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Red imported fire ants : attacking everything
\"In this book, readers learn about the invasive fire ant\"-- Provided by publisher.
Book
DDT and the American century : global health, environmental politics, and the pesticide that changed the world
Praised for its ability to kill insects effectively and cheaply and reviled as an ecological hazard, DDT continues to engender passion across the political spectrum as one of the world's most controversial chemical pesticides. In DDT and the American Century, David Kinkela chronicles the use of DDT around the world from 1941 to the present with a particular focus on the United States, which has played a critical role in encouraging the global use of the pesticide. Kinkela's study offers a unique approach to understanding both this contentious chemical and modern environmentalism in an international context.
eBook
Ecologically controlling insect and mite pests of tea plants with microbial pesticides: a review
Insect and mite pests are damaging stressors that are threatening the cultivation of tea plants, which result in enormous crop loss. Over the years, the effectiveness of synthetic pesticides has allowed for its prominent application as a control strategy. However, the adverse effects of synthetic pesticides in terms of pesticide residue, environmental contamination and insect pest resistance have necessitated the need for alternative strategies. Meanwhile, microbial pesticides have been applied to tackle the damaging activities of the insect and mite pests of tea plants, and their performances were scientifically adjudged appreciable and environmental friendly. Herein, entomopathogenic microbes that were effective against tea geometrid (Ectropis obliqua Prout), tea green leafhopper (Empoasca onukii Matsuda), paraguay tea ampul (Gyropsylla spegazziniana), tea mosquito bug (Helopeltis theivora Waterhouse) and red spider mite (Oligonychus coffea Nietner) have been reviewed. The current findings revealed that microbial pesticides were effective and showed promising performances against these pests. Overall, this review has provided the basic and integrative information on the integrated pest management (IPM) tool(s) that can be utilized towards successful control of the aforementioned insect and mite pests.Graphic abstract
Journal Article
Coffee pests, diseases and their management
Price collapse and oversupply have made coffee a high-profile crop in recent years: never has efficient production and crop protection been more important for reducing costs and increasing quality. Packed with illustrations, this book covers the origins, botany, agroecology and worldwide production statistics of coffee, and the insect pests, plant pathogens, nematodes and nutrient deficiencies that afflict it. With emphasis on integrated crop management, this book reviews control measures suitable for any coffee pest or disease and will enable agriculturists to design and implement sustainable pest management systems.
eBook
Sterile Insect Technique (SIT) and Its Applications
Although most insect species have a beneficial role in the ecosystems, some of them represent major plant pests and disease vectors for livestock and humans. During the last six–seven decades, the sterile insect technique (SIT) has been used as part of area-wide integrated pest management strategies to suppress, contain, locally eradicate or prevent the (re)invasion of insect pest populations and disease vectors worldwide. This Special Issue on “Sterile insect technique (SIT) and its applications”, which consists of 27 manuscripts (7 reviews and 20 original research articles), provides an update on the research and development efforts in this area. The manuscripts report on all the different components of the SIT package including mass-rearing, development of genetic sexing strains, irradiation, quality control as well as field trials.
Journal Article
Genomic content of chemosensory genes correlates with host range in wood-boring beetles (Dendroctonus ponderosae, Agrilus planipennis, and Anoplophora glabripennis)
Background
Olfaction and gustation underlie behaviors that are crucial for insect fitness, such as host and mate selection. The detection of semiochemicals is mediated via proteins from large and rapidly evolving chemosensory gene families; however, the links between a species’ ecology and the diversification of these genes remain poorly understood. Hence, we annotated the chemosensory genes from genomes of select wood-boring coleopterans, and compared the gene repertoires from stenophagous species with those from polyphagous species.
Results
We annotated 86 odorant receptors (ORs), 60 gustatory receptors (GRs), 57 ionotropic receptors (IRs), 4 sensory neuron membrane proteins (SNMPs), 36 odorant binding proteins (OBPs), and 11 chemosensory proteins (CSPs) in the mountain pine beetle (
Dendroctonus ponderosae
), and 47 ORs, 30 GRs, 31 IRs, 4 SNMPs, 12 OBPs, and 14 CSPs in the emerald ash borer (
Agrilus planipennis
). Four SNMPs and 17 CSPs were annotated in the polyphagous wood-borer
Anoplophora glabripennis.
The gene repertoires in the stenophagous
D. ponderosae
and
A. planipennis
are reduced compared with those in the polyphagous
A. glabripennis
and
T. castaneum
, which is largely manifested through small gene lineage expansions and entire lineage losses. Alternative splicing of GR genes was limited in
D. ponderosae
and apparently absent in
A. planipennis
, which also seems to have lost one carbon dioxide receptor (GR1).
A. planipennis
has two SNMPs, which are related to SNMP3 in
T. castaneum. D. ponderosae
has two alternatively spliced OBP genes, a novel OBP “tetramer”, and as many as eleven IR75 members
.
Simple orthology was generally rare in beetles; however, we found one clade with orthologues of putative bitter-taste GRs (named the “GR215 clade”), and conservation of IR60a from
Drosophila melanogaster.
Conclusions
Our genome annotations represent important quantitative and qualitative improvements of the original datasets derived from transcriptomes of
D. ponderosae
and
A. planipennis
, facilitating evolutionary analysis of chemosensory genes in the Coleoptera where only a few genomes were previously annotated. Our analysis suggests a correlation between chemosensory gene content and host specificity in beetles. Future studies should include additional species to consolidate this correlation, and functionally characterize identified proteins as an important step towards improved control of these pests.
Journal Article
Transgenic microRNA‐14 rice shows high resistance to rice stem borer
Summary Rice stem borer (RSB, Chilo suppressalis) is an insect pest that causes huge economic losses every year. Control efforts rely heavily on chemical insecticides, which leads to serious problems such as insecticide resistance, environment pollution, and food safety issues. Therefore, developing alternative pest control methods is an important task. Here, we identified an insect‐specific microRNA, miR‐14, in RSB, which was predicted to target Spook (Spo) and Ecdysone receptor (EcR) in the ecdysone signalling network. In‐vitro dual luciferase assays using HEK293T cells confirmed the interactions of Csu‐miR‐14 with CsSpo and with CsEcR. Csu‐miR‐14 exhibited high levels of expression at the end of each larval instar stage, and its expression was negatively correlated with the expression of its two target genes. Overexpression of Csu‐miR‐14 at the third day of the fifth instar stage led to high mortality and developmental defects in RSB individuals. We produced 35 rice transformants to express miR‐14 and found that three lines had a single copy with highly abundant miR‐14 mature transcripts. Feeding bioassays using both T0 and T1 generations of transgenic miR‐14 rice indicated that at least one line (C#24) showed high resistance to RSB. These results indicated that the approach of miRNAs as targets has potential for improving pest control methods. Moreover, using insect‐specific miRNAs rather than protein‐encoding genes for pest control may prove benign to non‐insect species, and thus is worthy of further exploration.
Journal Article
Recommending Advanced Deep Learning Models for Efficient Insect Pest Detection
Insect pest management is one of the main ways to improve the crop yield and quality in agriculture and it can accurately and timely detect insect pests, which is of great significance to agricultural production. In the past, most insect pest detection tasks relied on the experience of agricutural experts, which is time-consuming, laborious and subjective. In rencent years, various intelligent methods have emerged for detection. This paper employs three frontier Deep Convolutional Neural Network (DCNN) models—Faster-RCNN, Mask-RCNN and Yolov5, for efficient insect pest detection. In addition, we made two coco datasets by ourselves on the basis of Baidu AI insect detection dataset and IP102 dataset, and compared these three frontier deep learning models on the two coco datasets. In terms of Baidu AI insect detection dataset whose background is simple, the experimental results strongly recommend Yolov5 for the insect pest detection, because its accuracy reaches above 99% while Faster-RCNN’s and Mask-RCNN’s reach above 98%. Meanwhile, Yolov5 has the faster computational speed than Faster-RCNN and Mask-RCNN. Comparatively speaking, with regard to the IP102 dataset whose background is complex and categories are abundant, Faster-RCNN and Mask-RCNN have the higher accuracy, reaching 99%, than Yolov5 whose accuracy is about 97%.
Journal Article
Crop insect pest detection based on dilated multi-scale attention U-Net
Background
Crop pests seriously affect the yield and quality of crops. Accurately and rapidly detecting and segmenting insect pests in crop leaves is a premise for effectively controlling insect pests.
Methods
Aiming at the detection problem of irregular multi-scale insect pests in the field, a dilated multi-scale attention U-Net (DMSAU-Net) model is constructed for crop insect pest detection. In its encoder, dilated Inception is designed to replace the convolution layer in U-Net to extract the multi-scale features of insect pest images. An attention module is added to its decoder to focus on the edge of the insect pest image.
Results
The experiments on the crop insect pest image IP102 dataset are implemented, and achieved the detection accuracy of 92.16% and IoU of 91.2%, which is 3.3% and 1.5% higher than that of MSR-RCNN, respectively.
Conclusion
The results indicate that the proposed method is effective as a new insect pest detection method. The dilated Inception can improve the accuracy of the model, and the attention module can reduce the noise generated by upsampling and accelerate model convergence. It can be concluded that the proposed method can be applied to practical crop insect pest monitoring system.
Journal Article
Insect Pest Image Recognition: A Few-Shot Machine Learning Approach including Maturity Stages Classification
Recognizing insect pests using images is an important and challenging research issue. A correct species classification will help choosing a more proper mitigation strategy regarding crop management, but designing an automated solution is also difficult due to the high similarity between species at similar maturity stages. This research proposes a solution to this problem using a few-shot learning approach. First, a novel insect data set based on curated images from IP102 is presented. The IP-FSL data set is composed of 97 classes of adult insect images, and 45 classes of early stages, totalling 6817 images. Second, a few-shot prototypical network is proposed based on a comparison with other state-of-art models and further divergence analysis. Experiments were conducted separating the adult classes and the early stages into different groups. The best results achieved an accuracy of 86.33% for the adults, and 87.91% for early stages, both using a Kullback–Leibler divergence measure. These results are promising regarding a crop scenario where the more significant pests are few and it is important to detect them at earlier stages. Further research directions would be in evaluating a similar approach in particular crop ecosystems, and testing cross-domains.
Journal Article