Acoustic Detection ofRhynchophorus ferrugineus(Coleoptera: Dryophthoridae) andOryctes elegans(Coleoptera: Scarabaeidae) inPhoenix dactylifera(Arecales: Arecacae) Trees and Offshoots in Saudi Arabian Orchards

Abstract

Rhynchophorus ferrugineus (Olivier) (Coleoptera: Dryophthoridae) larvae are cryptic, internal tissue-feeding pests of palm trees that are difficult to detect; consequently, infestations may remain hidden until they are widespread in an orchard. Infested trees and propagable offshoots that develop from axillary buds on the trunk frequently are transported inadvertently to previously uninfested areas. Acoustic methods can be used for scouting and early detection of R. ferrugineus, but until now have not been tested on multiple trees and offshoots in commercial date palm orchard environments. For this report, the acoustic detectability of R. ferrugineus was assessed in Saudi Arabian date palm orchards in the presence of commonly occurring wind, bird noise, machinery noise, and nontarget insects. Signal analyses were developed to detect R. ferrugineus and another insect pest, Oryctes elegans Prell (Coleoptera: Scarabaeidae), frequently co-occurring in the orchards, and discriminate both from background noise. In addition, it was possible to distinguish R. ferrugineus from O. elegans in offshoots by differences in the temporal patterns of their sound impulses. As has been observed often with other insect pests, populations of the two species appeared clumped rather than uniform or random. The results are discussed in relation to development of automated methods that could assist orchard managers in quickly identifying infested trees and offshoots so that R. ferrugineus infestations can be targeted and the likelihood of transferring infested offshoots to uninfested areas can be reduced.

Acoustic Signal Applications in Detection and Management of Rhynchophorus spp. in Fruit-Crops and Ornamental Palms

“…The "typical" pattern of movement and feeding activity includes 0.1 to 0.3 s trains of short, 1 to 10 ms impulses with broadband spectra produced by weak contacts of larvae scraping or sliding along a tunnel, or by snapping of wood fibers during feeding (Mankin et al 2011). Such trains, hereafter termed bursts, have been reported previously in studies where larvae and adults of a variety of different insect species had been recovered after recording (Mankin et al 2011), including palmetto weevil (Dosunmu et al 2014), red palm weevil (Jalinas et al 2015(Jalinas et al , 2017, and Oryctes elegans Prell (Coleoptera: Scarabaeidae), with or without red palm weevil recovered from the same tree (Mankin et al 2016a). In contrast to the commonly observed pattern, each 0.2 to 0.3 s squeal in Figure 1 begins with descending bands of 2 or more loud harmonics, which then are followed by the more typical trains (bursts) of short impulses with broadband spectra.…”

“…The finding that red palm weevil larval movement can produce 2 distinctively different sounds, likely dependent on wet vs. dry interactions with the substrate, is an example where knowledge of the physical characteristics of the substrate and the larval epicuticle, combined with knowledge of larval behavior, can provide useful guidance for interpretation of sounds produced by red palm weevil larvae in palm trunks. In future field studies, signal analysis algorithms that match spectra of individual signals against profiles of known red palm weevil larval sounds (e.g., Mankin et al 2016a) may benefit from inclusion of squeal profiles to discriminate red palm weevil signals from background noise, depending on the size of the tree. Additional studies discussed below provide other examples where information about environmental conditions, insect physiology, and behavior together provide helpful cues about the interpretation of insect acoustic recordings.…”

“…Field studies of acoustic detection of hidden insect infestations often must interpret signals collected from insects of unknown physiological state in substrates whose signal-transmission characteristics are not well understood (Mankin et al 2018). In addition, field-collected signals often contain considerable background noise, including sounds of other insects that may need to be discriminated from sounds of the target insect under study (Mankin et al 2016a). One successful approach to these problems has been to identify multiple spectral and temporal pattern features of the target insect sounds, and employ ground-truthing to determine which feature combinations provide the most reliable estimates of infestation likelihood (Mankin 2011;Mankin et al 2018).…”

Monitoring, Detection and Control Techniques of Agriculture Pests and Diseases using Wireless Sensor Network: A Review

“…In [12] researchers developed an acoustic model to capture the sound of fruit flies (Ceratitis capitata). They conducted a large number of tests with this acoustic model on the Mediterranean fruit fly.…”

Acoustic Detection ofMallodon dasystomus(Coleoptera: Cerambycidae) inPersea americana(Laurales: Lauraceae) Branch Stumps

“…The insect acoustic detection device included an AED-2010 amplifier system (Acoustic Emission Consulting [AEC], Sacramento, California, USA) previously used to detect hidden infestations of larvae in trees (Dosunmu et al 2014;Mankin et al 2016). A 1.6-mm screw was inserted into solid wood near the wound.…”