Identification, behavior analysis, and control of snail pest in agricultural fields using signal analysis and nanoparticles

Abstract

Giant African snail has been considered as the most challenging and evolving pest all over the world. This Pest is recognized as one of the topmost 100 destructive species in the world. This Snail is an agricultural pest devours only vegetables, fruits and sometimes sand. It also disturbs the households. It has the capacity to transmit both human and plant pathogens. This snail feeds on the stem, leaves, and flower of the cauliflower. This paper gives the brief study of various behavior of Giant African snail in acoustic environment. The Signals of various behavior of snails are recorded and analyzed using a MATLAB 2019 software. The time domain specification and frequency domain specification of pest Snails are done. Eradication of snail from its habitat is the tedious process. The eradication of snail is quite simple when it is detected automatically. This paper also suggests the identification of snails automatically by its acoustic signals and uses Machine Learning algorithm for effective detection. Added to above, the addition of the 5% of AgNP nanoparticles eliminated the presence of Giant African snail in the agricultural fields.