Submit to Forests Review for Forests Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Prevention and Control of Forest Diseases

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Health".

Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 11079

Share This Special Issue

Special Issue Editor

Dr. Juan Antonio Martín

E-Mail Website
Guest Editor

Departamento de Sistemas y Recursos Naturales, Universidad Politécnica de Madrid, Madrid, Spain
Interests: forest health; forest pathogens; breeding; resistance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

While outbreaks of aggressive forest diseases are increasing worldwide, conventional methods for controlling them are being banned due to their negative environmental impact. Therefore, there is an urgent need to find and apply alternative and environmentally friendly methods for reducing the impact of pathogens in forest ecosystems. These alternative methods constitute the basis of integrated management of diseases, i.e., the combination of an array of different strategies, such as prevention, biological control, physical methods, or eco-friendly chemical products (e.g., plant extracts, biostimulators, or mineral products) that are able to increase forest resilience against pathogens or to reduce pathogen pressure. In the context of integrated control, strategies for the prevention of the spread or the accidental introduction of aggressive pathogens take on special relevance. In forest declines, control should rely on the management of predisposing, inciting, and contributing factors. Furthermore, the development of techniques for the rapid detection of dangerous pathogens can help to avoid their spread. Breeding for resistance is an alternative strategy to recover forest species heavily affected by aggressive forest pathogens. Genomic-assisted breeding appears as a promising alternative to traditional breeding.

This Special Issue is seeking contributions on all aspects of prevention and control of forest pathogens. For instance, we welcome works on biological control, biostimulators or inductors of resistance, antimicrobial natural extracts, prevention measures, detection of pathogens, forest management to enhance forest resilience, and traditional and genomic-assisted breeding for resistance against pathogens. This issue aims to provide an up-to-date compendium of recent research in this field from around the world.

Dr. Juan Antonio Martín
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

resistance
tree breeding
biocontrol
biostimulator
integrated control, ecological control
inductors of resistance
forest decline
pathogen
disease

Published Papers (7 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

19 pages, 9177 KiB

Open AccessArticle

Evaluation of Fungicides as Protective and Curative Treatments against Canker Disease of Eucalyptus urograndis Caused by Chrysoporthe deuterocubensis in Malaysia

by Annya Ambrose, Attlee Banyang Peter Remun, Nura Adilla Shamsul Kamar, Ahmad Mustapha Mohamad Pazi, Wan Muhammad Azrul Wan Azhar, Norida Hanim Awing, Jack Liam and Razak Terhem

Forests 2023, 14(12), 2337; https://doi.org/10.3390/f14122337 - 29 Nov 2023

Viewed by 919

Abstract

Over the years, Eucalyptus plantations have rapidly expanded in Sarawak, Malaysia, accounting for 19% of the total forest plantation area. In a routine forest health surveillance conducted in 2022 at Sarawak, Malaysia, tree stands of Eucalyptus urograndis (Eucalyptus grandis × Eucalyptus urophylla hybrid) were detected with symptoms of stem canker disease caused by Chrysoporthe infection. Given the limited information on the chemical control of Chrysoporthe stem canker disease, there is a growing need to develop effective chemical control strategies to protect and cure Chrysoporthe infection on E. urograndis trees. Therefore, this study aimed to identify the causal pathogen of this stem canker disease in 7-year-old E. urograndis trees in Sarawak, Malaysia, and evaluate the efficacy of various fungicides as curative or protectant treatments on canker infection using artificial inoculation methods. Fungal isolates were first collected and subjected to molecular identification and pathogenicity analysis. Then, in vitro efficacy tests were evaluated using five licensed fungicides: thiram, prochloraz manganese chloride, copper hydroxide, dimethomorph, and mancozeb. Subsequently, the performance of these fungicides was assessed through preventive and curative field experiments on 10-year-old E. urograndis trees using the artificial inoculation technique. Based on the morphological and phylogenetic analysis of the ITS1/ITS4, β-tubulin 2 (BT2), and the combined ITS1/ITS4 and BT2 sequences extracted from 20 fungal isolates, Chrysoporthe deuterocubensis was identified as the causal pathogen of the canker disease, with isolate CHRY18 recording the highest virulence. The in vitro efficacy tests showed that prochloraz manganese chloride achieved 100% inhibition against C. deuterocubensis at 1.0 mg/mL. In the preventive experiment, thiram significantly inhibited C. deuterocubensis infection, yielding the shortest lesion length (19.40 mm) compared to the non-treated control (47.48 mm) at 20 weeks post-inoculation. In the curative experiment, a significant reduction of 54.7% in lesion length was observed in inoculated symptomatic trees after 20 weeks of post-fungicide treatment with copper hydroxide. In conclusion, this study demonstrated prochloraz manganese chloride, thiram, and copper hydroxide as effective chemical controls of C. deuterocubensis stem canker on E. urograndis. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Figure 1

25 pages, 6859 KiB

Open AccessArticle

Friend or Foe? The Endophytic Fungus Alternaria tenuissima Might Be a Major Latent Pathogen Involved in Ginkgo Leaf Blight

by Xiaojia Su, Ruirui Shi, Xiaobo Li, Zine Yu, Linfeng Hu, Haiyan Hu, Meng Zhang, Jingling Chang and Chengwei Li

Forests 2023, 14(7), 1452; https://doi.org/10.3390/f14071452 - 14 Jul 2023

Cited by 2 | Viewed by 1157

Abstract

Ginkgo leaf blight, one of the most economically important ginkgo diseases, has become very prevalent in many places in China. Flavonoids and endophytes are both considered important in ginkgo plant functioning. However, little is known about the potential relationships among ginkgo leaf blight pathogens, flavonoid accumulation profiles in infected leaves, and ginkgo leaf endophytes. In this study, the flavonoid accumulation profiles in infected leaves, pathogens of ginkgo leaf blight, and the endophytes of healthy ginkgo leaves were characterized. The levels of total flavonoids in the healthy parts of the infected leaves were significantly higher than those in the healthy leaves. Furthermore, Alternaria tenuissima, Botryosphaeria dothidea, and Dothiorella gregaria were identified as pathogens of ginkgo leaf blight; among them, A. tenuissima was the major pathogen. The in vitro experiments showed that flavonoids (apigenin, luteolin, and kaempferol) could significantly inhibit the growth of one or more pathogens at a concentration of 10 mg/L. Furthermore, fifty-six ginkgo leaf endophytic fungi (GLEF) from healthy ginkgo plants were isolated and characterized. Among them, Alternaria spp. were the most abundant, and GLEF55 shared the same ITS sequence with the pathogen Alternaria tenuissima. Thereafter, four flavonoid-producing endophytes were selected and their effects on the growth of pathogens were evaluated. The extracts of GLEF55 could significantly inhibit the growth of the pathogens B. dothidea and D. gregaria simultaneously in vitro, but not the growth of the pathogen A. tenuissima. Furthermore, the dual cultures of the candidate GLEF and ginkgo leaf blight pathogens revealed that GLEF55 had a similar growth rate to that of A. tenuissima and D. gregaria, but its growth rate was significantly slower than that of B. dothidea. Finally, the GLEF exhibited variable roles when facing pathogens in ginkgo leaves. Among them, GLEF55 showed similar pathogenicity as the pathogen A. tenuissima when they were dually cultured in ginkgo leaves. By contrast, GLEF17 (an uncultured soil fungus) could significantly counteract the pathogenic effects of A. tenuissima and D. gregaria, but it dramatically exacerbated the pathogenic effects of B. dothidea. Larger lesion areas were observed on the side of ginkgo leaves where GLEF39 (Alternaria sp.) or GLEF54 (Aspergillus ruber) and pathogens were simultaneously inoculated, which suggested that the pathogenicity of specific endophytic fungi occurred when plants were wounded. Overall, A. tenuissima, a major pathogen of ginkgo leaf blight, might lurk inside the plants as a friendly endogenous fungus and convert into a hostilely pathogenic mode at a particular time. This study proposed a possible cause of ginkgo leaf blight and provided potential theoretical guidance for its prevention. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Figure 1

16 pages, 7958 KiB

Open AccessFeature PaperArticle

Resin Canal Traits Variation in Pinus spp. with Different Susceptibility to the Pine Wood Nematode

by Aida Rodríguez-García, Juan A. Martín, Luis Gil, María Menéndez-Gutiérrez and Raquel Díaz

Forests 2023, 14(5), 925; https://doi.org/10.3390/f14050925 - 29 Apr 2023

Viewed by 1925

Abstract

Different studies have emphasized the influence of resin canal traits in the susceptibility of pine trees to the pine wood nematode (PWN) Bursaphelenchus xylophilus. Resin canals can facilitate the PWN migration through the stem and are involved in the accumulation of volatile terpenes in the xylem in response to the pathogen, inducing tracheid embolisms. In this work, we conducted a PWN inoculation experiment under greenhouse conditions to investigate the anatomical traits of constitutive resin canals among seven Pinus species with different degrees of susceptibility to the PWN: P. canariensis, P. halepensis, P. pinea and P. taeda were grouped into a ‘low-susceptible group’, and P. pinaster, P. radiata, and P. sylvestris were grouped into a ‘high-susceptible group’. The high-susceptible group presented higher xylem radial growth, wider constitutive canals in the cortex, lower frequency of constitutive canals in the cortex, and smaller constitutive canals in the xylem than the low-susceptible group. The size of constitutive cortical canals was positively related to the number of seedlings colonized by the PWN, suggesting that wider canals facilitated migration. The inoculation of the PWN increased the frequency and diminished the mean area of canals in the xylem, and the high-susceptible group showed more frequency of induced xylem canals than the low-susceptible group. Additionally, the high-susceptible group presented larger radial growths in the xylem than the low-susceptible group. These results suggest a role of resin canal traits on Pinus spp. susceptibility to the PWN. Nevertheless, the high interspecific variability found in these traits within each susceptibility group evidences the importance of other factors in the susceptibility to the PWN. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Figure 1

18 pages, 4174 KiB

Open AccessArticle

Monitoring the Severity of Rubber Tree Infected with Powdery Mildew Based on UAV Multispectral Remote Sensing

by Tiwei Zeng, Huiming Zhang, Yuan Li, Chenghai Yin, Qifu Liang, Jihua Fang, Wei Fu, Juan Wang and Xirui Zhang

Forests 2023, 14(4), 717; https://doi.org/10.3390/f14040717 - 31 Mar 2023

Cited by 5 | Viewed by 2002

Abstract

Rubber tree powdery mildew (PM) is one of the most devastating leaf diseases in rubber forest plantations. To prevent and control PM, timely and accurate detection is essential. In recent years, unmanned Aerial Vehicle (UAV) remote sensing technology has been widely used in the field of agriculture and forestry, but it has not been widely used to detect forest diseases. In this study, we propose a method to detect the severity of PM based on UAV low-altitude remote sensing and multispectral imaging technology. The method uses UAVs to collect multispectral images of rubber forest canopies that are naturally infected, and then extracts 19 spectral features (five spectral bands + 14 vegetation indices), eight texture features, and 10 color features. Meanwhile, Pearson correlation analysis and sequential backward selection (SBS) algorithm were used to eliminate redundant features and discover sensitive feature combinations. The feature combinations include spectral, texture, and color features and their combinations. The combinations of these features were used as inputs to the RF, BPNN, and SVM algorithms to construct PM severity models and identify different PM stages (Asymptomatic, Healthy, Early, Middle and Serious). The results showed that the SVM model with fused spectral, texture, and color features had the best performance (OA = 95.88%, Kappa = 0.94), as well as the highest recognition rate of 93.2% for PM in early stages. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Figure 1

11 pages, 1357 KiB

Open AccessArticle

Development of New Preventive Strategies for Pine Pitch Canker Caused by Fusarium circinatum in Irrigation Water and Evaluation in a Real Nursery Context

by Luís Fernandes, Diana Paiva, Ivo Roxo, Ana Rita Fernandes, Dina Ribeiro, Henrique Ribeiro and António Portugal

Forests 2023, 14(3), 443; https://doi.org/10.3390/f14030443 - 21 Feb 2023

Viewed by 1187

Abstract

Fusarium circinatum is one of the many threats to forests and Pinus nurseries all over the world, being classified as a quarantine organism by several organizations and governing bodies, such as the European and Mediterranean Plant Protection Organization (EPPO) and the European Union (EU), with associated phytosanitary measures in place to prevent its spread through the various means of dispersal. One such means of dispersal is the water used for irrigation in nurseries, which can contain fungal propagules. Three different treatments, namely, Desogerme, Intra Hydrocare and sodium hypochlorite (NaClO), were tested for their efficacy in eliminating F. circinatum spores in water at several concentrations. Those that showed 100% disinfection rates were selected for further assays regarding seed germination and water quality impact. From these studies, Desogerme 1% and Intra Hydrocare 4% were then selected for large-scale seed germination and plant certification assays in nurseries, where they showed promising results in regard to the prevention of infections in nurseries, and in this way, contribute to the efforts of mitigating this disease. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Figure 1

13 pages, 8510 KiB

Open AccessArticle

Monitoring of Discolored Trees Caused by Pine Wilt Disease Based on Unsupervised Learning with Decision Fusion Using UAV Images

by Jianhua Wan, Lujuan Wu, Shuhua Zhang, Shanwei Liu, Mingming Xu, Hui Sheng and Jianyong Cui

Forests 2022, 13(11), 1884; https://doi.org/10.3390/f13111884 - 10 Nov 2022

Cited by 2 | Viewed by 1266

Abstract

Pine wilt disease (PWD) has caused severe damage to ecosystems worldwide. Monitoring PWD is urgent due to its rapid spread. Unsupervised methods are more suitable for the monitoring needs of PWD, as they have the advantages of being fast and not limited by samples. We propose an unsupervised method with decision fusion that combines adaptive threshold and Lab spatial clustering. The method avoids the sample problem, and fuses the strengths of different algorithms. First, the modified ExG-ExR index is proposed for adaptive threshold segmentation to obtain an initial result. Then, k-means and Fuzzy C-means in Lab color space are established for an iterative calculation to achieve two initial results. The final result is obtained from the three initial extraction results by the majority voting rule. Experimental results on unmanned aerial vehicle images in the Laoshan area of Qingdao show that this method has high accuracy and strong robustness, with the average accuracy and F1-score reaching 91.35% and 0.8373, respectively. The method can help provide helpful information for effective control and tactical management of PWD. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Figure 1

22 pages, 11818 KiB

Open AccessArticle

A Detection Method for Individual Infected Pine Trees with Pine Wilt Disease Based on Deep Learning

by Yan Zhou, Wenping Liu, Haojie Bi, Riqiang Chen, Shixiang Zong and Youqing Luo

Forests 2022, 13(11), 1880; https://doi.org/10.3390/f13111880 - 09 Nov 2022

Cited by 5 | Viewed by 1828

Abstract

Pine wilt disease (PWD) can cause destructive death in many species of pine trees within a short period. The recognition of infected pine trees in unmanned aerial vehicle (UAV) forest images is a key technology for automatic monitoring and early warning of pests. This paper collected UAV visible and multispectral images of Korean pines (Pinus koraiensis) and Chinese pines (P. tabulaeformis) infected by PWD and divided the PWD infection into early, middle, and late stages. With the open-source annotation tool, LabelImg, we labeled the category of infected pine trees at each stage. After coordinate-correction preprocessing of the ground truth, the Korean pine and Chinese pine datasets were established. As a means of detecting infected pine trees of PWD and determining different infection stages, a multi-band image-fusion infected pine tree detector (MFTD) based on deep learning was proposed. Firstly, the Halfway Fusion mode was adopted to fuse the network based on four YOLOv5 variants. Simultaneously, the Backbone network was initially designed as a dual branching network that includes visible and multispectral subnets. Moreover, the features of visible and multispectral images were extracted. To fully utilize the features of visible and multispectral images, a multi-band feature fusion transformer (MFFT) with a multi-head attention mechanism and a feed-forward network was constructed to enhance the information correlation between visible and multispectral feature maps. Finally, following the MFFT module, the two feature maps were fused and input into Neck and Head to predict the categories and positions of infected pine trees. The best-performing MFTD model achieved the highest detection accuracy with mean average precision values (mAP@50) of 88.5% and 86.8% on Korean pine and Chinese pine datasets, respectively, which improved by 8.6% and 10.8% compared to the original YOLOv5 models trained only with visible images. In addition, the average precision values (AP@50) are 87.2%, 93.5%, and 84.8% for early, middle, and late stages on the KP dataset and 81.2%, 92.9%, and 86.2% on the CP dataset. Furthermore, the largest improvement is observed in the early stage with 14.3% and 11.6%, respectively. The results show that MFTD can accurately detect the infected pine trees, especially those at the early stage, and improve the early warning ability of PWD. Full article

(This article belongs to the Special Issue Prevention and Control of Forest Diseases)

► Show Figures

Journal Menu

Journal Browser

Prevention and Control of Forest Diseases

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (7 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI