0944 Red palm weevil detection and management

Tuesday, November 18, 2008: 12:10 AM
Room A6, First Floor (Reno-Sparks Convention Center)
Victoria Soroker , Department of Entomology, Agricultural Research Organization, The Volcani Center, Rishon LeZion, Israel
J. Pinhas , Department of Mathematics, Bar-Ilan University, Ramat Gan, Israel
S. Levsky , ARO, The Volcani Center, Bet Dagan, Israel
S. Reneh , ARO, The Volcani Center, Bet Dagan, Israel
Y. Nakache , The School of Engineering, Bar-Ilan University, Ramat Gan, Israel
A. Mizrach , Institute of Agricultural Engineering, The Volcani Center, Bet Dagan, Israel
A. Hetzroni , Institute of Agricultural Engineering, The Volcani Center, Bet Dagan, Israel
The red palm weevil (RPW) is a key pest of horticultural and ornamental palm species in Asia, the Middle East and the Mediterranean region, currently dispersing in Mediterranean European countries, endangering the landscape. The RPW larvae bore deep into palm crowns, trunks and offshoots, concealed from visual inspection until the palms are nearly dead. Traded palm trees are intensively transported between and within countries, spreading the pest worldwide. Due to known difficulties in the control of RPW in palms an intensive program for containing the pest is operated in Israel since 1999. The current RPW situation in Israel suggests that the program has successfully diminished the problem. The weevil population is currently under control and below the damage level. Relative contribution of various control measures will be discussed. Still, the occasional weevil trappings indicate instability which requires ongoing surveillance. We focused our research efforts on developing tools to identify and monitor concealed RPW larvae. Acoustic signals of boring RPW larvae can be recorded from the infested palms using off-the-shelf recording devices, but the discrimination of RPW signals from those emitted by healthy palms is still a challenge. The purpose of this research was to develop a mathematical method to automatically detect acoustic activity of RPW in offshoots and implement it in a prototype setup. The methodology applied was similar to techniques used in the field of speech recognition, utilizing Vector Quantization or Gaussian Mixture Modeling. The algorithm successfully achieved detection ratios as high as 98.9%. The study indicated feasibility of detecting RPW sounds by integrating a mathematical model and commercial recording devices, which could be utilized to monitor trade and transportation of offshoots.

doi: 10.1603/ICE.2016.34198