Background Fall armyworm, Spodoptera frugiperda (J.E. Smith) threatens staple crops across Africa. Integrating entomopathogenic fungi into Integrated Pest Management (IPM) offers a sustainable alternative to sole reliance on insecticides. This study quantified the pathogenicity of Purpureocillium lilacinum and Clonostachys rosea against S. frugiperda under controlled conditions. Methods Second-fifth instar larvae and eggs were exposed to 1 × 10 7 , 1 × 10 8 , and 1 × 10 9 conidia mL -1 of each fungus; sterile water served as control. Mortality was recorded over 3–9 days after treatment (DAT); feeding reduction was measured gravimetrically. Larval mortality was analyzed with GLMs/GLMMs (binomial-probit); feeding reduction by ANOVA/Tukey; LD50 and LT50 were estimated from dose-response models. Results Larval mortality was significantly affected by concentration × time interaction and declined with advancing larval stage. Peak larval mortality was reached at a concentration of 1 × 10 9 conidia mL -1 at 9 DAT. Feeding consumption reduction was significantly affected by larval instar, EPF species, and instar × concentration. Feeding reduction reached 60−74% in early instars at the highest dose. Egg mortality was primarily concentration-dependent with maximum values (up to 82% and 88% for P. lilacinum and C. rosea , respectively) at the dose of 1 × 10 9 conidia mL -1 highest dose. Our findings supported the study hypothesis that efficacy of entomopathogenic fungi against S. frugiperda is primarily driven by interaction of spore concentration and exposure time across the host developmental stages, rather than the interaction of fungal species. The consistent susceptibility of early instars and the strong concentration-dependent responses highlight the functional potential of these native fungi as biologically relevant components of sustainable IPM strategies. Conclusions Native P. lilacinum and C. rosea display dose‑, stage‑, and time‑dependent pathogenicity and feeding suppression against S. frugiperda . These species are promising candidates for IPM; field validation and formulation optimization are the next steps.
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Mussa et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69ba429c4e9516ffd37a2fbd — DOI: https://doi.org/10.1371/journal.pone.0334730
Abel Jonathan Mussa
Sija Kabota
Joseph Oswald Ruboha
PLoS ONE
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