scholarly journals Early Detection of Red Palm Weevil, Rhynchophorus ferrugineus (Olivier), Infestation Using Data Mining

Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 95
Author(s):  
Heba Kurdi ◽  
Amal Al-Aldawsari ◽  
Isra Al-Turaiki ◽  
Abdulrahman S. Aldawood
Keyword(s):  
Data Mining ◽  
Plant Size ◽  
Support Vector ◽  
Classification Algorithms ◽  
Palm Tree ◽  
Rhynchophorus Ferrugineus ◽  
Red Palm Weevil ◽  
Palm Weevil ◽  
Using Data ◽  
F Measure

In the past 30 years, the red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier), a pest that is highly destructive to all types of palms, has rapidly spread worldwide. However, detecting infestation with the RPW is highly challenging because symptoms are not visible until the death of the palm tree is inevitable. In addition, the use of automated RPW weevil identification tools to predict infestation is complicated by a lack of RPW datasets. In this study, we assessed the capability of 10 state-of-the-art data mining classification algorithms, Naive Bayes (NB), KSTAR, AdaBoost, bagging, PART, J48 Decision tree, multilayer perceptron (MLP), support vector machine (SVM), random forest, and logistic regression, to use plant-size and temperature measurements collected from individual trees to predict RPW infestation in its early stages before significant damage is caused to the tree. The performance of the classification algorithms was evaluated in terms of accuracy, precision, recall, and F-measure using a real RPW dataset. The experimental results showed that infestations with RPW can be predicted with an accuracy up to 93%, precision above 87%, recall equals 100%, and F-measure greater than 93% using data mining. Additionally, we found that temperature and circumference are the most important features for predicting RPW infestation. However, we strongly call for collecting and aggregating more RPW datasets to run more experiments to validate these results and provide more conclusive findings.

scholarly journals Pheromone receptor of the globally invasive quarantine pest of the palm tree, the red palm weevil ( Rhynchophorus ferrugineus )

2021 ◽  
Author(s):  
Binu Antony ◽  
Jibin Johny ◽  
Nicolas Montagné ◽  
Emmanuelle Jacquin‐Joly ◽  
Rémi Capoduro ◽  
...  
Keyword(s):  
Palm Tree ◽  
Rhynchophorus Ferrugineus ◽  
Red Palm Weevil ◽  
Pheromone Receptor ◽  
Quarantine Pest ◽  
Palm Weevil

scholarly journals AN EVALUATION OF INVASIVE PEST, RED PALM WEEVIL RHYNCHOPHORUS FERRUGINEUS (OLIVIER, 1790) (COLEOPTERA, CURCULIONIDAE) POPULATION IN IRAQ

2020 ◽  
Vol 16 (2) ◽  
pp. 203-218
Author(s):  
Mohammed M. Alderawii ◽  
◽  
Aqeel A. Alyousuf ◽  
Samir A. Hasan ◽  
Jasim K. Mohammed ◽  
...  
Keyword(s):  
Date Palm ◽  
Monitoring Program ◽  
Invasive Pest ◽  
Palm Tree ◽  
Rhynchophorus Ferrugineus ◽  
Red Palm Weevil ◽  
Palm Trees ◽  
Palm Weevil ◽  
Baited Traps ◽  
Management Protocol

The Red Palm Weevil (RPW), Rhynchophorus ferrugineus (Olivier, 1790) is a devastating invasive pest of palm trees, invading the Iraqi date palm tree in 2015 for the first time in Safwan county, Basrah province. The Red Palm weevil has been categorized as a quarantine pest of date palm trees worldwide. In this study, a five years monitoring program has been achieved by scouting the invasive pest RPW population in Safwan county by using visual sampling and Pheromone baited traps. The results indicated that the number of infested palms, increased from 12 trees in 2015 to 111 in 16 orchards in 2016. The number of the infested palms was minimized to 3 trees in the county in 2019 due to the management protocol of the Ministry of Agriculture. Furthermore, the results of RPW adults appeared monthly in the county with two activity peaks during the moderate-temperature-months. In conclusion, the quarantine and management protocol of RPW decreased the population of the invasive pest which did not spread to other districts of Iraq.

scholarly journals Pheromone receptor of the globally invasive quarantine pest of the palm tree, the red palm weevil (Rhynchophorus ferrugineus)

2020 ◽  
Author(s):  
Binu Antony ◽  
Jibin Johny ◽  
Nicolas Montagné ◽  
Emmanuelle Jacquin-Joly ◽  
Rémi Capoduro ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Insect Pest ◽  
Economic Losses ◽  
Palm Tree ◽  
Rhynchophorus Ferrugineus ◽  
Red Palm Weevil ◽  
Pheromone Receptor ◽  
Pheromone Detection ◽  
Palm Trees ◽  
Palm Weevil

AbstractPalm trees are of immense economic, sociocultural, touristic and patrimonial significance all over the world, and date palm-related knowledge, traditions and practices are now included in UNESCO’s list of the Intangible Cultural Heritage of Humanity. Of all the pests that infest these trees, the red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier) is its primary enemy. The RPW is a category-1 quarantine insect pest that causes enormous economic losses in the cultivation of palm trees worldwide. The RPW synchronizes mass gathering on the palm tree for feeding and mating, regulated by a male-produced pheromone composed of two methyl-branched compounds, (4RS,5RS)-4-methylnonan-5-ol (ferrugineol) and 4(RS)-methylnonan-5-one (ferrugineone). Despite the importance of odorant detection in long-range orientation towards palm trees, palm colonization and mating, nothing regarding the molecular mechanisms of pheromone detection in this species is known. In this study, we report the identification and characterization of the first RPW pheromone receptor, RferOR1. Using gene silencing and functional expression in Drosophila olfactory receptor neurons, we demonstrate that RferOR1 is tuned to both ferrugineol and ferrugineone and binds five other structurally related molecules. We reveal the lifetime expression of RferOR1, which correlates with adult mating success irrespective of age, a factor that could explain the wide distribution and spread of this pest. As palm weevils are challenging to control based on conventional methods, elucidation of the mechanisms of pheromone detection opens new routes for mating disruption and the early detection of this pest via the development of pheromone receptor-based biosensors.

scholarly journals Using Data Mining Techniques to Analyze the Customers Reaction towards Social Media Advertisements

2019 ◽  
Vol 8 (2) ◽  
pp. 1139-1143
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Support Vector Machine ◽  
Nearest Neighbors ◽  
Support Vector ◽  
Classification Algorithms ◽  
Bayes Classifier ◽  
K Nearest Neighbors ◽  
Online Social Media ◽  
Using Data

As social media is in boom, it is becoming very easier for customers to share their views and comments and express their feelings regarding any products which are present in online social media. . If these data can be analyzed efficiently different suggestions can be provided to the company regarding to improvise their products sale. It becomes easier for the company to understand the customer’s reaction after seeing the advertisements of the products posted on social media. This research focuses on analyzing the sentiments of customers based on the comments and reviews of products available in Facebook. Sentimental Analysis is performed to analyze the customer comments as positive, negative and neutral and later they are labeled as 0 or 1. After the labeling process, a comparative analysis is performed using different classification algorithms. The classification algorithms used are K Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naïve Bayes Classifier. The classification algorithm with the highest accuracy is identified to predict the sales of online products

scholarly journals Performance Comparison of Data Mining Classification Algorithms for Early Warning System of Students Graduation Timeliness

2018 ◽  
Vol 6 (4) ◽  
pp. 158-163
Author(s):  
Ari Fadli ◽  
Mulki Indana Zulfa ◽  
Yogi Ramadhani
Keyword(s):  
Data Mining ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Performance Comparison ◽  
Support Vector ◽  
Classification Algorithms ◽  
Student Graduation ◽  
Using Data ◽  
Artificial Neural Network Ann

Observation of growing academic data can be carried using data mining methods, for example, to obtain knowledge related to the determinants of timeliness of students graduation. This study conducted a performance comparison of the classification algorithms using decision tree (DT), support vector machine (SVM), and artificial neural network (ANN). This study used students academic data from Faculty of Engineering, Universitas Jenderal Soedirman in the 2014/2015 odd semester until the 2017/2018 odd semester and the attributes that conform to the academic regulations. The analytical method used is CRISP-DM. The results showed that SVM provided the best performance in an accuracy of 90.55% and AUC of 0.959, compared to other algorithms. A Model with SVM algorithm can be implemented in an early warning system for timeliness of student graduation.

scholarly journals Electrocution and containment methods to reduce the activity of red palm weevil (Rhynchophorus ferrugineus, Ol.)

2020 ◽  
Vol 18 (4) ◽  
pp. e1006
Author(s):  
Marco Fedrizzi ◽  
Mauro Pagano ◽  
Mirko Guerrieri ◽  
Roberto Tomasone ◽  
Sergio Musmeci ◽  
...  
Keyword(s):  
Integrated Control ◽  
Plant Residues ◽  
Palm Tree ◽  
Strong Impact ◽  
Electric Discharges ◽  
Rhynchophorus Ferrugineus ◽  
Red Palm Weevil ◽  
Electric Voltage ◽  
Larval Stages ◽  
Palm Weevil

Aim of study: To evaluate the susceptibility of the Rhynchophorus ferrugineus to electric discharges, to eventually use this application in synergy with other methods as part of an integrated control strategy.Area of study: Worldwide.Material and methods: Three different electric voltage intensities were applied to R. ferrugineus to investigate the insect’s susceptibility in both adult and larval stages. The transmission and diffusion of electricity within a portion of the palm tree was tested. In addition, the suitability of containment materials for handling and transportation of plant residues was tested.Main results: The results of adult test showed that the total number of eggs laid per mating couple and the number of larvae born were about 1.5 times higher in the control compared to the electrified samples. The duration of the electric discharge on larvae had a small impact on the mortality rate, while the electric voltage showed a strong impact on mortality (87% for 10 V and 99% for 15 V). The presence of a significant electric current was observed in a viable portion of stem (distance from the source of electricity 10 cm) providing a direct current with 250 V tension. Among the materials tested for the transportation of palm residues, the aluminium net sheet showed the best results in the containment of both larval and adult individuals.Research highlights: Electrocution has proven to be a system which can help in the control of red palm weevil reducing the use of synthetic chemicals.

Quarantine Protocol Against Coleopteran Borers in Date Palm Offshoots Using Eco2 Fume Gas

2020 ◽  
Vol 31 (4) ◽  
pp. 190-192
Author(s):  
H.A. El-Shafie ◽  
M.E. Mohammed ◽  
A.A. Sallam
Keyword(s):  
Date Palm ◽  
Exposure Period ◽  
Rhynchophorus Ferrugineus ◽  
Internal Tissue ◽  
Red Palm Weevil ◽  
Rhinoceros Beetle ◽  
Planting Material ◽  
Palm Weevil ◽  
Longhorn Beetle ◽  
The World

Date palm offshoots represent an important source of planting material in many date palm-growing countries around the world. Infestation by the red palm weevil ((RPW) Rhynchophorus ferrugineus), the longhorn beetle ((LHB) Jebusaea hammerschmidti) and the rhinoceros beetle ((OB) Oryctes spp.) hinders commercialization and movement of these offshoots. An effective quarantine protocol, with exposure period of 72 h at 25 °C using ECO2FUME (EF) with phosphine concentration of 1500 ppm has been developed for date palm offshoots against these coleopteran internal tissue borers.

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