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Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests

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A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Crop Protection, Diseases, Pests and Weeds".

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 80144

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Special Issue Editors

Dr. Grazia Licciardello

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Guest Editor

Council for Agricultural Research and Analysis of Agricultural Economics, (CREA-OFA, Rende, CS)
Interests: plant pathogens; molecular diagnosis; HTS for virus detection; genotypic characterization, bacterial regulation systems
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Giuliana Loconsole

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Guest Editor

National Research Council, Institute for Sustainable Plant Protection, Bari, Italy
Interests: plant viruses; molecular and serological tools for pathogen detection; manipulation and characterization of quarantine plant pathogens; EU legislation in plant health

Special Issue Information

Dear Colleagues,

Globalization and climate change are significantly shaping the worldwide distribution of plant harmful organisms and alien invasive species. The emergence of Xylella fastidiosa and citrus black spot in the Mediterranean basin are just some of the most recent cases of the detrimental impact of pathogens/pests/diseases entering new areas, threatening natural and cultivated environments, agriculture and forestry, ecosystems, and biodiversity. Effective surveillance strategies are critical to support prevention and biosecurity plant health programs. Early detection and correct identification of pests and disease agents require effective and sensitive diagnostic tools that NPPOs can adopt for implementing their monitoring programs to reduce risks posed by exotic and alien pathogens/pests. Nowadays, molecular methods and remote sensing approaches have improved the efficiency and the capability for inspections and for testing. But we need to go further and improve pathogen detection at the earliest stage of the infections as well as gather information on the genetics of the pathogen population(s), a crucial step for setting proper control actions. Likely, the next frontiers will be the use of high-throughput sequencing (HTS) technologies, the use of remote sensing approaches for prioritizing areas to be inspected, and the development of point-of-care tests (POCT), once validated and cost-efficient.

This Special Issue aims to collect original contributions and review articles focusing on the more recent advanced technologies from rapid field detection at different levels, from landscape, to plant/tree (i.e., remote sensing), to laboratory tests for the detection of regulated harmful organisms in host plants and insect vectors. Moreover, papers on techniques focused on genotypic and/or phenotypic characterization are also welcome. I am confident that this Issue will help to provide updates on tools for efficient pest surveillance systems and will assist technical programmes for reducing epidemic risks in agriculture.

Dr. Grazia Licciardello
Prof. Dr. Giuliana Loconsole
Guest Editors

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Keywords

Detection methods; Genetic diversity; Pest risk; Early detection; Phytosanitary measures; Economic impact; Remote sensing; Alien invasive pests

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Published Papers (10 papers)

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15 pages, 2725 KiB

Open AccessArticle

Detection of Xylella fastidiosa in Host Plants and Insect Vectors by Droplet Digital PCR

by Serafina Serena Amoia, Angelantonio Minafra, Angela Ligorio, Vincenzo Cavalieri, Donato Boscia, Maria Saponari and Giuliana Loconsole

Agriculture 2023, 13(3), 716; https://doi.org/10.3390/agriculture13030716 - 20 Mar 2023

Cited by 3 | Viewed by 2798

Abstract

Xylella fastidiosa (Xf) is a Gram-negative plant bacterium that causes severe diseases affecting several economically important crops in many countries. To achieve early detection of the pathogen, a droplet digital PCR (ddPCR)-based approach was used to detect the bacterium at low concentrations in different plant species and insect vectors. In this study, we implemented the reaction conditions of a previously developed ddPCR assay, and we validated its use to detect Xf in insect vectors as well as in a broader list of host species. More specifically, the sensitivity and accuracy of the protocol were assessed by testing five plant matrices (Olea europaea, Nerium oleander, Vitis vinifera, Citrus sinensis, and Prunus dulcis), and for the first time, the insect vector (Philaenus spumarius), was either naturally infected or artificially spiked with bacterial suspension at known concentrations. The lowest concentrations detected by ddPCR were 5 ag/µL of bacterial DNA and 1.00 × 10² CFU/mL of bacterial cells. Both techniques showed a high degree of linearity, with R² values ranging from 0.9905 to 0.9995 and from 0.9726 to 0.9977, respectively, for qPCR and ddPCR. Under our conditions, ddPCR showed greater analytical sensitivity than qPCR for O. europea, C. sinensis, and N. oleander. Overall, the results demonstrated that the validated ddPCR assay enables the absolute quantification of Xf target sequences with high accuracy compared with the qPCR assay, and can support experimental research programs and the official controls, particularly when doubtful or inconclusive results are recorded by qPCR. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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14 pages, 1720 KiB

Open AccessArticle

A Colorimetric LAMP Detection of Xylella fastidiosa in Crude Alkaline Sap of Olive Trees in Apulia as a Field-Based Tool for Disease Containment

by Serafina Serena Amoia, Giuliana Loconsole, Angela Ligorio, Alexandros K. Pantazis, George Papadakis, Electra Gizeli and Angelantonio Minafra

Agriculture 2023, 13(2), 448; https://doi.org/10.3390/agriculture13020448 - 14 Feb 2023

Cited by 8 | Viewed by 2885

Abstract

Xylella fastidiosa subsp. pauca (Xfp) infects olive trees and other hosts in Southern Apulia (Italy), devastating agriculture and landscape. A containment strategy of the disease requires quick and sensitive detection tools. Therefore, a colorimetric LAMP protocol was developed using as a template a crude alkaline sap obtained from incubation of 50–60 mg of thin slices of olive twigs in a NaOH-containing buffer. This rapid molecular assay can be performed directly in the field, as it needs only a portable isothermal block. Tissues of the same olive trees analysed by this technique were also compared to qPCR (using purified total plant DNA as template) as well as digital droplet PCR (on the same crude alkaline extracts used in cLAMP). A titration of the cLAMP reaction with healthy olive sap, spiked with dilutions of in vitro cultivated Xfp cells and plasmid DNA containing the target sequence, gave positive detection results as low as 10² CFU/mL and up to 169.2 target copies/µL, equivalent to about 0.9 pg of the genomic DNA. A portable, sensitive and target-specific Xfp field test was developed, which has a 40 min sample-to-answer time and does not require any DNA isolation procedure or laboratory equipment. The application of this detection assay could help the monitoring and containment of the disease spread. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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12 pages, 263 KiB

Open AccessArticle

Diagnostic Procedures to Detect Xylella fastidiosa in Nursery Stocks and Consignments of Plants for Planting

by Giuliana Loconsole, Stefania Zicca, Lorenzo Manco, Oumaima El Hatib, Giuseppe Altamura, Oriana Potere, Vito Elicio, Franco Valentini, Donato Boscia and Maria Saponari

Agriculture 2021, 11(10), 922; https://doi.org/10.3390/agriculture11100922 - 26 Sep 2021

Cited by 10 | Viewed by 3350

Abstract

Preventive measures for infectious diseases caused by the harmful plant pathogenic bacterium Xylella fastidiosa include inspections and diagnostic tests on imported consignments of plants and in nurseries. Currently, mandatory checks on plant propagating materials are enforced in Europe (EU regulation 2021/1201) for the most susceptible species found in the European outbreaks, and prior to move propagating materials of the “specified plants” from nurseries located in the so-called “demarcated areas”. These requirements imply sampling and laboratory manipulation of a large number of samples, nevertheless plants to be sampled are often small size potted plants. While statistically based methods for inspections and sampling are available, namely the International Standards for Phytosanitary Measures n. 31, validated laboratory procedures to test large volumes of plant materials are lacking. In this work, we optimized two distinct protocols to detect X. fastidiosa in pooled plant materials collected from lots of plants for planting. The first protocol was designed to test in pool few samples (up to 8), the second to process through a single diagnostic test plant material from a high number of samples (up to 225). Accuracy of the newly developed protocols was assessed by pooling at different ratio tissues collected from healthy and infected Polygala myrtifolia, Nerium oleander, Olea europaea, Lavandula stoechas and Prunus avium. Moreover, tests included pools of plantlets of Brassicaceae and Solanaceae artificially inoculated with stem portions of infected periwinkle. Using both protocols, high diagnostic sensitivity values were generated using serological and molecular tests, with qPCR consistently yielding the highest performance values, regardless the host species tested. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

10 pages, 955 KiB

Open AccessCommunication

Neofusicoccum batangarum Causing Dieback of Mango (Mangifera indica) in Florida

by Alina S. Puig and Mike C. Winterstein

Agriculture 2021, 11(9), 853; https://doi.org/10.3390/agriculture11090853 - 7 Sep 2021

Cited by 4 | Viewed by 3319

Abstract

Mango (Mangifera indica) is an economically significant crop, and is affected by dieback in nearly all commercial production areas. Due to the wide range of organisms previously associated with these disease symptoms in Florida, isolations and pathogenicity tests were carried out to determine the causal organism. The pathogen was identified as Neofusicoccum batangarum based on genetic sequences from three loci (internal transcribed spacer of the rDNA (ITS), β-tubulin (BT), and translation elongation factor 1-α (EF)), recommended for members of the Botryosphaeriaceae family. Possible infection routes were determined by inoculating wounded and unwounded stems with N. batangarum. Trees wounded prior to pathogen inoculation developed larger lesions (5.85 cm ± 1.51) than unwounded trees (0.51 cm ± 0.48), p < 0.0003. In addition, lesions only developed at a small number of inoculation sites in the absence of wounds (14.3%), compared to 93% when stems were wounded. No necrosis was observed in the negative controls. This study provides molecular data on N. batangarum, and evidence of its role causing mango dieback in Florida. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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16 pages, 1712 KiB

Open AccessArticle

Genetic Structure and Molecular Variability of Grapevine Fanleaf Virus in Sicily

by Stefano Panno, Andrea Giovanni Caruso, Sofia Bertacca, Antonino Pisciotta, Rosario Di Lorenzo, Serafino Marchione, Slavica Matić and Salvatore Davino

Agriculture 2021, 11(6), 496; https://doi.org/10.3390/agriculture11060496 - 27 May 2021

Cited by 5 | Viewed by 4822

Abstract

Grapevine fanleaf virus (GFLV) is one of the main causes of grapevine fanleaf degeneration disease (GFDD) and is present in almost all areas where grapevine is cultivated. In this work, we ascertained the presence and spread of GFLV in different commercial vineyards in four Sicilian provinces (Italy), and its genetic structure and molecular variability were studied. In detail, a total of 617 grapevine samples of 11 autochthonous grapevine cultivars were collected in 20 commercial vineyards. Preliminary screening by serological (DAS-ELISA) and molecular (RT-PCR) analyses for ArMV (arabis mosaic virus) and GFLV detection were conducted. Results obtained showed the absence of ArMV in all the samples analyzed, while 48 out of 617 samples gave positive results to GFLV, for a total of 9 out of 11 cultivars analyzed. Phylogenetic analyses carried out on the GFLV-CP gene of 18 Sicilian GFLV sequences selected in this study showed a certain degree of variability among the Sicilian isolates, suggesting a different origin, probably as a consequence of the continuous interchange of GFLV-infected propagating material with other Italian regions or viticultural areas located in other countries. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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17 pages, 3667 KiB

Open AccessArticle

A Simulation of the Use of High Throughput Sequencing as Pre-Screening Assay to Enhance the Surveillance of Citrus Viruses and Viroids in the EPPO Region

by Grazia Licciardello, Rosario Ferraro, Giuseppe Scuderi, Marcella Russo and Antonino F. Catara

Agriculture 2021, 11(5), 400; https://doi.org/10.3390/agriculture11050400 - 27 Apr 2021

Cited by 9 | Viewed by 3331

Abstract

Citrus are affected by many viruses and viroids, some globally widespread and some restricted to particular countries or areas. In this study, we simulated the use of high throughput sequencing (HTS) and the bioinformatic analysis of small interfering RNAs (siRNA) as a pre-screening method to guide bioindexing and molecular detection to enhance the surveillance survey of some key or emerging citrus viruses, such as non-European citrus tristeza virus isolates (non-EU CTV), citrus tatter leaf virus, citrus leprosis virus, citrus yellow mosaic virus, and citrus bark cracking viroid, present in the EPPO lists, and the citrus yellow vein clearing virus. The HTS’s ability to detect other citrus viroids was also evaluated. The results demonstrate that HTS provides a comprehensive phytosanitary status of citrus samples either in single and multiple infections of viruses and viroids. It also provides effective information on citrus tristeza virus mixed infections despite not being able to identify the non-EU variants of the virus. Bioindexing checks each single virus infection but does not differentiate viroids on the Etrog citron indicator and is time-consuming. Molecular assays are valuable as confirmation tests of viruses and viroids but many pairs of primers are needed for a full screening and new or non-target pathogens remain undetected. In addition, the genomes of two isolates of the citrus yellow vein clearing virus and the citrus tatter leaf virus, detected in a sample from China, are described. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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16 pages, 28821 KiB

Open AccessArticle

Occurrence and Distribution of Major Viruses Infecting Eggplant in Lebanon and Molecular Characterization of a Local Potato Virus X Isolate

by Raied Abou Kubaa, Elia Choueiri, Angelo De Stradis, Fouad Jreijiri, Maria Saponari and Fabrizio Cillo

Agriculture 2021, 11(2), 126; https://doi.org/10.3390/agriculture11020126 - 5 Feb 2021

Cited by 4 | Viewed by 4428

Abstract

This research was carried out in order to evaluate the presence and distribution of viral infections causing severe disease in eggplant plants collected from different districts in Bekaa valley, Lebanon. Most infected plants showed virus-like symptoms consisting predominantly of leaf blotch, mottling chlorotic and ring spots; leaf twisting and plant dwarf were also observed in the visited fields. Symptomatic and asymptomatic plants were collected and screened by ELISA test for the presence of several different pathogenic viruses potentially present in the area. Results showed that potato virus Y (PVY) was the most prevalent virus found by ELISA (detected in the 15.3% of the tested plants), followed by eggplant mottled dwarf virus (EMDV, 2.9%) and cucumber mosaic virus (CMV, 1.2%), while tomato spotted wilt virus (TSWV), alfalfa mosaic virus (AMV) and pepper mottle virus (PepMoV) were not detected. Biological indexing of symptomatic ELISA-negative plants, followed by electron microscopy, indicated the presence of virus-like particles of the genus Potexvirus, which was subsequently confirmed as potato virus X (PVX) by RT-PCR and Sanger sequencing. PVX was found in 35.3% of the tested plants, all sampled in the northern Bekaa area. In a phylogenetic analysis, the partial coat protein gene sequence of a selected Lebanese isolate, PVX-AK1, clustered together with other PVX isolates from Asia. Furthermore, the 124-aa sequence of PVX-AK1 shared 100% identity with PVX-UK3, an isolate which is known as avirulent in potato genotypes carrying either Nx or Rx resistance genes. This work revealed a picture of the previously uninvestigated phytosanitary status of eggplant crops in an important horticultural area of Lebanon. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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13 pages, 3462 KiB

Open AccessArticle

RobHortic: A Field Robot to Detect Pests and Diseases in Horticultural Crops by Proximal Sensing

by Sergio Cubero, Ester Marco-Noales, Nuria Aleixos, Silvia Barbé and Jose Blasco

Agriculture 2020, 10(7), 276; https://doi.org/10.3390/agriculture10070276 - 7 Jul 2020

Cited by 48 | Viewed by 13649

Abstract

RobHortic is a remote-controlled field robot that has been developed for inspecting the presence of pests and diseases in horticultural crops using proximal sensing. The robot is equipped with colour, multispectral, and hyperspectral (400–1000 nm) cameras, located looking at the ground (towards the plants). To prevent the negative influence of direct sunlight, the scene was illuminated by four halogen lamps and protected from natural light using a tarp. A GNSS (Global Navigation Satellite System) was used to geolocate the images of the field. All sensors were connected to an on-board industrial computer. The software developed specifically for this application captured the signal from an encoder, which was connected to the motor, to synchronise the acquisition of the images with the advance of the robot. Upon receiving the signal, the cameras are triggered, and the captured images are stored along with the GNSS data. The robot has been developed and tested over three campaigns in carrot fields for the detection of plants infected with ‘Candidatus Liberibacter solanacearum’. The first two years were spent creating and tuning the robot and sensors, and data capture and geolocation were tested. In the third year, tests were carried out to detect asymptomatic infected plants. As a reference, plants were analysed by molecular analysis using a specific real-time Polymerase Chain Reaction (PCR), to determine the presence of the target bacterium and compare the results with the data obtained by the robot. Both laboratory and field tests were done. The highest match was obtained using Partial Least Squares-Discriminant Analysis PLS-DA, with a 66.4% detection rate for images obtained in the laboratory and 59.8% for images obtained in the field. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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Review

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27 pages, 18803 KiB

Open AccessReview

Exotic and Emergent Citrus Viruses Relevant to the Mediterranean Region

by Antonino F. Catara, Moshe Bar-Joseph and Grazia Licciardello

Agriculture 2021, 11(9), 839; https://doi.org/10.3390/agriculture11090839 - 31 Aug 2021

Cited by 6 | Viewed by 10457

Abstract

Citrus production in the Mediterranean area is of considerable importance, in both cultural and economic terms, and the viability of the industry greatly depends on proper phytosanitary management. In this review, we focus on exotic and emerging dangerous citrus viruses that have still not been reported in the countries of the Mediterranean area, that are not yet regulated or that are restricted to certain small areas. We also discuss the contribution that old and new technologies may offer for valuable surveys aimed at promoting the adoption and sharing of better control measures and the production of pathogen-tested citrus trees and rootstocks. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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18 pages, 2363 KiB

Open AccessEditor’s ChoiceReview

Review on Convolutional Neural Network (CNN) Applied to Plant Leaf Disease Classification

by Jinzhu Lu, Lijuan Tan and Huanyu Jiang

Agriculture 2021, 11(8), 707; https://doi.org/10.3390/agriculture11080707 - 27 Jul 2021

Cited by 262 | Viewed by 29360

Abstract

Crop production can be greatly reduced due to various diseases, which seriously endangers food security. Thus, detecting plant diseases accurately is necessary and urgent. Traditional classification methods, such as naked-eye observation and laboratory tests, have many limitations, such as being time consuming and subjective. Currently, deep learning (DL) methods, especially those based on convolutional neural network (CNN), have gained widespread application in plant disease classification. They have solved or partially solved the problems of traditional classification methods and represent state-of-the-art technology in this field. In this work, we reviewed the latest CNN networks pertinent to plant leaf disease classification. We summarized DL principles involved in plant disease classification. Additionally, we summarized the main problems and corresponding solutions of CNN used for plant disease classification. Furthermore, we discussed the future development direction in plant disease classification. Full article

(This article belongs to the Special Issue Enhancing Surveillance and Detection of Invasive Harmful Plant Pathogens and Pests)

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