Evidence map›Paper›PMID 31889863›Full record

ArticleSaudi journal of biological sciences2020

Evaluation of some non-invasive approaches for the detection of red palm weevil infestation.

Khawaja Ghulam Rasool, Mureed Husain, Shehzad Salman, Muhammad Tufail, Sukirno Sukirno, Khalid Mehmood, Wazirzada Aslam Farooq, Abdulrahman S Aldawood

Open access · hybridAbstract read
In one paragraph

Article in Saudi journal of biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 3 countries.

Khawaja Ghulam RasoolEconomic Entomology Research Unit, Department of Plant Protection, College of Food and Agriculture Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Mureed HusainEconomic Entomology Research Unit, Department of Plant Protection, College of Food and Agriculture Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Shehzad SalmanEconomic Entomology Research Unit, Department of Plant Protection, College of Food and Agriculture Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Muhammad TufailEconomic Entomology Research Unit, Department of Plant Protection, College of Food and Agriculture Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Sukirno SukirnoEntomology Laboratory, Universitas Gadjah Mada, Indonesia.
Khalid MehmoodEconomic Entomology Research Unit, Department of Plant Protection, College of Food and Agriculture Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Wazirzada Aslam FarooqDepartment of Physics and Astronomy, College of Science, King Saud University, Riyadh, Kingdom of Saudi Arabia.
Abdulrahman S AldawoodEconomic Entomology Research Unit, Department of Plant Protection, College of Food and Agriculture Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia.
King Saud University · SAUniversitas Gadjah Mada · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Red palm weevil (RPW) causes severe damage to date palm trees, leading to the death of trees if not detected and treated in time. A major obstacle in RPW control is the difficulty in identifying an early stage infestation In the present study, we measured the efficacy of some non-invasive optical devices including cameras (digital camera and thermal camera), TreeRadarUnit™ (TRU) (Radar 2000, Radar 900), resistograph, magnetic DNA biosensor, and Near-infrared Spectroscopy (NIRS) to detect RPW infestation in date palm trees under field conditions at Riyadh, Saudi Arabia. Date palm trees used in these experiments were selected based on visual observations. After inspection of date palm trees with different devices to detect RPW infestation, each tree was taken down and dissected in detail to validate the accuracy of each device. Results indicated that the visual RPW detection approach presented the highest accuracy (87%) followed by Radar 2000 (77%), Radar 900 (73%), resistograph (73%), thermal camera (61%), and digital camera (52%). Moreover, different stages of RPW placed in plastic cups were fastened onto the healthy date palm trunks to judge RPW presence, the magnetic DNA biosensor correctly detected RPW eggs 75% of the time, followed by detection of larvae (64%) and the control (empty cup) (54%). In another experiment where determinations were made in an open area, the efficiency of the DNA biosensor for detecting adults was 100%, followed by 83%, 63%, 60%, and 39% for pupae, larvae, eggs, and control, respectively. Absorption spectra generated through NIRS for infested, wounded, and control samples of date palm tissue showed a remarkable variation in the gradient of the corresponding peaks between 1850 nm and 1950 nm. Based on the detection efficiency of the tested devices, the resistograph and NIRS have the best potential to detect RPW infestation in date palm trees.

Indexed as

Digital cameraMagnetic DNA biosensorNear-infrared SpectroscopyPhoenix dactyliferaResistographThermal cameraTreeRadarUnit™

Identifiers

PMID31889863
PMCPMC6933274
OpenAlexW2982296445

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.