Rust Disease Research Articles

A recent shift in the Puccinia striiformis f. sp. tritici population in Serbia coincides with changes in yield losses of commercial winter wheat varieties

Wheat yellow (stripe) rust, caused by the fungus Puccinia striiformis f.sp. tritici (Pst), is a devastating disease of wheat worldwide. The success of Pst is largely due to the pathogens ability to rapidly overcome host resistance, generating new races that are easily dispersed between territories through wind-borne transmission of Pst urediniospores. Thus, first signs of entry of new Pst races into a region is usually captured by changes in disease severity. To examine any alterations of winter wheat variety response to Pst infection in Serbia, we analyzed yield and Pst disease severity in field trials conducted in 2014, 2021, and 2023. We specifically focused on analyzing Pst disease severity at growth stages related to yield. Associations between qualitative variables (variety, year) and quantitative variables (yield in untreated plots, yield loss, and disease index (DI) of Pst infection) were analyzed using Principal Component Analysis with mixed data. A General Linear Model was used to investigate the most influential factors on yield, yield loss, and Pst infection. The results indicated that yellow rust disease severity increased over the past decade, suggesting a potential recent change in the Pst population in Serbia. Comparative population genetic analysis of Pst samples from the 2023 wheat season and those collected in Serbia in 2014 confirmed a potential change in the Pst population. In addition, we found that yield losses across wheat varieties varied independently of Pst infection levels, indicating that wheat varieties differ in their ability to overcome damage caused by high levels of Pst infection. Given that the level of pathogen pressure triggering susceptibility reactions is cultivar-specific, our study highlights the need for a deeper focus on the mechanisms underlying these differences. Expanding our understanding of the interactions between pathogens, plant defense responses, and the ability of cultivars to mitigate yield losses will better equip us to predict and prevent potential yield losses in commercial wheat varieties due to yellow rust in the future.

Development of a new tool to detect Melampsora medusae f.sp. tremuloidae causing rust disease on Populus tremuloides.

Melampsora medusae f. sp. tremuloidae is a quarantine organism for the EU. In North America, this fungus causes rust disease on Populus tremuloides. In Europe, Populus tremula, an aspen closely related to P. tremuloides, is widespread and plays an important ecological role. Introduction of M. medusae f. sp. tremuloidae into Europe could be a major risk if this forma specialis could evolve and become virulent on P. tremula. To date no PCR-based assay exists to specifically detect M. medusae f. sp. tremuloidae. In this study, a sensitive and specific real-time PCR assay has been developed based on the 28S rDNA. The assay proved to be reliable using many real-time PCR kits and platforms. It can be used to monitor the introduction and the spread of M. medusae f. sp. tremuloidae in the context of phytosanitary regulations.

Classification of Corn Diseases and Pests Using Fuzzy Naïve Bayes Method

Corn is an essential dietary source for humans and animals. In addition to being a food source, corn has numerous benefits as a manufacturing commodity. The quality of grain crops must be considered to minimise the likelihood of disease and pest infestations. Therefore, the diseases and pests that attack corn plants must be classified so that farmers can control them during the growth period of corn plants. The fuzzy naive Bayes method is a statistical machine learning method that can be used to classify the diseases and pests of corn crops based on colour space-transformed digital images. This study aims to classify corn plant diseases and pests using the fuzzy naive Bayes method. Digital images of corn plant diseases and pests were transformed into a red, green and blue colour space model. The following seven classes of corn plant diseases and pests were classified: leaf rust disease, downy mildew disease, leaf blight disease, Locusta pest, Heliotis armigera pest, Spodoptera frugiperdita pest and non-pathogenic pest. With this method, the classification model achieves an accuracy of 87.83%, a macro precision of 34.91%, a macro recall of 35.90% and a macro f-score of 33.82%.

First report of rust disease caused by Puccinia Porri on Egyptian leek in Egypt and its control by bergamot essential oil

First report of rust disease caused by Puccinia Porri on Egyptian leek in Egypt and its control by bergamot essential oil

A Diagnostic Guide for Orange Rust Disease in Sugarcane

Puccinia kuehnii is an important airborne fungal pathogen of sugarcane, causing orange rust disease. P. kuehnii has been present in the Asia–Oceania region for over a century. The first report of this pathogen in the Western Hemisphere was in 2007, when it appeared in Florida, U.S.A. The main objective of this diagnostic guide is to provide detailed information about symptoms and signs of sugarcane orange rust as well as taxonomy, geographic distribution, isolation, identification, and storage of P. kuehnii. We also highlight the management strategies used in recent years to control this devastating fungal disease. This diagnostic guide will help facilitate future research focusing on fungal isolation procedures, genetics, and population studies of this pathogen.

First Report of Puccinia leontodontis on Scorzoneroides autumnalis from Iceland

Scorzoneroides autumnalis, commonly known as fall dandelion or autumn hawkbit, is a perennial plant with branched stems and several flower heads with bright yellow florets. In September 2023, rust disease was observed on 25% of plants present in two areas of Iceland showing reddish-yellow spots on the older leaves of the basal rosette. Morphological characteristics and sequencing analysis identified the rust species as Puccinia leontodontis. Our analyses confirm that P. leontodontis and P. hieracii are different species distinguishable through DNA analyses and by host genera, despite previously being regarded as synonyms. To our knowledge, this is the first report of P. leontodontis in Iceland.

Marker trait association and candidate gene identification for brown rust disease in sugarcane

AbstractBrown rust (caused by Puccinia melanocephala H. & P. Sydow) is one of the most devastating diseases in commercial sugarcane production. It could reduce sugarcane yield by up to 50% depending on the susceptibility levels of cultivars. Breeding disease‐resistant cultivars is the most effective, economical, and environmentally friendly option to control brown rust. A genome‐wide association study was conducted on a field trial using 432 sugarcane clones following an augmented design with two replications. Brown rust was screened using the whorl inoculation method over two crop cycles. The genotype data were obtained through target enrichment sequencing technologies. The gene actions considering six different models and marker dosage effects were included during the marker‐trait analysis. A total of seven, nine, and seven nonredundant marker‐trait associations were identified for plant cane, first ratoon, and across two crop cycles, respectively. The most significant (p‐value 6.17E−20) marker (chr01p59833543) has the additive effect of −0.63 for the diplo‐additive model and reduced disease severity the most (41.35%) due to heterozygote (AG) over homozygote allele (AA) combination in the tested clones. Gene annotation of the monoploid sugarcane genome R570 suggested that six putative candidate genes were co‐located with significant markers associated with brown rust resistance in sugarcane. The putative candidate genes regulated the formation of a cell wall barrier that plays a crucial role in controlling brown rust pathogen infection. The results of this study will open the path to exploiting new resistance sources for brown rust resistance in commercial sugarcane.

Wheat Rust Disease Detection Using Convolutional Neural Network

Wheat is a vital crop globally, playing a crucial role in ensuring food security. Any damage to wheat crops, particularly from diseases like wheat rust, can exacerbate the global food crisis. Wheat rust, along with other crop diseases, poses a serious threat to agricultural sustainability and food supply. Technological approaches to detect crop health can significantly enhance disease prevention compared to traditional manual methods. This study focuses on detecting wheat rust diseases, specifically wheat leaf rust, stem rust, and yellow rust, all of which vary in their impact on crops. By employing image analysis of wheat plants, the research aims to accurately distinguish between healthy crops and those affected by rust diseases. The experiments consider multiple variables, such as learning rate, dropout, and train-test split ratio, reflecting a comprehensive research approach. The model achieved an impressive 99.64% accuracy in detecting wheat rust, highlighting its potential for early disease detection and prevention.

Confirmation of oat crown rust disease in Taiwan.

Oat is a minor forage crop grown in Taiwan. Only a few historical records of oat rust disease have been reported in the country. Therefore, the pathogen population remains poorly characterized. A rust-like disease outbreak was detected at the Experimental Farm of National Taiwan University in 2019, which caused significant damage to field experiments. To determine the identity of the pathogen responsible for this disease outbreak, we collected infected foliar material. Disease signs suggested infection by the oat crown rust fungus. Hence, common procedures in rust pathology were applied to confirm the identity of the pathogen with phenotypic and molecular diagnostic techniques. A total of 50 field pathogen samples from infected oat cultivars were collected in 2019 and five single pustule rust isolates were obtained in 2020 and 2021. These isolates were initially identified as Puccinia coronata var. avenae f. sp. avenae (Pca) based on the phylogenetic analysis of nrITS sequence data. This identification was subsequently confirmed through whole-genome phylogeny, which showed that the representative Taiwanese isolate NTU1 clustered with other Pca representative strains in Basidiomycota. Phenotyping assays across 36 oat differential lines demonstrated that Taiwanese isolates are phenotypically similar with relatively low virulence. This study presents the first molecular confirmation of Pca in Taiwan and reports the virulence profiles of Taiwanese Pca population.

Phenotypic Selection of Bread Wheat (Triticum aestivum L.) Elite Lines for Diseases Resistance and Yield Potential

Wheat diseases and pests globally threaten wheat production. Wheat rust diseases are the most distractive biotic constraint of wheat in Ethiopia. Therefore, this experiment aimed to select and develop wheat rust resistance bread wheat varieties for the farmers. The result of the study revealed highly significant variation existed among tested genotypes for Plant Height (PHT), Days to Heading (DTH), Days to Maturity (DTM), Thousand Kernel Weight (TKW), Hectoliter Weight (HLW), and Yield (YLD) at (P< 0.001). Out the forty-nine introduced genotypes, five genotypes: EBW222153, EBW222159, EBW222160, EBW222162, and EBW222164, showed resistance to moderately resistance for both yellow rust and stem rust diseases across the two test locations. Also, they delivered high average yield: 5.9 tha-1, 4.46 tha-1, 5.17tha-1,4.15 tha-1, and 4.79tha-1 respectively. Furthermore, all the above-mentioned genotypes, except EBW222162, showed significantly higher yield at (P<0.05) than the check variety, Shaki. Furthermore, EBW222153, EBW222159, EBW222160, EBW222162, EBW222164, and EBW222178 would resistance to moderately resistance for stem rust at Melkasa. Thus, the selection of these genotypes and advancing to the next stage of breeding pipelines enables to release noble bread wheat varieties for the farmers.

Gamma-Aminobutyric Acid (GABA) as a Defense Booster for Wheat against Leaf Rust Pathogen (Puccinia triticina).

Wheat leaf rust, caused by Puccinia triticina, poses a growing threat to global wheat production, necessitating alternative strategies for effective disease management. This study investigated the potential of gamma-aminobutyric acid (GABA) to enhance resistance to leaf rust in two wheat cultivars: the susceptible Morocco and moderately resistant Sakha 94 cultivar. Our findings revealed that GABA significantly improved resistance in both cultivars to P. triticina, particularly in Morocco, by mitigating disease severity and reducing pustule density and size while extending both incubation and latent periods. This study assessed the effectiveness of two GABA application methods: plants received 1 mM GABA treatment, as a foliar spray, twenty-four hours prior to infection (pre-GABA), and plants received 1 mM GABA treatment both 24 h before and after infection (pre-/post-GABA), with the latter yielding significantly better results in reducing infection severity and improving plant resilience. Additionally, GABA application influenced stomatal behavior, promoting closure that may enhance resilience against leaf rust. GABA application on plants also modulated the production of reactive oxygen species (ROS). This led to a stronger oxidative burst in both susceptible and moderately resistant cultivars. GABA increased O2●- levels in guard cells and surrounding stomata, enhancing stomatal closure and the hypersensitive response. GABA enhanced the accumulation of soluble phenols and increased the activity of key antioxidant enzymes, catalase (CAT) and peroxidase (POX), which are vital for managing oxidative stress. To the best of our knowledge, this investigation represents the first report into the impact of GABA on wheat leaf rust disease.

Rust Disease Changes the Abundance and Composition of Bacterial Community in Iris lactea Rhizosphere

The microbial community plays a vital role in root–environment interactions, which affect plant performance under biotic stress. Rust disease significantly affects plant growth, which may also affect rhizosphere microbial community. However, there is a scarcity of studies investigating the microbial community of rhizosphere under rust disease stress. Iris lactea is a widely utilized plant in gardening and landscaping due to its versatility and ornamental value, but it is often susceptible to rust disease in landscape settings. In this study, we compared the bacterial communities between bulk soil (non-cultivated control), rhizosphere soil of healthy Iris lactea plants, and rhizosphere soil of Iris lactea plants infected with rust disease (rhizosphere-R). Results revealed significant alterations in the abundance and composition of bacterial communities associated with rust disease infection. Specifically, the rhizosphere-R samples exhibited a decreased Shannon index at 1.9% compared to bulk soil and the relative abundance of Proteobacteria was increased at 31.65%. Moreover, distinct changes in β-diversity were shown between bulk soil and rhizosphere samples. Notably, potentially pathogenic bacteria increased in abundance under rust disease stress, while beneficial bacterial taxa decreased. Overall, our results show that rust disease affects the rhizosphere microbial community, which emphasizes the ecological implications of plant–microbe interactions under biotic stress and implications for developing targeted rhizobacterial-based biocontrol strategies.

Rapid transfer of the leaf rust resistance gene Lr52 for the improvement of bread wheat cultivar HD3086

For varietal improvement, parental genotypes are crossed and advanced to generate homozygous lines with selection for desirable traits like disease resistance and yield. In the current study, leaf rust resistance gene Lr52 from Lr52/Yr47/2*Mace, the donor parent (DP), transferred to the recurrent parent (RP) HD3086, a popular Indian wheat cultivar, which has become susceptible to leaf rust. During the backcross breeding, the plants were grown sequentially under natural field conditions during the winter season and under controlled environmental conditions to take two crop generations during the summer season. Generations comprising F1, BC1F1, and BC2F1-3 plants were developed by crossing and successive backcrossing with RP HD3086 and further selfing to generate homozygous resistant lines. Plants with leaf rust resistance in backcross generations were selected phenotypically to identify the superior or similar plants as of RP HD3086. The Lr52/Yr47-linked SSR marker icg16c004_2 was initially utilised to confirm hybridity and foreground analysis in the BC1F1 generation but was found to be recombinant. Homozygous resistant (HR) lines in BC2F3 generation were selected based on leaf rust disease score and phenome recovery. Finally, the SSR markers unveiling parental polymorphism across the genome were employed to estimate the background recovery of phenotypically selected superior plants, revealing a recovery of 91.48 to 94.81 % of RP genome. The selected improved lines of HD3086+Lr52 displayed similar performance for most agro-morphological traits, and a few lines were also found to yield significantly superior to that of RP HD3086. Overall, the study shows the practical utility of phenotypic selection with intermittent selection under controlled and natural field conditions for improving popular cultivars with relatively higher speed and precision.

Colocalization of genetic regions that confer resistance/susceptibility against Puccinia species and association with Pyrenophora teres loci within the barley genome

Cereal rust diseases, including leaf, stem, and stripe rust, are some of the most devastating and economically important diseases of barley. However, host–pathogen genetic interaction research for each pathosystem is typically conducted independently and in isolation. Examples of host resistance/susceptibility genes functioning sympathetically to multiple pathogens or antagonistically to additional pathogens have been reported. Therefore, consolidation of loci that have been reported in multiple studies and across pathosystems is useful for variety development to maximize resistance to multiple pathogens and avoid inadvertent incorporation of susceptibility loci that act antagonistically to other pathogens. This review summarizes loci reported in three key biotrophic pathosystems of barley, including leaf, stem, and stripe rust. In conjunction with previously consolidated net blotch loci, this review lays the foundation for a wider barley rust resistance/susceptibility atlas. This review aims to inform breeders and researchers in rapidly identifying accessions and loci that need further characterization and which loci would be most useful to introgress into elite varieties.

Wheat leaf localization and segmentation for yellow rust disease detection in complex natural backgrounds

Wheat yellow rust disease poses a significant threat to global wheat yield and grain quality. Early detection of this disease will help to minimize the loss caused by its effects. Existing models work well on images taken in a controlled environment, whereas a uniform background is placed behind the leaf, but these models fail to produce good results in natural settings. Previous research also involves manual interventions in the pipeline to achieve good classification results such as cropping the images, using uniform backgrounds, etc. These systems are not practical to use in natural environments where there will be a lot of background noise to the image and manual cropping becomes an extra step for the farmer. Moreover, the unavailability of the dataset in which images of leaves are taken in a natural setting became another challenge. In this research, a dataset is curated and leaves are annotated for object detection, object segmentation further the leaves are classified into 3 classes ie healthy, resistant, and susceptible. A novel unsupervised image rotation algorithm is proposed that takes input from YOLOv8 to align the leave in such a way that maximum background can be removed by a rectangular bounding box . Then the comparison between multiple state-of-the-art segmentation models ie. UNET, Segment-Anything (SAM), Segnet, LinkNet, PSPNet, FPN, Deep-Labv3+ (Xception), and DeepLabv3+ (Mo-bileNet) has shown that UNET has outperformed all the other segmentation models with an IOU score of 0.9563. Lastly for classification, the performance of multiple convolution neural networks ie. VGG16, Resnet 101(v2), Xception, Mo-bileNetV2, and Transformer-based models ie. Swin trans-former and MobileVit have been compared. Swin transformer has outperformed the state-of-the-art CNN models with an accuracy of 95.8%. This paper proposes a complete robust pipeline that can be deployed in natural environment and does not need any manual intervention to produce good results. This research shows that good localization of leaves and removal of unwanted background noise at the earliest stage of the pipeline will assist the segmentation model to effectively segment the leaf from the background which will enable classification models to achieve high classification accuracy, even when dealing with very small datasets.

Analysis of Plant and Fungal Transcripts from Resistant and Susceptible Phenotypes of Leptospermum scoparium Challenged by Austropuccinia psidii.

Austropuccinia psidii is the causal pathogen of myrtle rust disease of Myrtaceae. To gain understanding of the initial infection process, gene expression in germinating A. psidii urediniospores and in Leptospermum scoparium-inoculated leaves were investigated via analyses of RNA sequencing samples taken 24 and 48 h postinoculation (hpi). Principal component analyses of transformed transcript count data revealed differential gene expression between the uninoculated L. scoparium control plants that correlated with the three plant leaf resistance phenotypes (immunity, hypersensitive response, and susceptibility). Gene expression in the immune resistant plants did not significantly change in response to fungal inoculation, whereas susceptible plants showed differential expression of genes in response to fungal challenge. A putative disease resistance gene, jg24539.t1, was identified in the L. scoparium hypersensitive response phenotype family. Expression of this gene may be associated with the phenotype and could be important for further understanding the plant hypersensitive response to A. psidii challenge. Differential expression of pathogen genes was found between samples taken 24 and 48 hpi, but there were no significant differences in pathogen gene expression that were associated with the three different plant leaf resistance phenotypes. There was a significant decrease in the abundance of fungal transcripts encoding three putative effectors and a putative carbohydrate-active enzyme between 24 and 48 hpi, suggesting that the encoded proteins are important during the initial phase of infection. These transcripts, or their translated proteins, may be potential targets to impede the early phases of fungal infection by this wide-host-range obligate biotrophic basidiomycete.

Transcriptome, hormonal, and secondary metabolite changes in leaves of DEFENSE NO DEATH 1 (DND1) silenced potato plants

DEFENSE NO DEATH 1 (DND1) is a cyclic nucleotide-gated ion channel protein. Earlier, it was shown that the silencing of DND1 in the potato (Solanum tuberosum L.) leads to resistance to late blight, powdery mildew, and gray mold diseases. At the same time, however, it can reduce plant growth and cause leaf necrosis. To obtain knowledge of the molecular events behind the pleiotropic effect of DND1 downregulation in the potato, metabolite and transcriptome analyses were performed on three DND1 silenced lines of the cultivar ‘Désirée.’ A massive increase in the salicylic acid content of leaves was detected. Concentrations of jasmonic acid and chlorogenic acid and their derivatives were also elevated. Expression of 1866 genes was altered in the same way in all three DND1 silenced lines, including those related to the synthesis of secondary metabolites. The activation of several alleles of leaf rust, late blight, and other disease resistance genes, as well as the induction of pathogenesis-related genes, was detected. WRKY and NAC transcription factor families were upregulated, whereas bHLHs were downregulated, indicating their central role in transcriptome changes. These results suggest that the maintenance of the constitutive defense state leads to the reduced growth of DND1 silenced potato plants.

Determination of the rate and frequency of Natura 250 EW fungicide for the management of cedar rust from Gesho (Rhamnus prinoides) in the north west Amhara Region, Ethiopia

Rhamnus prinoides (Gesho) is grown in the homesteads of farmers in western Amhara. The leaves, twigs, and stems of Gesho are indispensable ingredients in traditional beverages. Its production has recently suffered from cedar rust caused by the fungus Gymnosporangium. To manage this disease, different fungicides have been recommended. Therefore, this research was designed to determine the rate and frequency of the use of the Natura 250 EW system for managing this disease in Gesho during 2020. Five application rates of Natura 250 EW and three spray frequencies were used as treatments to manage the disease in infected Gesho plants via the Randomized Complete Block Design (RCBD). Statistically significant differences (P ≤ 0.05) were found between treatments for most parameters. Among these 0.75 litter ha-1 treatments, two spray applications resulted in the lowest severity and greatest relative efficacy, followed by three spray applications of 0.50 litter ha−1 at Bahir Dar Zuria district. However, at Yilmana Densa district, the lowest severity and greatest relative efficacy were found for the 0.75 litter ha−1 spray, followed by the 0.50 litter ha−1 spray, compared with the other treatments. Even though 0.75 litter ha−1 had greater relative efficacy and lower disease severity than the other treatments, there was no statistically significant difference between the three sprays of 0.50 litter ha−1 at both locations. Therefore, three sprays of Natura 250 EW at 0.50 litter ha−1 in 15-day intervals should be recommended and demonstrated for the management of cedar rust disease on Gesho.

Comprehensive analysis of hairpin small RNAs involved in resistance and pathogenesis during wheat-Puccinia triticina interactions.

Wheat leaf rust, caused by the fungus Puccinia triticina (Pt), severely affects the grain quality and quantity of bread wheat (Triticum aestivum L.). Hairpin small(s)RNAs, like micro(mi)RNAs and their variants [including isomiRNAs (isomiRs) and microRNA-like RNAs (milRNAs)], along with their corresponding target genes, bestow leaf rust disease resistance, development and progression from both interacting species. However, the regulatory networks remain inadequately understood. Thirteen differentially expressed novel miRNAs, including two isomiRs and three milRNAs were discerned from induced reads of wheat sRNA libraries, and a further 5,393 and 1,275 candidate target genes were predicted in wheat and Pt, respectively. Functional annotation divulged that wheat-originated miRNAs/isomiRs were involved in resistance, while Pt-derived milRNAs imparted pathogenesis. The identified milRNAs- Tae-Pt-milR5, Tae-Pt-milR12, and Tae-Pt-milR14b and their cleavage sites on Pt target gene MEP5 were confirmed through degradome library screening, suggesting cross-kingdom translocation of Pt virulent genes in wheat host. Co-expression analysis of miRNAs/isomiRs-target genes provided insights into combating leaf rust disease, while co-expression analysis of milRNAs-target gene pairs reflected the extent of pathogenicity exerted by Pt with varied expression levels at the analyzed time points. The analysis pinpointed leaf rust-responsive candidate hairpin sRNAs- Tae-miR8, Tae-Pt-miR12, Tae-Pt-miR14a, and Tae-Pt-miR14b in wheat and Tae-Pt-milR12 in Pt. This study provides new insights into the hairpin sRNAs involved in the resistance and pathogenesis of wheat and Pt, respectively. Furthermore, crucial hairpin sRNAs and their promising targets for future biotechnological interventions to augment stress resilience have been identified.

A potential cause for extensive dieback of Acacia mearnsii plantation in highland districts of Awi zone, northwestern Ethiopia

Although Acacia mearnsii De Wild has rapidly expanded for economic and ecological purposes in the highland districts of the Awi zone, northwestern Ethiopia, recent plantations have suffered from severe defoliation, dieback, and stunted growth. We conducted this study in four districts that hold potential for A. mearnsii plantations. The study examined the identification of the causal agent, its occurrence, and local community perceptions of the plantation's significant dieback. Most respondents (75.8 %) indicated that the substantial dieback began in the rainy season of 2020 and spread rapidly. They also noted that close spacing of plantings and limited silvicultural measures exacerbated the damage. We discovered in this study that the wattle rust disease caused by the Uromycladium acacia fungus was the root cause of significant dieback for A. mearnsii plantations. The incidence and severity of this wattle rust varied significantly (p = 0.001) between districts, seasons, and plantation age groups. In Fegita-Lekuma district, the maximum disease severity was over 72 % in plantations up to two years after planting during the rainy season. The progression of the wattle rust disease caused by U. acacia has led to the loss of A. mearnsii plantations in the Awi zone, resulting in a severe economic and environmental crisis. Consequently, we should apply fungicides to seedlings at nursery sites in the short term. Eventually, however, the focus should shift towards prioritizing disease-resistant species and implementing proper forest management practices. This should be achieved through scientific initiatives that engage key stakeholders in areas where this tree species could potentially grow.