wide varroosis and eventually colony death, especially when no control measures are taken against the mites. Varroa has become a successful parasite of A. mellifera because of its ability to reproduce within both drone cells and worker cells, which allows populations to expand rapidly. Varroa uses several chemical cues to complete its life cycle, many of which remain understudied and should be further explored. Given the growing reports of pesticide resistance by Varroa in several countries, a better understanding of the mite’s basic biology is needed to find alternative pest management strategies. This review focuses on the genetics, behavior, and chemical ecology of V. destructor within A. mellifera colonies, and points to areas of research that should be exploited to better control this pervasive honey bee enemy.