scholarly journals An updated global COI barcode reference data set for Fall Armyworm (Spodoptera frugiperda) and first record of this species in Bhutan

2020 ◽  
Author(s):  
Kiran Mahat ◽  
Andrew Mitchell ◽  
Tshelthrim Zangpo
Keyword(s):  
Spodoptera Frugiperda ◽  
Reference Data ◽  
Dna Barcode ◽  
Fall Armyworm ◽  
First Record ◽  
Molecular Techniques ◽  
Data Sets ◽  
Pest Species ◽  
Maize Crop ◽  
Data Set

AbstractWe report the first detection of Fall Armyworm (FAW), Spodoptera frugiperda (Smith, 1797), in Bhutan. FAW feeds on more than 300 plant species and is a serious pest of many. It has been spreading through Africa since 2016 and Asia since 2018. In Bhutan, this species was first detected in maize fields in the western part of the country in September 2019 and subsequently found infesting maize crop in southern parts of the country in December 2019 and April 2020. Using morphological and molecular techniques the presence of the first invading populations of S. frugiperda in Bhutan is confirmed through this study. We present an updated reference DNA barcode data set for FAW comprising 374 sequences, which can be used to reliably identify this serious pest species, and discuss some of the reasons why such compiled reference data sets are necessary, despite the publicly availability of the underlying data. We also report on a second armyworm species, the Northern Armyworm, Mythimna separata (Walker, 1865), in rice, maize and other crops in eighteen districts of Bhutan.

scholarly journals A system dynamics model for pests and natural enemies interactions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bonoukpoè Mawuko Sokame ◽  
Henri E. Z. Tonnang ◽  
Sevgan Subramanian ◽  
Anani Y. Bruce ◽  
Thomas Dubois ◽  
...  
Keyword(s):  
System Dynamics ◽  
Spodoptera Frugiperda ◽  
Busseola Fusca ◽  
Fall Armyworm ◽  
Sesamia Calamistis ◽  
System Thinking ◽  
Pest Species ◽  
Causal Loop Diagram ◽  
System Dynamics Model ◽  
Dynamics Model

AbstractStemborers (Busseola fusca, Sesamia calamistis and Chilo partellus), the fall armyworm (Spodoptera frugiperda) and associated parasitoids constitute an interacting system in maize fields in Kenya. This work aims at developing and evaluating models that represent the evolution of those interactions by applying system thinking and system dynamics approaches with its archetypes [causal loop diagram (CLD), reinforcing (R) and balancing (B)] to analyse the population of these multi-species systems. The software Vensim PLE 8.0.9 was used to implement the models and carry out the simulations of single- and multi-species systems. The results showed that when a single pest species with its associated parasitoids interact with the host plant, the species was able to establish and sustain by cyclical relationship between populations of the pest and the associated parasitoids. However, in multi- pest species systems, dominance of S. frugiperda and C. partellus over B. fusca and S. calamistis was observed, but without extinction. However, there was a likelihood for B. fusca being displaced by C. partellus. Overall, the models predict the co-existence of fall armyworm with stemborer species as an additional pest of maize in Africa that need to be considered henceforth in designing IPM strategies in maize.

scholarly journals First record of a parasitoid, Megaselia (M) scalaris (Diptera: Phoridae) of fall armyworm, Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) from India

2021 ◽  
Vol 31 (1) ◽  
Author(s):  
Sharanabasappa S. Deshmukh ◽  
S. Kiran ◽  
Atanu Naskar ◽  
Palam Pradeep ◽  
C. M. Kalleshwaraswamy ◽  
...  
Keyword(s):  
Outer Surface ◽  
Spodoptera Frugiperda ◽  
Fall Armyworm ◽  
First Record ◽  
Instar Larva ◽  
Major Threat ◽  
Megaselia Scalaris ◽  
Maize Cultivation ◽  
First Time ◽  
Lepidoptera Noctuidae

AbstractThe fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae), has become a major threat in maize cultivation since its invasion to India in 2018. The humpbacked fly, Megaselia scalaris (Loew) (Diptera: Phoridae), was recorded as a laboratory parasitoid of FAW, for the first time in India. Initially, 30–40 maggots of M. (M) scalaris emerged out from the dead pre-pupa and pupa of laboratory-reared FAW. The fly laid up to 15 eggs on the outer surface of 6th instar larva or pre-pupa of the FAW. The incubation period was 1–2 days. The fly had 3 larval instars which lasted 3–4 days and a pupal period of 10–11 days. The adults survived for 6–7 days.

First Record of the Fall Armyworm, Spodoptera frugiperda (J.E. Smith, 1797) (Lepidoptera: Noctuidae), in Rwanda

2018 ◽  
Vol 26 (1) ◽  
pp. 244-246 ◽  
Author(s):  
B. Uzayisenga ◽  
B. Waweru ◽  
J. Kajuga ◽  
P. Karangwa ◽  
B. Uwumukiza ◽  
...  
Keyword(s):  
Spodoptera Frugiperda ◽  
Fall Armyworm ◽  
First Record ◽  
Lepidoptera Noctuidae

scholarly journals Insecticidal activity of essential oils in controlling fall armyworm, Spodoptera frugiperda

2019 ◽  
Vol 86 ◽  
Author(s):  
Marcelo Negrini ◽  
Elisangela Gomes Fidelis ◽  
Daniel Augusto Schurt ◽  
Francisco dos Santos Silva ◽  
Rosely Souza Pereira ◽  
...  
Keyword(s):  
Chemical Analysis ◽  
Essential Oils ◽  
Topical Application ◽  
Spodoptera Frugiperda ◽  
Management Strategies ◽  
Fall Armyworm ◽  
Maize Crop ◽  
Insect Rearing ◽  
Corymbia Citriodora ◽  
Implementation Management

ABSTRACT: Fall armyworm, Spodoptera frugiperda (Smith) (Lepidoptera: Noctuidae) is one of the main pests in maize crop with developing resistance to chemical products and Bt technology. Therefore, alternative control methods such as essential oils are important steps in the implementation management strategies for this pest. This study aimed to evaluate the efficiency of essential oils (EOs) of Corymbia citriodora, Myrciaria dubia (Myrtaceae), Lippia microphylla (Verbenaceae) and Piper umbelattum (Piperaceae) in controlling S. frugiperda. The OEs were extracted and mortality tests were conducted with topic and volatile applications, in 30 second-instar caterpillars originated from insect rearing and artificial diet. As a control, we conducted tests with distilled water and acetone. EOs that provided mortality rates above 80% were submitted to chemical analysis for constituent identification. The efficient EOs were only those of C. citriodora and L. microphylla. For EO of C. citriodora, the LD80 was 7.06 ± 0.73 mg.g-1 in topical application and 5.85 ± 0.75 µL via volatile application. On the other hand, for EO of L. microphylla, DL80 was 9.95 ± 1.25 mg.g-1 in topical application and 18.56 ± 3.55 µL via volatile application. Chemical analysis showed that the main constituents were citronella for the EO of C. citriodora and (E)-caryophyllene and (E)-nerolidol to the EO of L. microphylla. EOs of C. citriodora and L. microphylla are promising for controlling S. frugiperda, with emphasis on the volatile effect of C. citriodora oil.

scholarly journals Influence of Adjacent and Border Crops on the Incidence of Fall Armyworm Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) in Maize

2021 ◽  
Author(s):  
P.S. Shanmugam ◽  
M. Sangeetha ◽  
P. Ayyadurai ◽  
Y.G. Prasad
Keyword(s):  
Spodoptera Frugiperda ◽  
Plant Protection ◽  
Management Strategies ◽  
Fall Armyworm ◽  
Cost Ratio ◽  
Cropping Pattern ◽  
Present Survey ◽  
Maize Crop ◽  
Benefit Cost Ratio ◽  
Benefit Cost

Background: Maize is one of the predominant millets cultivated in an area of 6500 ha both under drip and open irrigation systems in Dharmapuri district. The infestation of invasive insect pest Spodoptera frugiperda poses major threat to maize cultivation and increased the cost towards plant protection since 2018. In the integrated pest management strategies, the benefits of growing border and inter crop has been studied in detail but least emphasis was given to the crops grown in adjacent fields to the main crop. The cropping pattern in Dharmapuri district is highly diversified and the farmers prefer to grow more number of crops across the seasons compared to other maize growing areas. Methods: The present survey envisages the influence of adjacent and border crops on the incidence of fall armyworm in maize. The field incidence of fall armyworm in maize crop surrounded by other crops such as tapioca, nerium, cotton and maize fields with blackgram, cowpea and sesame as border crops were studied during kharif season of 2018 and 2019. Result: The maize fields surrounded by tapioca and nerium crop recorded lower fall armyworm incidence (3.00 - 10.00%) followed by field surrounded by tapioca on either side of maize (4.50 - 14.50%) during 15 to 60 days after emergence. Growing of border crops such as blackgram, sesame and cowpea recorded 24.50, 23.50 and 16.50% incidence at 60 DAE, respectively. With regard to grain yield, no marked variation was observed in different crop combination. The higher return (Rs. 86040/ha) and benefit cost ratio (2.65) was observed in maize crop adjacent to tapioca and nerium crop. The lower net return (Rs. 75360/ha) and benefit cost ratio (2.36) was realized in maize crop adjacent to maize crop. In most of the management strategies pulses have been inducted either border or intercrop to attract natural enemies and thwart the host insects. In the present survey, tapioca and nerium crop combination reduces the fall armyworm incidence. Hence tapioca and nerium crop combinations can be tried as border crop to push the fall armyworm away from the maize crop. The days required for advanced planting and crop combinations should be studied in detail to devise effective fall armyworm management strategies.

scholarly journals Influence of Control Points Configuration on the Mobile Laser Scanning Accuracy

2021 ◽  
Vol 906 (1) ◽  
pp. 012091
Author(s):  
Petr Kalvoda ◽  
Jakub Nosek ◽  
Petra Kalvodova
Keyword(s):  
Reference Point ◽  
Point Cloud ◽  
Laser Scanning ◽  
Reference Data ◽  
Data Sets ◽  
Control Points ◽  
Mobile Mapping ◽  
Data Set ◽  
Accuracy Test ◽  
Data Subset

Abstract Mobile mapping systems (MMS) are becoming widely used in standard geodetic tasks more commonly in the last years. The paper is focused on the influence of control points (CPs) number and configuration on mobile laser scanning accuracy. The mobile laser scanning (MLS) data was acquired by MMS RIEGL VMX-450. The resulting point cloud was compared with two different reference data sets. The first reference data set consisted of a high-accuracy test point field (TPF) measured by a Trimble R8s GNSS system and a Trimble S8 HP total station. The second reference data set was a point cloud from terrestrial laser scanning (TLS) using two Faro Focus3D X 130 laser scanners. The coordinates of both reference data sets were determined with significantly higher accuracy than the coordinates of the tested MLS point cloud. The accuracy testing is based on coordinate differences between the reference data set and the tested MLS point cloud. There is a minimum number of 6–7 CPs in our scanned area (based on MLS trajectory length) to achieve the declared relative accuracy of trajectory positioning according to the RIEGL datasheet. We tested two types of ground control point (GCP) configurations for 7 GCPs, using TPF reference data. The first type is a trajectory-based CPs configuration, and the second is a geometry-based CPs configuration. The accuracy differences of the MLS point clouds with trajectory-based CPs configuration and geometry-based CPs configuration are not statistically significant. From a practical perspective, a geometry-based CPs configuration is more advantageous in the nonlinear type of urban area such as our one. The following analyzes are performed on geometry-based CPs configuration variants. We tested the influence of changing the location of two CPs from ground to roof. The effect of the vertical configuration of the CPs on the accuracy of the tested MLS point cloud has not been demonstrated. The effect of the number of control points on the accuracy of the MLS point cloud was also tested. In the overall statistics using TPF, the accuracy increases significantly with increasing the number of GCPs up to 6. This number corresponds to a requirement of the manufacturer. Although further increasing the number of CPs does not significantly increase the global accuracy, local accuracy improves with increasing the number of CPs up to 10 (average spacing 50 m) according to the comparison with the TLS reference point cloud. The accuracy test of the MLS point cloud was divided into the horizontal accuracy test on the façade data subset and the vertical accuracy test on the road data subset using the TLS reference point cloud. The results of this paper can help improve the efficiency and accuracy of the mobile mapping process in geodetic praxis.

scholarly journals Voxel-wise and spatial modelling of binary lesion masks: A review and comparison of methods

2021 ◽  
Author(s):  
Petya Kindalova ◽  
Ioannis Kosmidis ◽  
Thomas E. Nichols
Keyword(s):  
Maximum Likelihood ◽  
Spatial Dependence ◽  
Reference Data ◽  
Spatial Modelling ◽  
Maximum Likelihood Estimates ◽  
Data Sets ◽  
Computationally Efficient ◽  
Data Set ◽  
Lesion Mapping ◽  
Modelling Approach

AbstractObjectivesWhite matter lesions are a very common finding on MRI in older adults and their presence increases the risk of stroke and dementia. Accurate and computationally efficient modelling methods are necessary to map the association of lesion incidence with risk factors, such as hypertension. However, there is no consensus in the brain mapping literature whether a voxel-wise modelling approach is better for binary lesion data than a more computationally intensive spatial modelling approach that accounts for voxel dependence.MethodsWe review three regression approaches for modelling binary lesion masks including massunivariate probit regression modelling with either maximum likelihood estimates, or mean bias-reduced estimates, and spatial Bayesian modelling, where the regression coefficients have a conditional autoregressive model prior to account for local spatial dependence. We design a novel simulation framework of artificial lesion maps to compare the three alternative lesion mapping methods. The age effect on lesion probability estimated from a reference data set (13,680 individuals from the UK Biobank) is used to simulate a realistic voxel-wise distribution of lesions across age. To mimic the real features of lesion masks, we suggest matching brain lesion summaries (total lesion volume, average lesion size and lesion count) across the reference data set and the simulated data sets. Thus, we allow for a fair comparison between the modelling approaches, under a realistic simulation setting.ResultsOur findings suggest that bias-reduced estimates for voxel-wise binary-response generalized linear models (GLMs) overcome the drawbacks of infinite and biased maximum likelihood estimates and scale well for large data sets because voxel-wise estimation can be performed in parallel across voxels. Contrary to the assumption of spatial dependence being key in lesion mapping, our results show that voxel-wise bias-reduction and spatial modelling result in largely similar estimates.ConclusionBias-reduced estimates for voxel-wise GLMs are not only accurate but also computationally efficient, which will become increasingly important as more biobank-scale neuroimaging data sets become available.

scholarly journals Integrated pest management of fall armyworm infestations in maize fields in Nepal: A review

2020 ◽  
Vol 5 (4) ◽  
pp. 583-591
Author(s):  
Sushil Khatri ◽  
Prakash Pakuwal ◽  
Saugat Khanal
Keyword(s):  
Spodoptera Frugiperda ◽  
Total Yield ◽  
Research Work ◽  
Fall Armyworm ◽  
Early Warning Systems ◽  
Climatic Conditions ◽  
Warning Systems ◽  
Maize Crop ◽  
Mountainous Regions ◽  
The People

Spodoptera frugiperda, commonly known as Fall Armyworm (FAW), is amongst the most terrifying pests of maize in Latin America, which unexpectedly appeared in Nepal in 2019 and spread expeditiously. Estimates of maize crop losses due to this pest are vital in order to compare the effect of these losses with the convenient of controlling FAW and suggest pertinent controlling technology and methods. Nepal is predominantly an agrarian nation thus, maize is grown substantially. However, climatic conditions of Nepal favor the outbreaks of pests such as FAW in many maize grown areas. On the grounds that most of the people of hill and mountainous regions depend on maize for their staple food, pests have appeared to be a great threat to cereal production. It causes   considerable   injuries   to   maize   by   feeding   on   leaf whorls, ears and tassel which often leads to total yield loss.  Yet, agriculture is an economic activity, even among subsistence farmers in Nepal. Seeing high potential losses caused by FAW, different control methods have been proposed. This pest demands meticulous and stepwise plan for its management. This review emphasized on adoption of IPM methods of pests’ control, which is the integration of biological, cultural, physical, chemical, and technological approaches. Meanwhile, early warning systems, though poorly developed in Nepal, can be highlighted for further studies and for further research work.

Sign in / Sign up

Export Citation Format

Share Document