scholarly journals Pest detection dogs for wood boring longhorn beetles

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Charlotte Holmstad Arnesen ◽  
Frank Rosell

AbstractInvasive alien species are increasing due to globalization. Their spread has resulted in global economic losses. Asian [Anoplophora glabripennis (Motschulsky)] (ALB) and citrus [A. chinensis (Forster)] (CLB) longhorn beetles are two introduced wood borers which contribute to these economic losses e.g. the destruction of tree plantations. Early detection is key to reduce the ecological influence alongside the detrimental and expensive eradication. Dogs (Canis lupus familiaris) can detect these insects, potentially at an early stage. We trained two privately owned dogs to investigate their use as detection tools. We tested the dog’s ability to discriminate ALB and CLB from native wood borers by carrying out double-blind and randomized experiments in three search conditions; (1) laboratory, (2) semi-field and (3) standardized field. For condition one, a mean sensitivity of 80%, specificity of 95% and accuracy of 92% were achieved. For condition two and three, a mean sensitivity of 88% and 95%, specificity of 94% and 92% and accuracy of 92% and 93% were achieved. We conclude that dogs can detect all types of traces and remains of ALB and CLB and discriminate them from native wood borers and uninfested wood, but further tests on live insects should be initiated.

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ze Peng ◽  
Yanhong He ◽  
Saroj Parajuli ◽  
Qian You ◽  
Weining Wang ◽  
...  

AbstractDowny mildew (DM), caused by obligate parasitic oomycetes, is a destructive disease for a wide range of crops worldwide. Recent outbreaks of impatiens downy mildew (IDM) in many countries have caused huge economic losses. A system to reveal plant–pathogen interactions in the early stage of infection and quickly assess resistance/susceptibility of plants to DM is desired. In this study, we established an early and rapid system to achieve these goals using impatiens as a model. Thirty-two cultivars of Impatiens walleriana and I. hawkeri were evaluated for their responses to IDM at cotyledon, first/second pair of true leaf, and mature plant stages. All I. walleriana cultivars were highly susceptible to IDM. While all I. hawkeri cultivars were resistant to IDM starting at the first true leaf stage, many (14/16) were susceptible to IDM at the cotyledon stage. Two cultivars showed resistance even at the cotyledon stage. Histological characterization showed that the resistance mechanism of the I. hawkeri cultivars resembles that in grapevine and type II resistance in sunflower. By integrating full-length transcriptome sequencing (Iso-Seq) and RNA-Seq, we constructed the first reference transcriptome for Impatiens comprised of 48,758 sequences with an N50 length of 2060 bp. Comparative transcriptome and qRT-PCR analyses revealed strong candidate genes for IDM resistance, including three resistance genes orthologous to the sunflower gene RGC203, a potential candidate associated with DM resistance. Our approach of integrating early disease-resistance phenotyping, histological characterization, and transcriptome analysis lay a solid foundation to improve DM resistance in impatiens and may provide a model for other crops.


2021 ◽  
Vol 13 (10) ◽  
pp. 1975
Author(s):  
Lin Wang ◽  
Yuzhen Zhou ◽  
Qiao Hu ◽  
Zhenghong Tang ◽  
Yufeng Ge ◽  
...  

Woody plant encroachment into grasslands ecosystems causes significantly ecological destruction and economic losses. Effective and efficient management largely benefits from accurate and timely detection of encroaching species at an early development stage. Recent advances in unmanned aircraft systems (UAS) enabled easier access to ultra-high spatial resolution images at a centimeter level, together with the latest machine learning based image segmentation algorithms, making it possible to detect small-sized individuals of target species at early development stage and identify them when mixed with other species. However, few studies have investigated the optimal practical spatial resolution of early encroaching species detection. Hence, we investigated the performance of four popular semantic segmentation algorithms (decision tree, DT; random forest, RF; AlexNet; and ResNet) on a multi-species forest classification case with UAS-collected RGB images in original and down-sampled coarser spatial resolutions. The objective of this study was to explore the optimal segmentation algorithm and spatial resolution for eastern redcedar (Juniperus virginiana, ERC) early detection and its classification within a multi-species forest context. To be specific, firstly, we implemented and compared the performance of the four semantic segmentation algorithms with images in the original spatial resolution (0.694 cm). The highest overall accuracy was 0.918 achieved by ResNet with a mean interaction over union at 85.0%. Secondly, we evaluated the performance of ResNet algorithm with images in down-sampled spatial resolutions (1 cm to 5 cm with 0.5 cm interval). When applied on the down-sampled images, ERC segmentation performance decreased with decreasing spatial resolution, especially for those images coarser than 3 cm spatial resolution. The UAS together with the state-of-the-art semantic segmentation algorithms provides a promising tool for early-stage detection and localization of ERC and the development of effective management strategies for mixed-species forest management.


2018 ◽  
Vol 14 (1) ◽  
pp. 66-73 ◽  
Author(s):  
Maarten A. de Jong ◽  
Sergei I. Petrykiv ◽  
Gozewijn D. Laverman ◽  
Antonius E. van Herwaarden ◽  
Dick de Zeeuw ◽  
...  

Background and objectivesThe sodium glucose cotransporter 2 (SGLT-2) inhibitor dapagliflozin is a novel drug for the treatment of diabetes mellitus. Recent studies suggest that SGLT-2 inhibitors affect phosphate homeostasis, but their effects on phosphate-regulating hormones in patients with diabetic kidney disease are still unclear.Design, setting, participants, & measurementsWe performed a post-hoc analysis of a double-blind, randomized, crossover trial in patients with type 2 diabetes with early-stage diabetic kidney disease on stable renin–angiotensin–aldosterone system blockade, with an albumin-to-creatinine ratio between 100 and 3500 mg/g, eGFR≥45 ml/min per 1.73 m2, and glycosylated hemoglobin≥7.2% and <11.4%. Patients were randomized to dapagliflozin 10 mg/d or placebo during consecutive 6-week study periods, separated by a 6-week wash-out. We investigated effects on circulating phosphate, calcium, parathyroid hormone (PTH), fibroblast growth factor 23 (FGF23), 25-hydroxyvitamin D (25[OH]D), and 1,25-dihydroxyvitamin D (1,25[OH]2D) levels.ResultsThirty-one patients (age 62 years; 23% female) were analyzed. Compared with placebo, dapagliflozin increased serum phosphate by 9% (95% confidence interval, 4% to 15%; P=0.002), PTH increased by 16% (3% to 30%; P=0.01), FGF23 increased by 19% (0.3% to 42%; P=0.05), and serum 1,25(OH)2D decreased by −12% (−25% to 4%; P=0.12). Calcium and 25(OH)D were unaffected. We found no correlation between changes in markers of phosphate homeostasis and changes in eGFR or 24-hour albumin excretion during dapagliflozin treatment.ConclusionsDapagliflozin increases serum phosphate, plasma PTH, and FGF23. This effect was independent of concomitant changes in eGFR or 24-hour albumin excretion.


2022 ◽  
Vol 12 ◽  
Author(s):  
Fei Xia ◽  
Xiaojun Xie ◽  
Zongqin Wang ◽  
Shichao Jin ◽  
Ke Yan ◽  
...  

Plants are often attacked by various pathogens during their growth, which may cause environmental pollution, food shortages, or economic losses in a certain area. Integration of high throughput phenomics data and computer vision (CV) provides a great opportunity to realize plant disease diagnosis in the early stage and uncover the subtype or stage patterns in the disease progression. In this study, we proposed a novel computational framework for plant disease identification and subtype discovery through a deep-embedding image-clustering strategy, Weighted Distance Metric and the t-stochastic neighbor embedding algorithm (WDM-tSNE). To verify the effectiveness, we applied our method on four public datasets of images. The results demonstrated that the newly developed tool is capable of identifying the plant disease and further uncover the underlying subtypes associated with pathogenic resistance. In summary, the current framework provides great clustering performance for the root or leave images of diseased plants with pronounced disease spots or symptoms.


2020 ◽  
Vol 35 (1) ◽  
pp. 40-49
Author(s):  
Qian Zhuang ◽  
Siyu Zhu ◽  
Xue Yang ◽  
Xinqi Zhou ◽  
Xiaolei Xu ◽  
...  

Background: Feedback evaluation of actions and error response detection are critical for optimizing behavioral adaptation. Oxytocin can facilitate learning following social feedback but whether its effects vary as a function of feedback valence remains unclear. Aims: The present study aimed to investigate whether oxytocin would influence responses to positive and negative feedback differentially or equivalently. Methods: The present study employed a randomized, double-blind, placebo controlled within-subject design to investigate whether intranasal oxytocin (24 IU) influenced behavioral and evoked electrophysiological potential responses to positive or negative feedback in a probabilistic learning task. Results: Results showed that oxytocin facilitated learning and this effect was maintained in the absence of feedback. Using novel stimulus pairings, we found that oxytocin abolished bias towards learning more from negative feedback under placebo by increasing accuracy for positively reinforced stimuli. Oxytocin also decreased the feedback-related negativity difference (negative minus positive feedback) during learning, further suggesting that it rendered the evaluation of positive and negative feedback more equivalent. Additionally, post-learning oxytocin attenuated error-related negativity amplitudes but increased the late error positivity, suggesting that it may lower conflict detection between actual errors and expected correct responses at an early stage of processing but at a later stage increase error awareness and motivation for avoiding them. Conclusions: Oxytocin facilitates learning and subsequent performance by rendering the impact of positive relative to negative feedback more equivalent and also by reducing conflict detection and increasing error awareness, which may be beneficial for behavioral adaption.


Micromachines ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 532 ◽  
Author(s):  
Jinjin Shen ◽  
Ting Zhou ◽  
Ru Huang

Pathogenic bacterial contamination greatly threats human health and safety. Rapidly biosensing pathogens in the early stage of infection would be helpful to choose the correct drug treatment, prevent transmission of pathogens, as well as decrease mortality and economic losses. Traditional techniques, such as polymerase chain reaction and enzyme-linked immunosorbent assay, are accurate and effective, but are greatly limited because they are complex and time-consuming. Electrochemiluminescence (ECL) biosensors combine the advantages of both electrochemical and photoluminescence analysis and are suitable for high sensitivity and simple pathogenic bacteria detection. In this review, we summarize recent advances in ECL sensors for pathogenic bacteria detection and highlight the development of paper-based ECL platforms in point of care diagnosis of pathogens.


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