Smart Palm: An IoT Framework for Red Palm Weevil Early Detection

Smart agriculture is an evolving trend in agriculture industry, where sensors are embedded into plants to collect vital data and help in decision making to ensure higher quality of crops and prevent pests, disease, and other possible threats. In Saudi Arabia, growing palms is the most important agricultural activity, and there is an increasing need to leverage smart agriculture technology to improve the production of dates and prevent diseases. One of the most critical diseases of palms if the red palm weevil, which is an insect that causes a lot of damage to palm trees and can devast large areas of palm trees. The most challenging problem is that the effect of the weevil is not visible by humans until the palm reaches an advanced infestation state. For this reason, there is a need to use advanced technology for early detection and prevention of infestation propagation. In this project, we have developed am IoT based smart palm monitoring prototype as a proof-of-concept that (1) allows to monitor palms remotely using smart agriculture sensors, (2) contribute to the early detection of red palm weevil. Users can use web/mobile application to interact with their palm farms and help them in getting early detection of possible infestations. We used Elm company IoT platform to interface between the sensor layer and the user layer. In addition, we have collected data using accelerometer sensors and we applied signal processing and statistical techniques to analyze collected data and determine a fingerprint of the infestation

CURRENT STATUS, CHALLENGES, MANAGEMENT AND FUTURE PERSPECTIVES OF THE RED PALM WEEVIL Rhynchophorus ferrugineus OLIVIER (COLEOPTERA, CURCULIONIDAE) ERADICATION - A REVIEW

The date palm is a cultural and economic heritage of many nations. The red palm weevil, Rhynchophorus ferrugineus Olivier (Coleoptera, Curculionidae) is among the world’s most serious insect pests of palms that have rapidly expanded its geographical distribution and host plant range during the last decades. Integrated pest management (IPM) is followed to suppress the pest using the most economical and least hazardous methods to humans and the environment. Since R. ferrugineus is a serious pest of date palm production worldwide, farmers, researchers, and scientists have developed many tactics to eradicate this pest. However, there was no published article covering and integrating the current status, biology, ecology, and future control tactics of R. ferrugineus and proposes an IPM program. Therefore, in this review, R. ferrugineus geographical distribution, host plant range, economic importance, infestation symptoms, morphology, biology, and its management tactics were thoroughly discussed. These tactics include early detection of R. ferrugineus infestation, trapping, chemical applications, use of bio-agents, bioinsecticides (plant extracts), resistance cultivars, cultural practices, sterile insect technique, gene silencing technology, quarantine, and geographical information system. In conclusion, all available control tactics suggest that R. ferrugineus could be successfully managed by developing IPM programs comprising several means of control. It is hoped that this review will highlight some aspects of date palm management and raise research gaps and directions deserving further investigations to develop a better understanding of R. ferrugineus management and therefore contributes to the sustainability of date palm cultivation worldwide

On the design of a bioacoustic sensor for the early detection of the red palm weevil

During the last two decades Red Palm Weevil (RPW, Rynchophorus Ferrugineus) has become one of the most dangerous threats to palm trees in many parts of the World. Its early detection is difficult, since palm trees do not show visual evidence of infection until it is too late for them to recover. For this reason the development of efficient early detection mechanisms is a critical element of RPW pest management systems. One of the early detection mechanisms proposed in the literature is based on acoustic monitoring, as the activity of RPW larvae inside the palm trunk is audible for human operators under acceptable environmental noise levels (rural areas, night periods, etc.). In this work we propose the design of an autonomous bioacoustic sensor that can be installed in every palm tree under study and is able to analyze the captured audio signal during large periods of time. The results of the audio analysis would be reported wirelessly to a control station, to be subsequently processed and conveniently stored. That control station is to be accessible via the Internet. It is programmed to send warning messages when predefined alarm thresholds are reached, thereby allowing supervisors to check on-line the status and evolution of the palm tree orchards. We have developed a bioacoustic sensor prototype and performed an extensive set of experiments to measure its detection capability, achieving average detection rates over 90%.We would like to acknowledge Michel Ferry and Susi Gomez (from Estacion Phoenix at Elche, Spain) for giving us access to their large RPW sound recording corpora and offering their cooperation during the development of this work. Finally, this work has been partially funded by Spanish Ministry of Education and Science under grants CTM2011-29691-C02-01, TIN2011-28435-C03-01 and TIN2011-27543-C03-03.Martinez Rach, MO.; Migallón, H.; López Granado, O.; Pérez Malumbres, MJ.; Martí Campoy, A.; Serrano Martín, JJ. (2013). On the design of a bioacoustic sensor for the early detection of the red palm weevil. Sensors. 13(2):1706-1729. doi:10.3390/s130201706S17061729132Mukhtar, M., Rasool, K. G., Parrella, M. P., Sheikh, Q. I., Pain, A., Lopez-Llorca, L. V., … Aldawood, A. S. (2011). New Initiatives for Management of Red Palm Weevil Threats to Historical Arabian Date Palms*. Florida Entomologist, 94(4), 733-736. doi:10.1653/024.094.0401R. P. Haff, & D. C. Slaughter. (2004). REAL-TIME X-RAY INSPECTION OF WHEAT FOR INFESTATION BY THE GRANARY WEEVIL, SITOPHILUS GRANARIUS (L.). Transactions of the ASAE, 47(2), 531-537. doi:10.13031/2013.16022Nakash, J., Osem, Y., & Kehat, M. (2000). A suggestion to use dogs for detecting red palm weevil (Rhynchophorus ferrugineus) infestation in date palms in Israel. Phytoparasitica, 28(2), 153-155. doi:10.1007/bf02981745Mielle, P., & Marquis, F. (1999). An alternative way to improve the sensitivity of electronic olfactometers. Sensors and Actuators B: Chemical, 58(1-3), 526-535. doi:10.1016/s0925-4005(99)00158-6Control and Pest Management of Red Palm Weevil (Rhynchophorus Ferrugineus) with Bioacoustic Methodshttp://www.laartech.biz/data/pdf/Control%20of%20Red%20Palm%20Weevil.pdfAcoustic Emission Consulting (AEC). AED-2000 Acoustic Detection Systemhttp://www.protecusa.biz/termatracaed2000L.htmlGutiérrez, A., Ruiz, V., Moltó, E., Tapia, G., & del Mar Téllez, M. (2010). Development of a bioacoustic sensor for the early detection of Red Palm Weevil (Rhynchophorus ferrugineus Olivier). Crop Protection, 29(7), 671-676. doi:10.1016/j.cropro.2010.02.001Siriwardena, K. A. P., Fernando, L. C. P., Nanayakkara, N., Perera, K. F. G., Kumara, A. D. N. T., & Nanayakkara, T. (2010). Portable acoustic device for detection of coconut palms infested by Rynchophorus ferrugineus (Coleoptera: Curculionidae). Crop Protection, 29(1), 25-29. doi:10.1016/j.cropro.2009.09.002HUSSEIN, W. B., HUSSEIN, M. A., & BECKER, T. (2010). DETECTION OF THE RED PALM WEEVILRHYNCHOPHORUS FERRUGINEUSUSING ITS BIOACOUSTICS FEATURES. Bioacoustics, 19(3), 177-194. doi:10.1080/09524622.2010.9753623Mankin, R. W. (2011). Recent Developments in the use of Acoustic Sensors and Signal Processing Tools to Target Early Infestations of Red Palm Weevil in Agricultural Environments1. Florida Entomologist, 94(4), 761-765. doi:10.1653/024.094.0405Fiaboe, K. K. M., Mankin, R. W., Roda, A. L., Kairo, M. T. K., & Johanns, C. (2011). Pheromone-Food-Bait Trap and Acoustic Surveys ofRhynchophorus ferrugineus(Coleoptera: Curculionidae) in Curacao1. Florida Entomologist, 94(4), 766-773. doi:10.1653/024.094.0406Pinhas, J., Soroker, V., Hetzroni, A., Mizrach, A., Teicher, M., & Goldberger, J. (2008). Automatic acoustic detection of the red palm weevil. Computers and Electronics in Agriculture, 63(2), 131-139. doi:10.1016/j.compag.2008.02.004JN5148 System-On-Chip Reference Datasheethttp://www.nxp.com/products/rf/wireless_microcontrollers/JN5148.htm

Recent Trends in the Early Detection of the Invasive Red Palm Weevil, <em>Rhynchophorus ferrugineus</em> (Olivier)

Red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier), is one of the most invasive pest species that poses a serious threat to date palm and coconut palm cultivation as well as the ornamental Canary Island palm. RPW causes massive economic losses in the date palm production sector worldwide. The most important challenge of RPW detection in the early stages of an infestation is the presence of a few externally visible signs. Infested palm shows visible signs when the infestation is more advanced; in this case, the rescuing of infested palms is more complicated. Early detection is a useful tool to eradicate and control RPW successfully. Until now, the early detection techniques of RPW rely mainly on visual inspection and pheromone trapping. Several methods to detect RPW infestation have recently emerged. These include remote sensing, highly sensitive microphones, thermal sensors, drones, acoustic sensors, and sniffer dogs. The main objective of this chapter is to provide an overview of the modern methods for early detection of the RPW and discuss the most important RPW detection technologies that are field applicable

Conservation Strategy for Palm Groves: Optimal Chemical Control Model for Red Palm Weevil, Rhynchophorus ferrugineus

Rhynchophorus ferrugineus (Olivier, 1790) is an invasive pest species that constitutes one of the most important problems around the Mediterranean region and has been responsible for the loss of over 100,000 palm trees with an estimated annual cost of EUR several hundred million since its introduction into Europe. Methodological approaches of conservation ecology, such as multidisciplinary modelling, also apply in the management of cultural landscapes concerning ornamental plants, such as palm trees of the area. In this paper, we propose a dynamic model for the control of the red palm weevil, contributing in this way to the sustainability of an existing cultural landscape. The primary data set collected is a sample from the density-time function of a two-cohort pest population. This data set suggests a bimodal analytic description. If, from this data set, we calculate a sample from the accumulated density-time function (the integral of the density-time function), it displays a double sigmoid function (with two inflections). A good candidate for the analytical description of the latter is the sum of two logistic functions. As for the dynamic description of the process, a two-dimensional system of differential equations can be obtained, where the solution’s second component provides the analytical description of the original density-time function for the two-cohort population. Since the two-cohort waves appear in all three cycle stages, this reasoning applies to the subpopulations of larvae, pupae and adults. The model fitting is always performed using the SimFit package. On this basis, a mathematical model is proposed, which is sufficiently versatile to be of help in the control of this pest species in other geographical areas

Automatic Large Scale Detection of Red Palm Weevil Infestation using Aerial and Street View Images

The spread of the Red Palm Weevil has dramatically affected date growers, homeowners and governments, forcing them to deal with a constant threat to their palm trees. Early detection of palm tree infestation has been proven to be critical in order to allow treatment that may save trees from irreversible damage, and is most commonly performed by local physical access for individual tree monitoring. Here, we present a novel method for surveillance of Red Palm Weevil infested palm trees utilizing state-of-the-art deep learning algorithms, with aerial and street-level imagery data. To detect infested palm trees we analyzed over 100,000 aerial and street-images, mapping the location of palm trees in urban areas. Using this procedure, we discovered and verified infested palm trees at various locations

ChatGPT in the context of precision agriculture data analytics

In this study we argue that integrating ChatGPT into the data processing pipeline of automated sensors in precision agriculture has the potential to bring several benefits and enhance various aspects of modern farming practices. Policy makers often face a barrier when they need to get informed about the situation in vast agricultural fields to reach to decisions. They depend on the close collaboration between agricultural experts in the field, data analysts, and technology providers to create interdisciplinary teams that cannot always be secured on demand or establish effective communication across these diverse domains to respond in real-time. In this work we argue that the speech recognition input modality of ChatGPT provides a more intuitive and natural way for policy makers to interact with the database of the server of an agricultural data processing system to which a large, dispersed network of automated insect traps and sensors probes reports. The large language models map the speech input to text, allowing the user to form its own version of unconstrained verbal query, raising the barrier of having to learn and adapt oneself to a specific data analytics software. The output of the language model can interact through Python code and Pandas with the entire database, visualize the results and use speech synthesis to engage the user in an iterative and refining discussion related to the data. We show three ways of how ChatGPT can interact with the database of the remote server to which a dispersed network of different modalities (optical counters, vibration recordings, pictures, and video), report. We examine the potential and the validity of the response of ChatGPT in analyzing, and interpreting agricultural data, providing real time insights and recommendations to stakeholdersComment: 33 pages, 21 figure

Frequency and time pattern differences in acoustic signals produced by Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae) and Sitophilus zeamais (Motschulsky) (Coleoptera: Curculionidae) in stored maize

Frequency spectra and timing patterns of brief, 1–10 ms broadband sound impulses produced by movement and feeding activities of Prostephanus truncatus and Sitophilus zeamais last instars and adults in maize were investigated to find spectral and temporal pattern information useful for distinguishing among these species and stages. The impulse spectra were categorized into five different types of frequency patterns (profiles), designated Broadband, HighF, MidF1, MidF2 and LowF to indicate differences in their peak energies and broadness of frequency range. Groups (trains) of three or more closely spaced impulses, termed bursts, were observed to occur frequently in all recordings, as has been reported for sounds produced by other insects. Mean rates of bursts, mean counts of impulses per burst, and mean rates of impulses in bursts were calculated and compared among the two species and stages. The counts of broadband and MidF2 impulses per burst and the rates of broadband and MidF2 impulses in bursts were significantly different for adult than for 4th instar S. zeamais and either stage of P. truncatus. These findings can be useful in developing an acoustic sensor system for automated detection of hidden insects including P. truncatus and S. zeamais in bulk storage warehouses. The findings are discussed in relation to different movement and feeding behavior patterns that have been identified in these important pests

PHID-Coleo - a database identification tool for wood-boring beetles in plant health interceptions: Poster

Recent examples for the introduction of wood-breeding beetles in Europe include the asian longhorn beetles Anoplophora spp. and Aromia bungii (red-necked longhorn beetle). These and other woodboring beetle species pose a high risk of economic damage to trees and wood products. Smaller beetles like the powderpost beetles from the families Bostrichidae and Lyctidae also have the potential for causing considerable damage. These are often not identified adequately during inspections of wood packaging materials, making it impossible to assess their risk for becoming invasive. This project will aim at closing that gap. Our project PHID-Coleo (= Plant Health Identification of Coleoptera) has the objective to develop new diagnostic tools for the identification of potentially invasive and economically important beetles that can be found in wood packaging materials. The identification methods include classical identification keys based on morphological characters as well as molecular methods based on DNA analysis by PCR (barcoding). The methods for species identification will be supplemented by molecular analyses of introduced populations to clarify within species variations. Such methods will make it possible to determine the taxonomic relationship of samples from different areas and to draw conclusions about the introduction pathways, resulting in more efficient monitoring of the invasive species and preventing their spread. PHID-Coleo will build a freely accessible database of relevant species which are potentially invasive.Recent examples for the introduction of wood-breeding beetles in Europe include the asian longhorn beetles Anoplophora spp. and Aromia bungii (red-necked longhorn beetle). These and other woodboring beetle species pose a high risk of economic damage to trees and wood products. Smaller beetles like the powderpost beetles from the families Bostrichidae and Lyctidae also have the potential for causing considerable damage. These are often not identified adequately during inspections of wood packaging materials, making it impossible to assess their risk for becoming invasive. This project will aim at closing that gap. Our project PHID-Coleo (= Plant Health Identification of Coleoptera) has the objective to develop new diagnostic tools for the identification of potentially invasive and economically important beetles that can be found in wood packaging materials. The identification methods include classical identification keys based on morphological characters as well as molecular methods based on DNA analysis by PCR (barcoding). The methods for species identification will be supplemented by molecular analyses of introduced populations to clarify within species variations. Such methods will make it possible to determine the taxonomic relationship of samples from different areas and to draw conclusions about the introduction pathways, resulting in more efficient monitoring of the invasive species and preventing their spread. PHID-Coleo will build a freely accessible database of relevant species which are potentially invasive

Detection and monitoring of invasive and native species of wood-boring beetles in a changing environment

Wood-boring insects are extremely important organisms because of their impact on forest ecosystems and on the economic value of forest products, wood in particular. Recent environmental modifications, linked to global climate change, lead to a variation in both distribution and impact of wood insects species in many forest areas. New trade pattern are added to this scenario, with an increase exchange of goods and their packaging, often wood-made, and with them an increase in risk of spreading wood insect species in new ecosystems. This work is based on trap monitoring of wood-boring beetles, mainly jewel beetles (Coleoptera: Buprestidae), Longhorn beetles (Coleoptera: Cerambyciadae), weevils (Coleoptera: Curculionidae) and bark beetles (Coleoptera: Curculionidae: Scolytinae), in order to evaluate the effect of climate, and in particular of temperature, on distribution and performance of some of the main species in the Alpine area. Furthermore, this works includes a study on the application of new monitoring tools based on the application of digital cameras remotely checked through the web, able to improve the early detection strategies for invasive species. A first study recalls the main wood-boring insect species invasive for Europe and their detection and monitoring techniques, and it is followed by the experimental trial of a new device for remote monitoring of wood-boring beetles. The second study concerns the distribution of wood-boring insects along an elevational gradient, considered as a spatial analogue of climate change, and it shows the positive effect of temperature on the abundance of most aggressive species against Norway spruce (Picea abies). The third study evaluates the effect of warm summer temperatures on the performance of Ips acuminatus, a bark beetle associated with Scots pine in the Alps, in the same season and between consecutive years. It shows that particularly high temperatures are likely to affect positively the population growth in the same season, but negatively the population growth of the following year. The fourth study presents an application of remote controlled photographic traps to the early detection of longhorn beetles belonging to the genus Monochamus spp., considered dangerous for being the vector of the pine wood nematode Bursaphelenchus xylophilus. Camera traps have been associated to a molecular analysis device for the species identification based on a technique named LAMP-PCR. The result is an integrated system able to focus the efforts of trap checking and field molecular analysis only to those traps showing the presence of the target species. To show the wide applicability of the new proposed technologies, at the end of this work is added a study carried on in New Zealand in which remote camera traps are applied to study the phenology of a stone fruit pest