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Published on: July 26, 2018
Monitoring and Behavioral Control of Lepidopteran Pests in Soybean: Evaluation of Food-Based Attractants, Trap
Vinicius Cesarin1, Sabrina Cesarin de Oliveira1, Allana Grecco Guedes2
1School of Agricultural and Veterinary Sciences, São Paulo State Univ (UNESP), Jaboticabal, Brazil.
Abstract:
Chemically mediated behavioral strategies, including semiochemicals and food-based attractants, have gained prominence in Integrated Pest Management (IPM) programs because of their potential for selective and environmentally friendly pest control. The objective of this study is to evaluate the use of food-based attractants and two trap models (delta-ajar and funnel-ball) for monitoring adult lepidopteran pests in soybean fields. Additionally, the field performance and selectivity of an attract-and-kill (attractant + insecticide) strategy were assessed. Field trials were conducted in commercial soybean areas in Jaboticabal, São Paulo state, Brazil. Results indicated that funnel-ball traps captured a significantly higher number of target moths (36.8 ± 4.3 moths/trap/month) than delta-ajar traps (17.4 ± 2.9 moths/trap/month). However, both models presented similar species richness. Temporal patterns of moth abundance varied along the crop cycle and Helicoverpa armigera and Chrysodeixis includens populations peaked during the reproductive stages of soybean. In contrast, Spodoptera frugiperda and Elasmopalpus lignosellus were more abundant during the early vegetative stages, particularly within the first 20 days after plant emergence. The attract-and-kill application was associated with significantly higher moth mortality than the untreated control, especially for C. includens and E. lignosellus, with mortality peaking at 40 days after trap installation. Importantly, mortality among non-target organisms was relatively low (< 2% of total mortality), and was mainly restricted to a limited number of families such as Dolichopodidae, and Tachinidae (Diptera). These findings underscore the relevance of adaptive, phenology-aware pest management strategies that incorporate semiochemical tools with minimal ecological disruptions.
