The fall armyworm strain associated with most rice, millet, and pasture infestations in the Western Hemisphere is rare or absent in Ghana and Togo

Open Access Journal; Published online: 21 June 2021The moth pest fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is now present throughout much of the Eastern Hemisphere where it poses a significant economic threat to a number of crops. Native to the Western Hemisphere, fall armyworm is one of the primary pests of corn in the Americas and periodically causes significant economic damage to sorghum, millet, cotton, rice, and forage grasses. This broad host range is in part the result of two populations historically designated as host strains (C-strain and R-strain) that differ in their host plant preferences. Reports of infestations in Africa have to date mostly been limited to the C-strain preferred crops of corn and sorghum, with little evidence of an R-strain presence. However, this could reflect a bias in monitoring intensity, with the R-strain perhaps being more prevalent in other crop systems that have not been as routinely examined for the pest. Because knowledge of whether and to what extent both strains are present is critical to assessments of crops at immediate risk, we analyzed specimens obtained from a systematic survey of pasture grass and rice fields, habitats typically preferred by the R-strain, done contemporaneously with collections from corn fields in Ghana and Togo. Substantial larval infestations were only observed in corn, while pheromone trap capture numbers were high only in corn and rice habitats. Little to no fall armyworm were found in the pasture setting. Comparisons with a meta-analysis of studies from South America identified differences in the pattern of strain-specific markers typically found in fall armyworm collected from rice habitats between the two hemispheres. Genetic tests of specimens from rice and corn area traps failed to show evidence of differential mating between strains. These results are consistent with the R-strain being rare or even absent in Africa and, at least for the Ghana-Togo area, this R-strain lack does not appear to be due to limitations in pest monitoring. The implications of these results to the crops at risk in Africa and the accuracy of existing molecular markers of strain identity are discussed

Natural enemies of the fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) in Ghana

Open Access JournalThe fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), is an invasive insect pest attacking maize in Ghana and sub-Saharan Africa countries. Biological control will need to be an important management strategy, and a first step was to identify potential natural enemies. Sampling was conducted in different localities of the 10 regions of Ghana from May to Nov 2017. A total of 1,062 larvae were collected from 106 maize farms, and the presence of natural enemies was recorded in 18 (17.0%) farms. Among natural enemies recorded, 7 species were parasitoids: Chelonus bifoveolatus Szpligeti, Coccygidium luteum (Brull), Cotesia icipe Fernandez, Meteoridea testacea (Granger), and Bracon sp. (all Hymenoptera: Braconidae), Anatrichus erinaceus Loew (Diptera: Chloropidae), and an undetermined tachinid fly (Diptera: Tachinidae). The parasitism rate was 3.58%. Three predator species were collected: Pheidole megacephala (F.) (Hymenoptera: Formicidae), Haematochares obscuripennis Stål, and Peprius nodulipes (Signoret) (both Heteroptera: Reduviidae). The 2 most abundant parasitoids were C. bifoveolatus and C. luteum with a relative abundance of 29.0% and 23.7%, respectively, and a parasitism rate of 1.04% and 0.85%, respectively. However, C. bifoveolatus was the most dispersed parasitoid, found in 6.6% of the inspected sites within all the agroecological zones of Ghana. This species is a good candidate as a biological control agent for fall armyworm in Africa. The predator that was most abundant (46.0%) and dispersed (3.8% of the farms) was P. megacephala. El cogollero, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), es una plaga de insectos invasora que ataca el maíz en Ghana y los países de África subsahariana. El control biológico deberá ser una estrategia de manejo importante, y un primer paso es identificar los enemigos naturales potenciales. Se realizó el muestreo en diferentes localidades de las 10 regiones de Ghana desde mayo hasta noviembre del 2017. Se recolectó un total de 1.062 larvas de 106 granjas de maíz, y se registró la presencia de enemigos naturales en 18 granjas (17.0%). Entre los enemigos naturales registrados, 7 especies fueron parasitoides: Chelonus bifoveolatus Szpligeti, Coccygidium luteum (Brull), Cotesia icipe Fernandez, Meteoridea testacea (Granger) y Bracon sp. (todos los Hymenoptera: Braconidae), Anatrichus erinaceus Loew (Diptera: Chloropidae) y una mosca taquinida indeterminada (Diptera: Tachinidae). La tasa de parasitismo fue del 3.58%. Se recolectaron tres especies de depredadores: Pheidole megacephala (F.) (Hymenoptera: Formicidae), Haematochares obscuripennis Stål y Peprius nodulipes (Signoret) (ambos Heteroptera: Reduviidae). Los 2 parasitoides más abundantes fueron C. bifoveolatus y C. luteum con una abundancia relativa del 29.0% y 23.7%, respectivamente, y una tasa de parasitismo del 1.04% y 0.85%, respectivamente. Sin embargo, C. bifoveotus fue el parasitoide más disperso, encontrado en el 6.6% de los sitios inspeccionados dentro de todas las zonas agroecológicas de Ghana. Esta especie es un buen candidato como agente de control biológico para el cogollero en África. El depredador que fue más abundante (46.0%) y disperso (3.8% de las granjas) fue P. megacephala

Genetic studies of fall armyworm indicate a new introduction into Africa and identify limits to its migratory behavior

Open Access Journal; Published online: 04 Feb 2022The fall armyworm, Spodoptera frugiperda (J.E. Smith) is native to the Americas and a major pest of corn and several other crops of economic importance. The species has characteristics that make it of particular concern as an invasive pest, including broad host range, long-distance migration behavior, and a propensity for field-evolved pesticide resistance. The discovery of fall armyworm in western Africa in 2016 was followed by what was apparently a remarkably rapid spread throughout sub-Saharan Africa by 2018, causing economic damage estimated in the tens of billions USD and threatening the food security of the continent. Understanding the history of the fall armyworm invasion of Africa and the genetic composition of the African populations is critical to assessing the risk posed to different crop types, the development of effective mitigation strategies, and to make Africa less vulnerable to future invasions of migratory moth pests. This paper tested and expanded on previous studies by combining data from 22 sub-Saharan nations during the period from 2016 to 2019. The results support initial descriptions of the fall armyworm invasion, including the near absence of the strain that prefers rice, millet, and pasture grasses, while providing additional evidence that the magnitude and extent of FAW natural migration on the continent is more limited than expected. The results also show that a second entry of fall armyworm likely occurred in western Africa from a source different than that of the original introduction. These findings indicate that western Africa continues to be at high risk of future introductions of FAW, which could complicate mitigation efforts

Harnessing data science to improve integrated management of invasive pest species across Africa: an application to Fall armyworm (Spodoptera frugiperda) (J.E. Smith) (Lepidoptera: Noctuidae)

Open Access Journal; Published online: 11 Feb 2022After five years of its first report on the African continent, Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) is considered a major threat to maize, sorghum, and millet production in sub-Saharan Africa. Despite the rigorous work already conducted to reduce FAW prevalence, the dynamics and invasion mechanisms of FAW in Africa are still poorly understood. This study applied interdisciplinary tools, analytics, and algorithms on a FAW dataset with a spatial lens to provide insights and project the intensity of FAW infestation across Africa. The data collected between January 2018 and December 2020 in selected locations were matched with the monthly average data of the climatic and environmental variables. The multilevel analytics aimed to identify the key factors that influence the dynamics of spatial and temporal pest density and occurrence at a 2 km x 2 km grid resolution. The seasonal variations of the identified factors and dynamics were used to calibrate rule-based analytics employed to simulate the monthly densities and occurrence of the FAW for the years 2018, 2019, and 2020. Three FAW density level classes were inferred, i.e., low (0–10 FAW moth per trap), moderate (11–30 FAW moth per trap), and high (>30 FAW moth per trap). Results show that monthly density projections were sensitive to the type of FAW host vegetation and the seasonal variability of climatic factors. Moreover, the diversity in the climate patterns and cropping systems across the African sub-regions are considered the main drivers of FAW abundance and variation. An optimum overall accuracy of 53% was obtained across the three years and at a continental scale, however, a gradual increase in prediction accuracy was observed among the years, with 2020 predictions providing accuracies greater than 70%. Apart from the low amount of data in 2018 and 2019, the average level of accuracy obtained could also be explained by the non-inclusion of data related to certain key factors such as the influence of natural enemies (predators, parasitoids, and pathogens) into the analysis. Further detailed data on the occurrence and efficiency of FAW natural enemies in the region may help to complete the tri-trophic interactions between the host plants, pests, and beneficial organisms. Nevertheless, the tool developed in this study provides a framework for field monitoring of FAW in Africa that may be a basis for a future decision support system (DSS)