Powdery Mildew Disease Research Articles (Page 1)

Nicotinamide adenine dinucleotide (NAD+) is a ubiquitous electron carrier in many metabolic pathways. Exogenous application of NAD+ induces systemic acquired resistance (SAR)-like defense responses in Arabidopsis thaliana, while potential NAD+ binding receptors in Arabidopsis, the lectin receptor-like kinases (LecRLK) family, have been reported influencing plant development and stress response. To evaluate the effects of exogenous NAD+ treatment of squash against powdery mildew disease, caused by fungal pathogen Podosphaera xanthii, greenhouse trials were conducted. NAD+ at the concentration of 0.25, 0.5, 0.75, 1, and 5 mM applied by leaf infiltration significantly lowered powdery mildew disease severity compared to the untreated control. The hyphal development of P. xanthii was inhibited after infiltrating NAD+ at 1 mM into squash leaves. Additionally, an RNA-sequencing study revealed the up-regulation of different function categories of genes in squash, including those in the stress and defense response pathways, after NAD+ treatment and during pathogen invasion and disease development. The LecRLK family in squash was also screened and analyzed as potential receptors. A total of 51 LecRLK genes were found in squash, and phylogenetic analysis revealed a close relationship between these genes and the Arabidopsis LecRLK genes. The results from RNA-sequencing showed that this gene family is positively regulated by NAD+ treatment and pathogen inoculation in squash. Taken together, results from this study showed that NAD+ has significant effects on reducing powdery mildew disease severity and implied the potential role LecRLK gene family played in disease resistance to powdery mildew in squash.

Transient overexpression of CpVQ27 reduced the Cucurbita pepo's resistance to powdery mildew.

Powdery mildew, caused by Erysiphe quercicola, is one of the primary diseases responsible for the reduction in natural rubber production in China. This disease is a typical airborne pathogen, characterized by its ability to spread via air currents and rapidly escalate into an epidemic under favorable environmental conditions. Accurate prediction and determination of the prevention and control period represent both a critical challenge and key focus area in managing rubber-tree powdery mildew. This study investigates the effects of spore concentration, environmental factors, and infection time on the progression of powdery mildew in rubber trees. By employing six distinct machine learning model construction methods, with the disease index of powdery mildew in rubber trees as the response variable and spore concentration, temperature, humidity, and infection time as predictive variables, a preliminary predictive model for the disease index of rubber-tree powdery mildew was developed. Results from indoor inoculation experiments indicate that spore concentration directly influences disease progression and severity. Higher spore concentrations lead to faster disease development and increased severity. The optimal relative humidity for powdery mildew development in rubber trees is 80% RH. At varying temperatures, the influence of humidity on the disease index differs across spore concentration, exhibiting distinct trends. Each model effectively simulates the progression of powdery mildew in rubber trees, with predicted values closely aligning with observed data. Among the models, the Kernel Ridge Regression (KRR) model demonstrates the highest accuracy, the R2 values for the training set and test set were 0.978 and 0.964, respectively, while the RMSE values were 4.037 and 4.926, respectively. This research provides a robust technical foundation for reducing the labor intensity of traditional prediction methods and offers valuable insights for forecasting airborne forest diseases.

Powdery mildew caused by Erysiphe polygoni (DC)is one of the most economically important diseases in urdbean, and it occurs at later stages of crop growth, resulting in a yield loss of 20-50%. Powdery mildew control strategies include the use of chemicals and sources of host plant resistance. But due to the cost of chemicals, farmers rarely practice such control measures, and the usage of such fungicides will negatively affect the environment and especially human health. Therefore, the most effective way to control powdery mildew is the use of resistant varieties. Keeping this in view, disease screening studies were made to understand the identification of powdery mildew disease. Since powdery mildew may inflict heavy losses to the crop in the Telangana state, till now, none of the cultivars have been identified as resistant in Telangana against powdery mildew; therefore, this study was initiated to evaluate available urdbean germplasm for the identification of resistance sources to breed disease-resistant cultivars. In Rabi 2024-25, forty-nine genotypes were screened against powdery mildew diseases under field conditions along with susceptible and resistant checks. Out of 49 genotypes, none of the genotypes showed immune or resistant, five genotypes viz., MBG 1134, MBG 1169, MBG 1171, MBG 1123, and DBG 32-1 identified as moderately resistant, the remaining genotypes showed moderately susceptible (MBG-8, VBG 17-026) to highly susceptible (TU-512, PU-31, IPU 19-56, IPU 19-2).

Ubiquitin-conjugating enzyme (UBC) E2 is a critical component of the ubiquitination process. It interacts with the RING domain of E3 ligases through its UBC domain, enables specific identification of substrate proteins, thereby plays a pivotal role in plant growth and development. In this study, the number, gene structure, and evolutionary relationships of UBC genes in wheat and Arabidopsis thaliana were analyzed at a whole-genome level. Furthermore, the roles of TaUBC genes in wheat resistance to powdery mildew were investigated. A total of 180 UBC genes were identified in wheat and categorized into 15 Classes through phylogenetic analysis. Quantitative real-time PCR analysis revealed significant expression changes of TaUBC1A-5, TaUBC1A-6, TaUBC3A-5, TaUBC3B-14, TaUBC5A-2, TaUBC6A-2, and TaUBC7A-2 after the powdery mildew infection, compared to the 0-h time point. Virus-induced gene silencing experiments demonstrated that TaUBC3A-5 positively regulates wheat resistance to powdery mildew, whereas TaUBC3B-14 acts as a negative regulator. These findings provide valuable insights into the function of the UBC gene family in wheat and offer support for development of new disease-resistant wheat germplasm using UBC genes.

ABSTRACTSince April 2020, a powdery mildew disease has been consistently observed on Plantago asiatica in northern India. Microscopic examination of the associated fungus revealed morphological characteristics typical of the genus Golovinomyces. Molecular identification based on a BLASTn similarity search of the internal transcribed spacer region, along with phylogenetic analyses using maximum likelihood, maximum parsimony, and Bayesian inference methods, confirmed the species as Golovinomyces sordidus. Pathogenicity was verified through inoculation of healthy P. asiatica plants. To the best of our knowledge, this is the first confirmed report of G. sordidus causing powdery mildew on P. asiatica in India.

Effect of biological control agents in the management of powdery mildew disease of cucumber under field conditions

Pisum sativum (field pea) belongs to the family Fabaceae. It is one of the six major pulse crops cultivated globally and is second highest yielding legume. A survey was conducted in Northern guinea savanna of Nigeria to identify the causative fungi of powdery mildew diseases on field pea. Temporay slides were prepared in the field by placing a clear tape on the infected part of the plant sticky side down and the tape was placed on a drop of distilled water/lactophenol cotton blue on a slide then observed under the microscope. The size and shape of the conidia and conidiophore were recorded. Samples were then sent to the Commonwealth Agricultural Bureaux International (CABI), UK for confirmation of the identification for the fungi inducing the diseases. Results obtained from CABI showed that four different species of Erysiphe i.e. E. pisi, E. brunneopunctata. E. cruciferarum and E. cichoracearum were responsible for the powdery mildew diseases observed on P. sativum in the study areas. As an exotic plant, the fungi might have come along with the seeds into the country, as Erysiphe spp. is seed borne or other reservoir hosts of the fungi might have occurred in the wild. To the best of our knowledge, this is the first report of the four species of Erysiphe inducing powdery mildew diseases of field pea in Nigeria.

The genus Golovinomyces (Erysiphaceae, Ascomycota) comprises obligate biotrophic fungi responsible for powdery mildew diseases on many economically important and wild plant species, mainly within the Asteraceae. From 1987 to 2024, we collected about 1000 samples of Golovinomyces spp. across Korea and performed morphological observation along with multi-locus sequence analyses (including internal transcribed spacer, large subunit, intergenic spacer, and glyceraldehyde-3-phosphate dehydrogenase). Resolving five previous ambiguous species complexes, Golovinomyces ambrosiae, Golovinomyces artemisiae, Golovinomyces biocellatus, Golovinomyces cichoracearum, and Golovinomyces orontii, clarified species boundaries and refined previous identifications. As a result, this study identified 21 Golovinomyces species, representing an increase from 15 species previously recorded in Korea. A new species, Golovinomyces physalidis, was described as the causal agent of powdery mildew on Physaliastrum echinatum and Physalis alkekengi var. franchetii. Additionally, five species (Golovinomyces chrysanthemi, Golovinomyces latisporus, Golovinomyces monardae, Golovinomyces montagnei, and Golovinomyces riedlianus) and three host plants (Achillea ptarmica var. acuminata, P. echinatum, and Xanthium italicum) were newly documented in Korea. The present findings establish an updated taxonomic framework for Golovinomyces species, thereby improving identification accuracy and enhancing disease management.

Mathematical modeling of powdery mildew disease in cashew plants with optimal control and cost-effectiveness analysis

The leaves of the vine plant, like its fruits, are used in human nutrition and meals in many countries. Grape leaves serve as an important ingredient in traditional foods. In Türkiye, the leaves of Narince, Sultani Çekirdeksiz and Yapıncak grape varieties are preferred for stuffed grape leaf production. However, pesticide residues generate a serious problem for brined vine leaves. Fungicides with different active ingredients are used to combat downy mildew and powdery mildew diseases in viticulture. Improper use of these chemicals results in serious residue problems on product surfaces. Such cases pose serious threats to human health and the environment. This study used the marker-Assisted Selection (MAS) method to identify individuals containing genes resistant to Plasmopara viticola in grape genotypes obtained through hybridization. The presence of the Rpv3 gene in hybrid individuals was examined. Total nucleic acids were extracted from fresh leaves of the plants, and the regions related to the Rpv3 gene were amplified on the genomic DNA with GF18-06/GF18-08 primers. PCR products were visualized using an agarose gel electrophoresis system, and allele gene sizes were also determined by fragment analysis. MAS method yielded 27 genotypes with the Rpv3 gene. DNA sizes were also confirmed by fragment analysis. The promising genotypes were selected for future studies.

Caffeic acid O-methyltransferase (COMT) is a multifunctional enzyme involved in lignin biosynthesis and plays an important role in various primary and secondary metabolic pathways, including the plant stress response. In this study, we identified 37 AsCOMT genes from the oat (Avena sativa) whole-genome database, which are distributed across 11 chromosomes. Phylogenetic analysis grouped these genes into two major subfamilies, indicating that they are highly conserved during evolution and share close relationships with COMT genes from Zea mays and Oryza sativa. Cis-acting elements analysis revealed a rich presence of regulatory motifs related to plant hormone signaling and stress responses. Expression profiling of different oat varieties infected with powdery mildew and leaf spot disease showed significant upregulation or downregulation of several AsCOMT genes (e.g., AsCOMT14, AsCOMT22, AsCOMT24, AsCOMT27). Moreover, disease-resistant oat varieties have higher lignin contents compared to susceptible varieties. Overexpression of AsCOMT23 and AsCOMT27 in tobacco leaves resulted in significantly increased lignin content, highlighting the potential of these genes in lignin biosynthesis. These results offer a preliminary exploration of the role of AsCOMT in both lignin synthesis and the plant stress response, laying the groundwork for further functional studies and potential applications in oat breeding.

The experiment was conducted during June, 2021 to September, 2021 at the Experimental Farm of Department of Vegetable Science, College of Horticulture & Forestry, Neri, Hamirpur, Himachal Pradesh, India with aim to identify downy and powdery mildew resistant genotype in cucumber. Twenty genotypes of cucumber were evaluated in Randomized Complete Block Design during rainy season (June–September), 2021. During periodic survey, downy mildew and powdery mildew diseases recorded in the field. Percent disease index in all genotypes of cucumber for downy mildew and powdery mildew ranged between 9.53–52.77 and 6.78–36.66, respectively. Maximum Percent disease index for downy mildew was observed in LC-C-2-21 (52.77) and minimum in LC-C-9-21 (9.53), whereas maximum Percent diseases index for powdery mildew was observed in LC-C-10-21(36.66) and minimum in Solan Srijan (6.78). Seven genotypes viz., LC-C-4-21, LC-C-6-21, LC-C-7-21, LC-C-9-21, LC-C-12-21, LC-C-14-21, Solan Srijan were found resistant and LC-C-2-21, LC-C-10-21 were susceptible to downy mildew diseases and rest of genotypes were found to be moderately resistant to disease. None of genotype was observed to be immune, resistant and highly susceptible to powdery mildew diseases. Two genotypes were found moderately resistant while ten genotypes were moderately susceptible and eight genotypes viz., LC-C-2-21, LC-C-3-21, LC-C-4-21, LC-C-7-21, LC-C-10-21, LC-C-14-21, LC-C-15-21, LC-C-16-21were susceptible to powdery mildew. From our study, LC-C-9-21 and Solan Srijan genotypes were recommended to farmer for getting higher production under low hill of Himachal Pradesh and to breeder for further resistance breeding programme.

Wheat powdery mildew disease prevalence across the Hindukush region of Pakistan during the four years period of 2019 to 2022

Map-based cloning revealed that the mutation in a highly conserved amino acid of the CsPBGD, which encodes porphobilinogen deaminase, causes the phenotype of leaf necrosis and enhanced resistance to powdery mildew and gray mold in cucumber. Lesion mimic mutants (LMMs) are valuable genetic resources for studying programmed cell death (PCD) and disease resistance. Although a number of genes controlling lesion mimic have been identified in model species, none have been mapped or cloned in cucumber. Here, we identified two cucumber mutants, C1173 and C2123, which exhibit leaf necrosis due to PCD. Genetic analysis revealed that these phenotypes are controlled by two semi-dominant loci, ln1 and ln2, respectively. Both mutants were heterozygous, as homozygous dominants were lethal (one caused cotyledon etiolation lethality; the other was unobtainable). Fine mapping placed the ln1 locus within a 54.1kb region on chromosome 3. Further investigation revealed ln1 and ln2 were allelic mutations, with CsPBGD (CsaV3_3G031800), encoding porphobilinogen deaminase, identified as the candidate gene for both mutants. Mutations in CsPBGD resulted in amino acid substitutions, Ala314Val in ln1 and Arg197Lys in ln2, disrupting enzyme activity and altering H₂O₂ accumulation. CsPBGD expression was significantly reduced in various organs of ln1. VIGS of CsPBGD in both cucumber and tobacco successfully displayed the leaf necrosis phenotype. CsPBGD proteins from both mutants and wild type (WT) were localized in chloroplasts. The mutants exhibited significantly enhanced resistance to powdery mildew (Podosphaera xanthii) and gray mold disease (Botrytis cinerea). Further studies showed that CsPBGD expression in the mutant was significantly more downregulated than in WT after P. xanthii infection, alongside increased H₂O₂ accumulation. This study is the first to characterize and clone CsPBGD in cucumber, revealing its involvement in resistance to disease.

By employing machine-learning models, this study utilizes agronomical and molecular features to predict powdery mildew disease resistance in Barley (Hordeum Vulgare L). A 130-line F8-F9 barley population caused Badia and Kavir to grow at the Gonbad Kavous University Research Farm on three planting dates (19 November, 19 January, and 19 March), with three replicates in 2018/2019 and 2019/2020. The study employed RReliefF, MRMR, and F-Test feature selection algorithms to identify essential phenotype traits and molecular markers. Subsequently, Decision Tree, Random Forest, Neural Network, and Gaussian Process Regression models were compared using MAE, RMSE, and R2 metrics. The Bayesian algorithm was utilized to optimize the parameters of the machine-learning models. The results indicated that the Neural Network model accurately predicted powdery mildew disease resistance in barley lines. The evaluation based on high R2 values, as well as low MAE and RMSE, highlighted the efficacy of these models in identifying significant phenotype traits and molecular markers associated with disease resistance. The findings demonstrate machine learning models’ potential in accurately predicting powdery mildew disease resistance in Barley. The neural network model specifically showed excellent results in this area because it managed to identify critical phenotypic traits and molecular markers very well. This research highlights the importance of combining AI with molecular markers for improved disease resistance and other desirable crop traits during plant breeding.

Agricultural production is crucial for nutrition, but it frequently faces challenges such as decreased yield, quality, and overall output due to the adverse effects of diseases and pests. Remote sensing technologies have emerged as valuable tools for diagnosing and monitoring these issues. They offer significant advantages over traditional methods, which are often time-consuming and limited in sampling. High-resolution images from drones and satellites provide fast and accurate solutions for detecting and diagnosing crops' health and identifying pests and diseases affecting them. The research focused on the early detection of Cercospora leaf spot (Cercospora beticola Sacc.) and powdery mildew (Erysiphe betae (Vaňha) Weltzien), which cause significant economic losses in sugar beet before visible symptoms emerge. The study was accomplished by capturing images of uncrewed aerial vehicle (UAV) in field conditions. To effectively evaluate different detection methods in agricultural contexts, the study targeted two key areas: (1) monitoring Cercospora in fields without pesticide application, utilizing the Metos climate station early warning system alongside UAV-based image analysis, and (2) monitoring powdery mildew, which involved visual disease detection and targeted spraying based on UAV image processing. Trial plots were established for this purpose, with six replications for each method. UAV-based images show that Normalized Difference Vegetation Index values in leaves decreased before disease onset. This change is an important warning sign for the emergence of the disease. Additionally, the study demonstrated that early detection of diseases is possible using K-nearest neighbors and logistic regression algorithms, exhibiting high discrimination and predictive accuracy.

Garden pea (Pisum sativum L.) is crucial in sub-Saharan Africa (SSA), serving both local consumption and export. Its production, however, faces significant challenges mainly due to powdery mildew (Erysiphe pisi), which is responsible for yield losses of up 60%. The objective of this study was to determine the optimum point of N fertiliser interaction with planting densities, for control of powdery mildew disease in garden pea. Treatments included N rates at 0, 15, 30, and 60 kg-1; mode of application (foliar or root base) and plant density (45 cm x 15 cm and 45 cm x 7.5 cm). The treatments were laid out in a randomised complete block design (RCBD), replicated four times. Results showed that disease severity and incidence increased along with N application and plant density; however, yield reduced at both high N rate (60 kg N ha-1) and in the control (0 kg N ha-1) rates. Fertiliser intensity significantly influenced powdery mildew occurrence, pod yield, and plant branches in garden peas, underscoring the need for strategic N management and planting density for sustainable disease management. The study identified 30 kg N ha-1 applied either by foliar or root application, together with 45 cm x 15 cm plant spacing as the most effective combination; which effectively reduced powdery mildew incidence; while improving crop yield.

The present investigation was conducted during two consecutive summer seasons (February to April) of 2022 and 2023 at Regional Agricultural Research Station, Polasa, Jagtial, Telangana (505529), India. The aim of the study was to determine ecofriendly, cost effective and potential disease management strategies for management of root rot and powdery mildew diseases in sesame. The investigation unveiled that all the three tested modules are significantly superior over control in suppressing the disease in randomized block design with five replications. Among the tested modules, Module 3, seed treatment with Trichoderma asperellum @ 10 g kg-1 + soil application of enriched Trichoderma (2.5 kg Trichoderma asperellum + 100 kg Vermicompost) @ 250 kg ha-1 + spray of Tebuconazole 50% + Trifloxysrobin 25% @ 0.5 g l-1 at 30–35 DAS and second spray at 50–60 DAS showed the highest reduction of root rot (% DI=78.59%) and powdery mildew (PDI=76.30%) over the untreated control with highest seed yield ha-1 (776.8 kg ha-1) and B:C ratio of 3.22 followed by module, M2: Seed treatment with carbendazim @ 2 g l-1 + spray of Tebuconazole 50% + Trifloxystrobin 25% @ 0.5 g l-1 at 30–35 DAS and second spray @ 0.5 g L-1 at 50–60 DAS. This integrated disease module can be used for the effective management of root rot and powdery mildew diseases in sesame and ensuring sustained yields, particularly in the Northern Telangana Zone in the state of Telangana.

Grape cultivation is playing an important role in global agriculture, it effect on economy and substance of various societies in worldwide. The production of grape and grapevine has been a challenging work since a longtime because of different type of diseases with common observations like bacteria, fungi and other viruses which employ separate or special infection technic and evasion system. Among fungi diseases powdery mildew and black rot are the well-known everywhere. These diseases not only compromise on quality of grape yield production but also effect on economic growth of farmer and vineyard manager. The diagnosis of diseases, such as grape leaf disease, on grape plantations plays a vital role in precision agriculture. When machine learning is applied to images of grape leaves, distinguishing between healthy and diseased samples with a high degree of precision becomes possible, which contributes to higher yields and improved qualities of the crops. This research aims to review grape leaf diseases, which include anthracnose, black rot, mites, and downy mildew, and the methodologies implemented for disease detection, e.g., visual, RS, ML, DL, and metaheuristic algorithms. On the basis of an analysis of 150 papers published between 2012 and 2022, the challenges associated with the current approaches are identified and categorized. This study also provides suggestions for increasing the precision and efficiency of grape leaf disease diagnosis, which may have profound effects on the agricultural industry. This paper provides a very informative review of the existing methods used for the detection of diseases in grape leaves, indicating possibilities for advancements in new detection techniques and improvements in current practices.