Diapause disruption in Cirina butyrospermi Vuillet (Lepidoptera, Attacidae), the shea caterpillar, in Burkina Faso

The shea caterpillar Cirina butyrospermi is an important insect, highly valued as a human food item in Burkina Faso. However, its appearance is seasonal due to its univoltine cycle. This study therefore investigated the possibilities of breaking the nymphal diapause by changing the environmental factors and through the hormonal treatment of prepupae and pupae using bovine insulin and 20-hydroxyecdysone. Changes in humidity and temperature did not result in emergence, suggesting a mandatory nature of the diapause in C. butyrospermi. Injection of 20-hydroxyecdysone between 20 and 40 ng on 20 C. butyrospermi pupae resulted in 15.24 and 47.5% emergence, respectively. The incubation time varied between 40 and 38 days, respectively. No emergence was observed with the injection of bovine insulin. Dipping of C. butyrospermi larvae and pupae in solutions of 20-hydroxyecdysone resulted in similar rates of emergence between the two stages, with slight variations between individual doses: (1) for larvae, emergence was recorded at 10, 8, 5 and 15 mg/l with 98.5, 62.14, 25.73 and 24.16%, respectively; the incubation times varied from 39 days at 5 mg/l to 26 days at 20 mg/l; and (2) for pupae, emergence occurred between 5 and 20 mg/l, with the highest emergence rate recorded at 10, 8 and 15 mg/l with 94.58, 65.83 and 29.58%, respectively; the incubation times varied from 53 days for the lowest dose (5 mg/l) to 37 days (20 mg/l); the best emergence rate of 94.58% coincided with an incubation time of 43 days at 10 mg/l. No emergence was observed beyond 20 mg/l in both stages. Hormonal treatment with 20-hydroxyecdysone did not affect the fecundity of C. butyrospermi, with the fecundity of artificially emerging adults overlapping with that of naturally emerging adults. The emergence rate for both was similar. These results contribute to a better understanding of the physiology of this insect, constituting a breakthrough in its sustainable use as human food

Advances in crop insect modelling methods—Towards a whole system approach

A wide range of insects affect crop production and cause considerable yield losses. Difficulties reside on the development and adaptation of adequate strategies to predict insect pests for their timely management to ensure enhanced agricultural production. Several conceptual modelling frameworks have been proposed, and the choice of an approach depends largely on the objective of the model and the availability of data. This paper presents a summary of decades of advances in insect population dynamics, phenology models, distribution and risk mapping. Existing challenges on the modelling of insects are listed; followed by innovations in the field. New approaches include artificial neural networks, cellular automata (CA) coupled with fuzzy logic (FL), fractal, multi-fractal, percolation, synchronization and individual/agent based approaches. A concept for assessing climate change impacts and providing adaptation options for agricultural pest management independently of the United Nations Intergovernmental Panel on Climate Change (IPCC) emission scenarios is suggested. A framework for estimating losses and optimizing yields within crop production system is proposed and a summary on modelling the economic impact of pests control is presented. The assessment shows that the majority of known insect modelling approaches are not holistic; they only concentrate on a single component of the system, i.e. the pest, rather than the whole crop production system. We suggest system thinking as a possible approach for linking crop, pest, and environmental conditions to provide a more comprehensive assessment of agricultural crop production.Peer reviewe

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)

Invasiveness, biology, ecology, and management of the fall armyworm, Spodoptera frugiperda.

First online

Biopesticide based sustainable pest management for safer production of vegetable legumes and brassicas in Asia and Africa

Published online: 10 May 2019Vegetables are one of the important crops which could alleviate the poverty and malnutrition among the smallholder farmers in tropical Asia and Africa. However, a plethora of pests limit the productivity of these crops, leading to economic losses. Vegetable producers overwhelmingly rely on chemical pesticides in order to reduce pest‐caused economic losses. However, over‐reliance on chemical pesticides poses serious threats to human and environmental health. Hence, biopesticides offer a viable alternative to chemical pesticides in sustainable pest management programs. Baculoviruses such as nucleopolyhedrovirus (NPV) and granulovirus (GV) have been exploited as successful biological pesticides in agriculture, horticulture and forestry. Maruca vitrata multiple nucleocapsid NPV (MaviMNPV) was found to be a unique baculovirus specifically infecting pod borer on food legumes, and it has been successfully developed as a biopesticide in Asia and Africa. Entomopathogenic fungi also offer sustainable pest management options. Several strains of Metarhizium anisopliae and Beauveria bassiana have been tested and developed as biopesticides in Asia and Africa. This review specifically focuses on the discovery and development of entomopathogenic virus and fungi‐based biopesticides against major pests of vegetable legumes and brassicas in Asia and Africa