Global growth in soilless plant production systems, coupled with an increase in the soilless production of many traditional field-grown horticultural crops, has substantially increased demand for soilless substrates. This demand, as well as increasing interest in reducing industry dependence on peat, has prompted growers to incorporate non-peat materials into their substrates, such as engineered wood fibers (WFs). While WFs have shown potential to enhance the suppressiveness of peat against Rhizoctonia solani, the breadth and mechanisms of this suppression remain unclear. Existing evidence suggests WF effects on substrate microbiomes may play a role: other substrate amendments, such as straw, can increase microbiome diversity, and more diverse microbiomes can be disease suppressive. Here, we evaluated the effects of three engineered pine WF-amendments on disease suppression and microbiome composition using Globisporangium ultimum root rot of chrysanthemum (Chrysanthemum × morifolium) as a model system. The three WF-amendments used in this study were processed using either disc refinement, screw-extrusion, or hammer-milling. Results indicate that hammer-milled and extruded WFs reduced Globisporangium root rot in chrysanthemums and maintained chrysanthemum growth equal to grower standard media in the absence of Globisporangium. 16s rRNA and ITS amplicon sequencing data of substrate samples revealed that fungal and bacterial alpha diversity did not increase in any WF-amended substrates compared to peatlite standards and was not correlated to disease severity in most treatments. However, some microbiome composition differences were driven by WF amendment type, suggesting that WF-driven community turnover could relate to disease suppression.
Hops are a culturally and economically important crop with centuries of use. The primary harvested component is the hop cone (female flower), which undergoes physiological and chemical changes during development. To better understand the relationship between developing hop cones and their associated microbes, this study utilized amplicon-based sequencing of the internal transcribed spacer 1 (ITS1) and the 16S regions to characterize the associated fungal and bacterial communities, respectively. By sampling developing cones (i.e. bract or burr tissues) across ten successive weeks, as well as rhizomes the following year, this study presents a preliminary profiling of the hop cone and rhizome microbial communities. Fungal diversity of the hop cone was found to vary throughout development (R 2 = 0.37, p < 0.0001), with diversity decreasing concomitant with the emergence of Diaporthe humulicola. Both fungal and bacterial communities varied between cones and rhizome, with a more variation in composition between tissues being observed in the bacterial communities (fungal: R 2 = 0.14, bacterial: R 2 = 0.24, p < 0.0001). A core microbiome across the weekly sampling of the hop cone and tissue types was identified for both the fungal and bacterial communities, with Alternaria, Diaporthe, and Vishniacozyma species among the fungal core microbiome and Pseudomonas, Pantoea, and Sphingomonas species among the bacterial. This work provides novel insights into the temporal patterns of the hop cone microbiome and the hop rhizome microbiome, as well as the observation of the emerging hop pathogen Diaporthe humulicola potentially reducing the abundance of other fungi in the hop cone.
Here, we present the first complete chromosome-scale genome assembly of a Brazilian Cunninghamella blakesleeana strain UFAC-CB2.1. We combined Nanopore long reads with high-quality Illumina paired-end reads to produce a final assembly comprising eight chromosomes (seven nuclear and one mitochondrial), totaling 33,158,829 bp. Ab initio gene prediction identified 10,659 protein-coding genes. We also predicted the secretome and effectorome, detecting at least 609 secreted proteins and 432 candidate secreted effector proteins. This telomere-to-telomere genome assembly of a poorly investigated fungus will shed light on the genetics of the species and genus, opening opportunities for further research in agricultural, biotechnological, and medical applications.
Alternaria late blight (ALB), caused by Alternaria spp., is one of the most prevalent and economically important diseases affecting pistachio production in California. Fungicide applications remain the primary strategy to control ALB. The fungicides Quinone outside Inhibitors (QoI) and Succinate Dehydrogenase Inhibitors (SDHI) are widely used in California. This study established two duplex real-time quantitative PCR (qPCR) approaches to determine the proportions of the mutant genotype G143A in the pathogen mitochondrial cytochrome b (cytb) gene (P G143A ) and the mutant genotype H134R in the succinate dehydrogenase subunit C (sdhC) gene (P H134R ). Specific primers and probes were designed to target the mutant and wild type genotypes associated with QoI and SDHI resistance. Strong correlations between the known proportions of mutant DNA in the prepared mixtures and the proportions estimated by qPCR demonstrated that the assays were suitable for quantifying QoI and SDHI resistance-associated genotypes. Multi-year surveys for fungicide resistance in pistachio orchards at a region-wide scale in California were conducted. Leaf samples collected from 2021 to 2023 were processed with the SYBR Green I technique and those collected from 2024 to 2025 were processed with the TaqMan technique in qPCR. A total of 195 and 182 samples were used for quantification of resistance levels to QoI and SDHI, respectively. Survey results demonstrated that 17.9 and 65.6% samples showed high and very high resistance levels to QoI, respectively. For SDHI, the very high resistance category represented the largest proportion of samples (45%) and was significantly greater than the other categories.
Trichoderma spp. can suppress plant diseases and increase crop growth. However, few studies have tested their effects on lettuce grown in pathogen-infested soil at the field scale. This study evaluated the effects of the commercial strain T. afroharzianum T22 on lettuce in a field infested with the soilborne pathogen Verticillium dahliae. Field experiments were conducted over two consecutive seasons by applying T. afroharzianum T22 to soil as the active ingredient of Trianum-P. At harvest, disease severity was rated, lettuce head weight was measured, and rhizosphere soil was collected. The amount of T. afroharzianum T22 and V. dahliae in sampled soil was measured using previously developed qPCR assays. Verticillium wilt disease severity and the abundance of V. dahliae were not significantly different between control and T. afroharzianum T22-treated plots. T. afroharzianum T22 application significantly increased lettuce yield in both seasons, and T. afroharzianum T22 was detected only in the soil of treated plots. The outcomes of this research demonstrate that T. afroharzianum T22 can significantly increase lettuce yield in pathogen-infested soil and will provide lettuce growers with additional options for improving crop productivity.The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2026.
A maximum residue limit (MRL) is a statutory limit of analyte concentration for a food or feed. An MRL for a given pesticide may vary from country to country, potentially creating technical barriers to trade when these limits are incongruous. Approximately half of the hops produced in the United States are exported, with the EU being the most important market and also having the most restrictive MRLs for numerous pesticides. Quinoxyfen historically has been central in fungicide programs for management of hop powdery mildew (Podosphaera macularis), but there is concern that loss of a harmonized MRL for quinoxyfen (currently 3 ppm) may create a barrier to export. We conducted 5 years of field studies to develop guidance on fungicide programs that are EU export-compliant, limit use of a single fungicide mode of action, and maximize efficacy without use of quinoxyfen. Plants that received fluopyram + tebuconazole during bloom and the juvenile stages of cone development had the least powdery mildew on cones, which were statistically comparable to disease levels when plants received quinoxyfen at the same timing. On leaves, the efficacy of MRL-compliant or MRL-exempt fungicides depended on the specific product and application interval. The most effective programs utilized trifloxystrobin on a 7-day or 10-day interval, or banda de Lupines albus doce on a 7-day interval, providing disease control comparable to a rotation of quinoxyfen and myclobutanil. These findings offer alternatives to quinoxyfen, provided that specific fungicides are used at and after bloom and that application intervals are appropriately matched for each fungicide.The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2026.
European canker, caused by Neonectria ditissima, is a destructive disease of apple in cool and humid regions worldwide, yet its presence has not been previously documented in Virginia. The objectives of this study were to confirm the causal agent, assess pathogenicity on apple twigs and fruit, and generate high-quality genomic resources to support future investigations of this emerging pathogen in the Mid-Atlantic region. Isolates obtained from cankered branches were identified as N. ditissima based on morphology and multilocus phylogenetic analysis. Pathogenicity tests on apple twigs and fruit reproduced characteristic canker lesions and fruit rot, respectively, fulfilling Koch's postulates. Two representative isolates were selected for de novo genome sequencing using Oxford Nanopore long-read data combined with RNA-seq–guided annotation. The resulting assemblies (45.6 to 46.1 Mb) were highly contiguous, with 19 to 21 chromosome-scale sequences assembled with >96% BUSCO completeness scores. Genome mining revealed 47 to 48 putative secondary metabolite biosynthetic gene clusters, including clusters putatively associated with polyketide, nonribosomal peptide, and terpene biosynthesis. Several clusters were previously reported to be transcriptionally active during growth on apple tissues, suggesting potential roles in host interactions. This study documents the first confirmed occurrence of N. ditissima on apple in Virginia and provides improved genomic resources that expand current knowledge of this pathogen's biology. These data establish a foundation for future work on population genomics, virulence mechanisms, and host–pathogen interactions associated with European canker in the Mid-Atlantic United States. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
As members of the Didymellaceae family within the Pleosporales order of fungi, species of the genus Didymella are notable for their global distribution. This genus includes plant pathogens, endophytes, and saprobes, as well as strains that are either harmful to human health or have potential applications in disease treatment. Therefore, Didymella species present a complex duality for both plants and humans. However, research on this genus remains limited and lacks a comprehensive, systematic investigation. This review article introduces key members of the genus Didymella that cause plant diseases, promote plant growth, impact human health, or offer therapeutic potential for human diseases. It discusses the genomics and key genes of the genus, highlighting important metabolic substances associated with Didymella that exhibit inhibitory effects on plant pathogens and demonstrate cytotoxic activity against human cancer cells. Building on the mechanisms of host-pathogen interactions, the article addresses both host resistance and virulence factors affecting plant hosts. Furthermore, it reviews pathogen detection methods within the genus Didymella, the epidemiology of crop diseases, the antifungal activity for the genus Didymella, and the associated inhibitory mechanisms. Lastly, it explores integrated disease management strategies, with a focus on resistant cultivars and agronomic practices.Copyright (c) 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Ralstonia solanacearum race 3 biovar 2 (R3Bv2; phylotype IIB, sequevars 1 and 2) is a bacterial plant pathogen internationally recognized as a quarantine pest due to its ability to cause potato brown rot and wilt in cool-temperate climates. It has recurrently been introduced to the United States through the importation of Pelargonium spp. (geranium) cuttings, in which it causes latent infections that often harbor low pathogen titers, which challenge the limits of detection by real-time PCR. Here, we developed a multiplex digital PCR (dPCR) assay that incorporates four sets of primers and probes to allow for improved confidence in the detection of a low-titer infection and for discrimination of the two subpopulations that comprise the R3Bv2 lineage (i.e., IIB-1 and IIB-2). Validation experiments indicated that the multiplex dPCR assay was approximately a magnitude of order more sensitive than real-time PCR, with a limit of detection corresponding to 0.3 genome equivalent copies per microliter in a plant DNA extraction. It also displayed 100% accuracy with a comprehensive panel of pure culture DNA ( N = 139) spanning the diversity of the R. solanacearum species complex and related pathogens. Finally, the ability of the method to confirm R. solanacearum R3Bv2 in both naturally and artificially infected geranium stem cuttings with high real-time PCR cycle quotient values was demonstrated. We expect that the multiplex dPCR assay developed here will strengthen agricultural biosecurity by improving confidence in the detection of low-titer, latent infections by R. solanacearum R3Bv2 that challenge traditional diagnostic techniques. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Dry Root Rot (DRR), caused by the soil-borne fungal pathogen Macrophomina phaseolina, is an emerging threat to global chickpea production. Screening large chickpea germplasm collections, mutant populations, and transgenic lines for DRR resistance remains challenging due to manual disease scoring, which is subjective, labor-intensive and often prone to rating bias. To address this, our laboratory has previously developed RootRotAI 2.0, a set of deep learning models developed using TensorFlow to support automated detection and assessment of DRR from images of chickpea collected under laboratory conditions. In the current study, we focus on the high-throughput deployment of these models by developing a mobile application, RootRotAI 2.2, and, a web application, RootRotAI 2.1, to facilitate a user-friendly interface and broader accessibility. These applications allow users to upload or capture images to automatically diagnose and assess DRR severity. RootRotAI 2.2 and 2.1 integrate two transformer-based multitask deep learning models now optimized and deployed via TensorFlow Lite for efficient on-device inference. These tools can be accessed via https://github.com/scipdatabase/RootRotAI and mobile app is available in play store. The application supports three imaging modalities, a handheld camera, a root scanner, and a light microscope each with modality-specific backgrounds. These tools offer a real-time assessment capabilities through an offline mobile mode and a high-capacity platform for large-scale data analysis via the online web application. While image-based disease detection tools are common, RootRotAI serves as a novel and key digital resource for the identification of DRR in chickpea, ultimately facilitating crop improvement programs and contributes to sustainable agriculture.
Rice blast, caused by the ascomycete Magnaporthe oryzae, remains a major threat to rice production. Although major resistance ( R) genes have been identified and deployed, their effectiveness depends on the presence of matching avirulence ( AVR) genes in the pathogen. In this study, we surveyed Arkansas commercial rice fields to assess the frequency and distribution of eight AVR genes: AVR-Pita1, AVR-Pik, ACE1, AVR-Pi9, AVR-Pib, AVR-Pii, AVR-Pizt, and AVR-Pia. A total of 227 M. oryzae isolates were collected during the 2024 and 2025 growing seasons from 15 counties and 5 cultivars. Eight AVR genes were tested using polymerase chain reaction with gene-specific primers. AVR-Pita1 and AVR-Pizt were present in all isolates, whereas AVR-Pib, AVR-Pi9, and ACE1 were detected in 226 isolates and AVR-Pii was detected in 225 isolates. AVR-Pik and AVR-Pia were absent. Three distinct AVR profile groups were identified: A ( AVR-Pita1 and AVR-Pizt), B ( AVR-Pita1, AVR-Pizt, AVR-Pib, AVR-Pi9, and ACE1), and C ( AVR-Pita1, AVR-Pizt, AVR-Pib, AVR-Pii, AVR-Pi9, and ACE1), with profile C representing the predominant combination of AVR genes in over 99% of the isolates. No significant variation in the AVR profiles was associated with the host genotype. These results reveal a highly uniform AVR gene composition in the Arkansas M. oryzae population and provide insights into the potential effectiveness of deployed R genes, supporting breeding efforts focused on durable resistance and economically sustainable blast management in the state. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2026.
Peronospora sparsa is an oomycete pathogen causing downy mildew in species of Rosa and Rubus, including economically important fruit crops. Despite its agricultural significance, genomic resources for this pathogen remain limited. Here we report the first complete mitochondrial genomes of P. sparsa, assembled from a historical herbarium specimen collected in 1899 and from a contemporary isolate obtained in 2021. The circular mitochondrial genomes were 36,924 bp and 36,980 bp in length and contained 64 annotated genes, including 40 protein-coding genes, 22 transfer RNAs, and 2 ribosomal RNA genes. Comparative analysis revealed only 41 single-nucleotide polymorphisms and 3 small insertions-deletions between the genomes, indicating extremely low mitochondrial divergence over more than a century. These mitogenomic resources provide a foundation for improved molecular diagnostics, enable reliable discrimination among species within the Sparsa clade, and facilitate molecular surveillance and epidemiological studies of this economically important plant pathogen.Copyright (c) 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
Airborne inoculum monitoring is becoming increasingly common as a disease monitoring and management tool. Approaches typically focus on monitoring a single pathogen rather than all pathogens of importance in a system. To increase efficiency, actively managed pathogens should be monitored simultaneously. It is also critical to examine the utility and positioning of different samplers for pathogens being monitored. The study objectives were to optimize three qPCR assays into a single multiplex assay to detect Botrytis cinerea, Erysiphe necator, and Plasmopara viticola; evaluate the effect of sampler height on detection efficiency; and compare sampler performance among the rotating-arm sampler, SporeCam, and Burkard. The qPCR multiplex assay was found to be sensitive to 10 fg of DNA for each of the three pathogens. During the sampling period of berry development to late veraison, the rotating-arm samplers successfully captured the pathogens at all heights (0.6, 1.4, and 1.8 m) and in- versus out-of-vineyard positions, with significant differences in collection only for B. cinerea. Detection of P. viticola was negatively correlated between the SporeCam and rotating-arm samplers (ρ = −0.48) but positively correlated between rotating-arm samplers and Burkard (ρ = 0.53). Detection of B. cinerea was positively correlated between the SporeCam and rotating-arm samplers (ρ = 0.39). E. necator was never detected by the Burkard but was detected by rotating-arm samplers each season, which were positively correlated with the SporeCam (ρ = 0.38). These findings advance integrated airborne multi-pathogen inoculum detection in vineyards and highlight the need for refinement of sampling technologies for real-time disease management. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Azoxystrobin (AZ), pyraclostrobin (PYR), and trifloxystrobin (TFR) are widely used quinone outside inhibitor (QoI) fungicides for managing leaf spot and leaf blight of soybean. However, QoI resistance is widespread among fungal field populations, mainly due to point mutations (G143A, F129L, and G137R) in the cytochrome b-encoding cytb gene. This study employed computational molecular docking to screen three QoIs for binding to wild-type fungal Cytb and single-, double-, and triple-substitution variants reported to be associated with resistance to QoI fungicides. Ubiquinol docking revealed reduced binding affinity and altered contact residues in mostly double and triple variants, suggesting potential fitness penalties and impaired electron transport. Among QoIs, PYR exhibited the strongest affinity with wild-type Cytb (-8.63 kcal/mol). The number of Cytb residues predicted to be in contact with the tested fungicides varied from 4 to 19, with PYR having the highest number. The substitutions dramatically altered the number of contact residues and the predicted binding energy by selectively favoring the binding of one type of QoI while disfavoring another. The combined F129L and G137R substitutions were predicted to completely block the binding of TFR but mildly reduce the binding of AZ and PYR. Conversely, the triple substitution was predicted to be most effective against AZ, whereas the G137R substitution was found to be most effective against PYR. Identifying predominant Cytb mutations in field fungal populations can support targeted and sustainable disease management by enabling rapid prescreening of QoI fungicide efficacy and predicting resistance development, stability, and sensitivity to existing and novel QoIs.Copyright (c) 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Early detection of fire blight in apple orchards is critical for effective disease management and sustainable crop production. This study explores the use of a portable spectral device combined with machine learning techniques to classify disease status and identify key spectral features associated with biotic stress. Vegetation health was assessed using NDVI values derived from spectral data, which showed a significant decrease from the healthy stage (mean NDVI = 0.7518) to the presymptomatic stage (mean NDVI = 0.7307, P < 0.001). Random forest classification achieved an overall accuracy of 92% in distinguishing healthy and infected samples, with an area under the receiver operating characteristic curve of 0.94. Models trained within specific treatment groups demonstrated consistent performance, with accuracies ranging from 81 to 90% depending on the algorithm and treatment type. Key spectral features identified by random forest models primarily spanned the near-infrared region (770 to 830 nm), highlighting their importance in capturing physiological changes associated with disease progression. However, unsupervised learning suggested minimal impact of chemical treatments on spectral patterns, with spectral differences largely driven by inoculation status. Although temporal analysis using long short-term memory (LSTM) networks demonstrated potential for disease progression tracking, results were limited due to the lack of laboratory-confirmed infection data. Future work will focus on validating the identified spectral features for fire blight detection, integrating laboratory-confirmed data for enhanced temporal modeling, and exploring regression-based approaches to quantify disease severity. This research establishes a foundation for portable, scalable, and machine learning-driven solutions for early disease detection in precision agriculture. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .
A highly contiguous and complete reference genome of Cercospora cf. flagellaris, the causal agent of foliar disease on many plant hosts, including Cercospora leaf blight of soybean, was assembled using a combination of PacBio and Illumina sequencing reads. The genome assembly is 33.72 Mb in length and consists of 14 nuclear scaffolds and one mitochondrial contig. Four scaffolds have telomeric repeats on both ends and represent fully assembled chromosomes, whereas nine scaffolds represent partially assembled chromosomes with telomeric repeats on one end. The assembly has an N50 of 2.90 Mb and an L50 of 5 scaffolds. Genome annotation identified 11,268 genes, of which 947 and 360 were predicted to encode secreted proteins and effectors, respectively. Additionally, 512 genes were predicted to encode carbohydrate-active enzymes, and 60 biosynthetic gene clusters were annotated. Taken together, this annotated genome assembly will be a valuable resource for genomics, host–pathogen interactions, and population biology research in this economically important pathosystem. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Crown gall disease, typically caused by tumorigenic Agrobacterium species, poses a significant threat to stone fruit crops worldwide. The disease results in compromised plant development and mortality. In the West Bank, almond (Prunus dulcis) represents the leading stone fruit crop. Recent reports have indicated widespread crown gall infections, however, no genomic resources have been available for local pathogenic Agrobacterium strains. Here, we report the first complete genome sequence of Agrobacterium radiobacter strain A23, isolated from gall-infected almond trees in Hebron, West Bank. We obtained a high-quality assembly of 5,551,953 bp comprising one circular chromosome, one linear chromid, and three plasmids. Phylogenetic analysis and overall genomic relatedness indices confirmed strain A23 as Agrobacterium radiobacter. Comprehensive annotation revealed key virulence determinants, including a complete T-DNA region, vir genes, and conjugative transfer machinery (tra and trb) genes located on the tumor-inducing plasmids. This genomic resource provides valuable insights into the pathogenicity mechanisms of crown gall disease in an economically important crop.
Chemical protection has been a key component of boxwood blight (Calonectria pseudonaviculata, Cps) management programs, but each application of fungicides only protects the iconic evergreen landscape plant for 2 to 3 weeks at best. The objective of this study was to evaluate the potential of six film-forming anti-desiccant products-Anti-Stress 2000, AquaLock, Moisture-Loc, TransFilm, Vapor Gard, and Wilt-Pruf-for managing boxwood blight in lab experiments and in production fields. In lab experiments with container-grown Buxus sempervirens 'Justin Brouwers', TransFilm, Vapor Gard, and Wilt-Pruf consistently outperformed the other three products in suppressing Cps infection, sporulation, and spore release. Specifically, these three top performers reduced blight incidence by >= 90.7% when they were applied 1 day before plants were inoculated with Cps. Likewise, they reduced conidial count by >= 76.1% when applied 6 days after inoculation. Both Wilt-Pruf and TransFilm provided significant but lesser degrees of protection to field-grown boxwood crops in western North Carolina compared with their performance in the lab experiments. Comparatively, Wilf-Pruf had more consistent field performance than TransFilm. TransFilm protected B. sempervirens ("American") only when applied monthly and B. sempervirens 'Vardar Valley' only when applied every 3 months. Wilt-Pruf protected both boxwood crops at both the monthly and 3-month application intervals.Copyright (c) 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
The composition and structure of plant-associated microbial communities are shaped by abiotic and biotic factors, with host-related traits and plant–microbe interactions playing key roles. Although studies on soil-based cultivation systems have shown that pathogen infection can disrupt plant microbial communities, little is known about how pathogen interactions affect hydroponically grown crops, particularly leafy greens. Despite the controlled conditions of hydroponic cultivation, these systems remain vulnerable to waterborne pathogens such as Pythium and Globisporangium spp. These oomycetes can rapidly spread through recirculated nutrient solutions and cause severe root diseases. This study aimed to examine how Pythium aphanidermatum inoculation affects the bacterial and fungal communities in the roots of hydroponically grown lettuce in deep-water culture systems under research greenhouse conditions. Our findings revealed that root inoculation with P. aphanidermatum significantly impacted lettuce biomass and microbial communities. Bacterial and fungal alpha diversity and evenness were significantly higher in inoculated roots compared with noninoculated controls. Beta diversity and network analyses indicated different modes of microbial response to pathogen invasion. Bacterial communities responded with compositional shifts regardless of disease severity. In contrast, fungal communities showed dramatic reorganization of network structure. Differential abundance and network analyses identified Pseudomonas and Olpidium as taxa consistently associated with Pythium-inoculated roots. A deeper understanding of hydroponics-associated microbial communities, their interactions, and functional roles will allow us to leverage these relationships for improved food security and environmental sustainability. Moreover, understanding the microbial composition dynamics during pathogen infection can have significant implications for disease management and the effective use of biological control agents. [Formula: see text] Copyright © 2026 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .
Hop downy mildew, caused by Pseudoperonospora humuli, is routinely managed using fungicides. Plot-level data from fungicide efficacy trials (n = 44) in Oregon and Washington between 1997 and 2024 were analyzed in a one-stage, contrast-based, multi-treatment individual participant data (IPD) meta-analysis. Data were aggregated by fungicide mode of action (MOA), inferred from the Fungicide Resistance Action Committee (FRAC) group, and analyzed when a given MOA appeared >= 5 times. In Oregon, fungicide MOA was resolved into four overlapping groups, with the most effective group being FRAC 49 + 4, providing estimated disease control of 87.4%. In Washington, the four MOAs analyzed were more effective than the nontreated control but had similar efficacy, with estimated disease control of 67.4 to 74.8%. Trial-level disease severity had an additive and multiplicative interaction with MOA on estimated disease control in trials in Oregon or combined over both states. After controlling for trial-level disease severity, state had a nonsignificant additive effect on estimated disease control (95% confidence interval -130.7 to 70.7%). Analysis of design inconsistency indicated that relative efficacy was stable across study designs in Washington. However, design inconsistency was detected in trials in Oregon and over both states, indicating that estimated efficacy varied depending on the specific combinations of MOAs evaluated. Design inconsistency was related to high variance in certain trials, including FRAC 49 + 40. These analyses provide a foundation for designing fungicide programs that are effective and consistent with resistance management principles. The study also illustrates the value of one-stage, multi-treatment IPD meta-analytic approaches and assessing design inconsistency.The author(s) have dedicated the work to the public domain under the Creative Commons CC0 "No Rights Reserved" license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2026.
