Machine Learning Analysis of the Impact of Silver Nitrate and Silver Nanoparticles on Wheat (Triticum aestivum L.): Callus Induction, Plant Regeneration, and DNA Methylation

The objective of this study was to comprehend the efficiency of wheat regeneration, callus induction, and DNA methylation through the application of mathematical frameworks and artificial intelligence (AI)-based models. This research aimed to explore the impact of treatments with AgNO3 and Ag-NPs on various parameters. The study specifically concentrated on analyzing RAPD profiles and modeling regeneration parameters. The treatments and molecular findings served as input variables in the modeling process. It included the use of AgNO3 and Ag-NPs at different concentrations (0, 2, 4, 6, and 8 mg L-1). The in vitro and epigenetic characteristics were analyzed using several machine learning (ML) methods, including support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), k-nearest neighbor classifier (KNN), and Gaussian processes classifier (GP) methods. This study's results revealed that the highest values for callus induction (CI%) and embryogenic callus induction (EC%) occurred at a concentration of 2 mg L-1 of Ag-NPs. Additionally, the regeneration efficiency (RE) parameter reached its peak at a concentration of 8 mg L-1 of AgNO3. Taking an epigenetic approach, AgNO3 at a concentration of 2 mg L-1 demonstrated the highest levels of genomic template stability (GTS), at 79.3%. There was a positive correlation seen between increased levels of AgNO3 and DNA hypermethylation. Conversely, elevated levels of Ag-NPs were associated with DNA hypomethylation. The models were used to estimate the relationships between the input elements, including treatments, concentration, GTS rates, and Msp I and Hpa II polymorphism, and the in vitro output parameters. The findings suggested that the XGBoost model exhibited superior performance scores for callus induction (CI), as evidenced by an R2 score of 51.5%, which explained the variances. Additionally, the RF model explained 71.9% of the total variance and showed superior efficacy in terms of EC%. Furthermore, the GP model, which provided the most robust statistics for RE, yielded an R2 value of 52.5%, signifying its ability to account for a substantial portion of the total variance present in the data. This study exemplifies the application of various machine learning models in the cultivation of mature wheat embryos under the influence of treatments and concentrations involving AgNO3 and Ag-NPs.

Investigation of the Influence of Polyamines on Mature Embryo Culture and DNA Methylation of Wheat (Triticum aestivum L.) Using the Machine Learning Algorithm Method

Numerous factors can impact the efficiency of callus formation and in vitro regeneration in wheat cultures through the introduction of exogenous polyamines (PAs). The present study aimed to investigate in vitro plant regeneration and DNA methylation patterns utilizing the inter-primer binding site (iPBS) retrotransposon and coupled restriction enzyme digestion-iPBS (CRED-iPBS) methods in wheat. This investigation involved the application of distinct types of PAs (Put: putrescine, Spd: spermidine, and Spm: spermine) at varying concentrations (0, 0.5, 1, and 1.5 mM). The subsequent outcomes were subjected to predictive modeling using diverse machine learning (ML) algorithms. Based on the specific polyamine type and concentration utilized, the results indicated that 1 mM Put and Spd were the most favorable PAs for supporting endosperm-associated mature embryos. Employing an epigenetic approach, Put at concentrations of 0.5 and 1.5 mM exhibited the highest levels of genomic template stability (GTS) (73.9%). Elevated Spd levels correlated with DNA hypermethylation while reduced Spm levels were linked to DNA hypomethylation. The in vitro and epigenetic characteristics were predicted using ML techniques such as the support vector machine (SVM), extreme gradient boosting (XGBoost), and random forest (RF) models. These models were employed to establish relationships between input variables (PAs, concentration, GTS rates, Msp I polymorphism, and Hpa II polymorphism) and output parameters (in vitro measurements). This comparative analysis aimed to evaluate the performance of the models and interpret the generated data. The outcomes demonstrated that the XGBoost method exhibited the highest performance scores for callus induction (CI%), regeneration efficiency (RE), and the number of plantlets (NP), with R2 scores explaining 38.3%, 73.8%, and 85.3% of the variances, respectively. Additionally, the RF algorithm explained 41.5% of the total variance and showcased superior efficacy in terms of embryogenic callus induction (ECI%). Furthermore, the SVM model, which provided the most robust statistics for responding embryogenic calluses (RECs%), yielded an R2 value of 84.1%, signifying its ability to account for a substantial portion of the total variance present in the data. In summary, this study exemplifies the application of diverse ML models to the cultivation of mature wheat embryos in the presence of various exogenous PAs and concentrations. Additionally, it explores the impact of polymorphic variations in the CRED-iPBS profile and DNA methylation on epigenetic changes, thereby contributing to a comprehensive understanding of these regulatory mechanisms.

Correction: Helal et al. Improving Yield Components and Desirable Eating Quality of Two Wheat Genotypes Using Si and NanoSi Particles under Heat Stress. Plants 2022, 11, 1819

In the original publication [...].

Genome-wide analysis revealed the stepwise origin and functional diversification of HSDs from lower to higher plant species

Hydroxysteroid dehydrogenase (HSDs) is an oil-body sterol protein (steroleosin) with an NADP(H) binding domain that belongs to the short-chain dehydrogenase/reductase (SDR) superfamily. There are numerous studies on the characterization of HSDs in plants. However, thus far, the evolutionary differentiation and divergence analysis of these genes remain to be explored. The current study used an integrated method to elucidate the sequential evolution of HSDs in 64 sequenced plant genomes. Analyses were conducted on their origins, distribution, duplication, evolutionary paths, domain functions, motif composition, properties, and cis-elements. Results indicate that except for algae, HSD1 was widely distributed in plant species ranging from lower to higher plants, while HSD5 was restricted to terrestrial plants, and HSD2 was identified in fewer monocots and several dicot plants. Phylogenetic analysis of HSD proteins revealed that monocotyledonous HSD1 in moss and ferns appeared closest to the outgroup, V. carteri HSD-like, M. musculus HSD1, and H. sapiens HSD1. These data support the hypothesis that HSD1 originated in bryophytes and then in non-vascular and vascular plants, followed by HSD5 only in land plants. Gene structure analysis suggests that HSDs in plant species came up with a fixed number of six exons, and the intron phase was primarily 0, 1, 0, 0, and 0. Similarly, duplication analysis revealed that segmental duplications were the main reason for HSDs in plant species. Physicochemical properties suggest that dicotyledonous HSD1s and HSD5s were mainly acidic. The monocotyledonous HSD1s and HSD2s and the dicotyledonous HSD2s, HSD3s, HSD4s, and HSD6s were mainly basic, implying that HSDs in plants may have a variety of functions. Cis-regulatory elements and expression analysis revealed that HSDs in plants might have roles in several abiotic stresses. Due to the high expression of HSD1s and HSD5s in seeds, these HSDs in plants may have roles in fatty acid accumulation and degradation.

Identification of Novel QTLs Associated with Frost Tolerance in Winter Wheat (Triticum aestivum L.)

Low temperature (cold) and freezing stress is a major problem during winter wheat growth. Low temperature tolerance (LT) is an important agronomic trait in winter wheat and determines the plants' ability to cope with below-freezing temperatures; thus, the development of cold-tolerant cultivars has become a major goal of breeding in various regions of the world. In this study, we sought to identify quantitative trait loci (QTL) using molecular markers related to freezing tolerance in winter. Thirty-four polymorphic markers among 425 SSR markers were obtained for the population, including 180 inbred lines of F₁₂ generation wheat, derived from crosses (Norstar × Zagros) after testing with parents. LT₅₀ is used as an effective selection criterion for identifying frost-tolerance genotypes. The progeny of individual F₁₂ plants were used to evaluate LT50. Several QTLs related to wheat yield, including heading time period, 1000-seed weight, and number of surviving plants after overwintering, were identified. Single-marker analysis illustrated that four SSR markers with a total of 25% phenotypic variance determination were linked to LT50. Related QTLs were located on chromosomes 4A, 2B, and 3B. Common QTLs identified in two cropping seasons based on agronomical traits were two QTLs for heading time period, one QTL for 1000-seed weight, and six QTLs for number of surviving plants after overwintering. The four markers identified linked to LT₅₀ significantly affected both LT₅₀ and yield-related traits simultaneously. This is the first report to identify a major-effect QTL related to frost tolerance on chromosome 4A by the marker XGWM160. It is possible that some QTLs are closely related to pleiotropic effects that control two or more traits simultaneously, and this feature can be used as a factor to select frost-resistant lines in plant breeding programs.

Response of Maize Varieties (Zea mays L.) to the Application of Classic and Stabilized Nitrogen Fertilizers-Nitrogen as a Predictor of Generative Yield

The study presents the results of a 3-year field trial aimed at assessing the yield and efficiency indicators of nitrogen application in the cultivation of three maize cultivars differing in agronomic and genetic profile. The advantages of the UltraGrain stabilo formulation (NBPT and NPPT) over ammonium nitrate and urea are apparent if a maize cultivar capable of efficient nutrient uptake in the pre-flowering period and effective utilization during the grain filling stage is selected. Therefore, the rational fertilization of maize with urea-based nitrogen fertilizer with a urease inhibitor requires the simultaneous selection of cultivars that are physiologically profiled for efficient nitrogen utilization from this form of fertilizer ("stay-green" cultivar). The interaction of a selective cultivar with a high genetically targeted potential for nitrogen uptake from soil, combined with a targeted selection of nitrogen fertilizer, is important not only in terms of production, but also environmental and economic purposes.

Somaclonal Variation for Genetic Improvement of Starch Accumulation in Potato (Solanum tuberosum) Tubers

Starch content is one of the major quality criteria targeted by potato breeding programs. Traditional potato breeding is a laborious duty due to the tetraploid nature and immense heterozygosity of potato genomes. In addition, screening for functional genetic variations in wild relatives is slow and strenuous. Moreover, genetic diversity, which is the raw material for breeding programs, is limited due to vegetative propagation used in the potato industry. Somaclonal variation provides a time-efficient tool to breeders for obtaining genetic variability, which is essential for breeding programs, at a reasonable cost and independent of sophisticated technology. The present investigation aimed to create potato somaclones with an improved potential for starch accumulation. Based on the weight and starch content of tubers, the somaclonal variant Ros 119, among 105 callus-sourced clones, recorded a higher tuberization potential than the parent cv Lady Rosetta in a field experiment. Although this somaclone was similar to the parent in the number of tubers produced, it exhibited tubers with 42 and 61% higher fresh and dry weights, respectively. Additionally, this clone recorded 10 and 75% increases in starch content based on the dry weight and average content per plant, respectively. The enhanced starch accumulation was associated with the upregulation of six starch-synthesis-related genes, namely, the AGPase, GBSS I, SBE I, SBE II, SS II and SS III genes. AGPase affords the glycosyl moieties required for the synthesis of amylose and amylopectin. GBSS is required for amylose elongation, while SBE I, SBE II, SS II and SS III are responsible for amylopectin.

Improving Yield Components and Desirable Eating Quality of Two Wheat Genotypes Using Si and NanoSi Particles under Heat Stress

Global climate change is a significant challenge that will significantly lower crop yield and staple grain quality. The present investigation was conducted to assess the effects of the foliar application of either Si (1.5 mM) or Si nanoparticles (1.66 mM) on the yield and grain quality attributes of two wheat genotypes (Triticum aestivum L.), cv. Shandweel 1 and cv. Gemmeiza 9, planted at normal sowing date and late sowing date (heat stress). Si and Si nanoparticles markedly mitigated the observed decline in yield and reduced the heat stress intensity index value at late sowing dates, and improved yield quality via the decreased level of protein, particularly glutenin, as well as the lowered activity of α-amylase in wheat grains, which is considered a step in improving grain quality. Moreover, Si and nanoSi significantly increased the oil absorption capacity (OAC) of the flour of stressed wheat grains. In addition, both silicon and nanosilicon provoked an increase in cellulose, pectin, total phenols, flavonoid, oxalic acid, total antioxidant power, starch and soluble protein contents, as well as Ca and K levels, in heat-stressed wheat straw, concomitant with a decrease in lignin and phytic acid contents. In conclusion, the pronounced positive effects associated with improving yield quantity and quality were observed in stressed Si-treated wheat compared with Si nanoparticle-treated ones, particularly in cv. Gemmeiza 9.

Dynamic effects of fiscal and monetary policy instruments on environmental pollution in ASEAN

This study aims to re-examine the impacts of monetary and fiscal policy on environmental quality in ASEAN countries from 1990 to 2019. We utilized the panel and time series NARDL approach to explore the long-run and short-run estimates at a regional level and country level. ASEAN regional-wise analysis shows that contractionary monetary policy reduces the CO2 emissions, while expansionary monetary policy enhances CO2 emissions in the long run. The long-run coefficient further confirms that expansionary fiscal policy mitigates CO2 emissions in ASEAN. The impact of expansionary monetary and fiscal policy on CO2 emissions is positive and significant, while contractionary monetary and fiscal policy have an insignificant impact on CO2 emissions in the short run. ASEAN country-wise analysis also reported the country-specific estimates for the short and long run. Some policies can redesign in light of these novel findings in ASEAN economies.

Roles of Exogenous α-Lipoic Acid and Cysteine in Mitigation of Drought Stress and Restoration of Grain Quality in Wheat

Cysteine (Cys) and α-lipoic acid (ALA) are naturally occurring antioxidants (sulfur-containing compounds) that can protect plants against a wide spectrum of environmental stresses. However, up to now, there are no conclusive data on their integrative roles in mitigation of drought stress in wheat plants. Here, we studied the influence of ALA at 0.02 mM (grain dipping pre-cultivation treatment) and Cys (25 and 50 ppm as a foliar application) under well watered and deficit irrigation (100% and 70% of recommended dose). The results showed that deficit irrigation markedly caused obvious cellular oxidative damage as indicated by elevating the malondialdehyde (MDA) and hydrogen peroxide content (H₂O₂). Moreover, water stressed plants exhibited multiple changes in physiological metabolism, which affected the quantitative and qualitative variables of grain yield. The enzymatic antioxidants, including superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT) and peroxidase (POX) were improved by Cys application. SOD and APX had the same response when treated with ALA, but CAT and POX did not. Moreover, both studied molecules stimulated chlorophyll (Chl) and osmolytes' biosynthesis. In contrast, the Chl a/b ratio was decreased, while flavonoids were not affected by either of the examined molecules. Interestingly, all above-mentioned changes were associated with an improvement in the scavenging capacity of reactive oxygen species (ROS), leaf relative water content (RWC), grain number, total grain yield, weight of 1000 kernels, gluten index, falling number, and alveographic parameters (P, W, and P/L values). Furthermore, heatmap plot analysis revealed several significant correlations between different studied parameters, which may explore the importance of applied Cys and ALA as effective compounds in wheat cultivation under water deficit conditions.

A Comprehensive Review about the Molecular Structure of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): Insights into Natural Products against COVID-19

In 2019, the world suffered from the emergence of COVID-19 infection, one of the most difficult pandemics in recent history. Millions of confirmed deaths from this pandemic have been reported worldwide. This disaster was caused by SARS-CoV-2, which is the last discovered member of the family of Coronaviridae. Various studies have shown that natural compounds have effective antiviral properties against coronaviruses by inhibiting multiple viral targets, including spike proteins and viral enzymes. This review presents the classification and a detailed explanation of the SARS-CoV-2 molecular characteristics and structure-function relationships. We present all currently available crystal structures of different SARS-CoV-2 proteins and emphasized on the crystal structure of different virus proteins and the binding modes of their ligands. This review also discusses the various therapeutic approaches for COVID-19 treatment and available vaccinations. In addition, we highlight and compare the existing data about natural compounds extracted from algae, fungi, plants, and scorpion venom that were used as antiviral agents against SARS-CoV-2 infection. Moreover, we discuss the repurposing of select approved therapeutic agents that have been used in the treatment of other viruses.

Modeling Agrobacterium-Mediated Gene Transformation of Tobacco (Nicotiana tabacum)-A Model Plant for Gene Transformation Studies

The multilayer perceptron (MLP) topology of an artificial neural network (ANN) was applied to create two predictor models in Agrobacterium-mediated gene transformation of tobacco. Agrobacterium-mediated transformation parameters, including Agrobacterium strain, Agrobacterium cell density, acetosyringone concentration, and inoculation duration, were assigned as inputs for ANN-MLP, and their effects on the percentage of putative and PCR-verified transgenic plants were investigated. The best ANN models for predicting the percentage of putative and PCR-verified transgenic plants were selected based on basic network quality statistics. Ex-post error calculations of the relative approximation error (RAE), the mean absolute error (MAE), the root mean square error (RMS), and the mean absolute percentage error (MAPE) demonstrated the prediction quality of the developed models when compared to stepwise multiple regression. Moreover, significant correlations between the ANN-predicted and the actual values of the percentage of putative transgenes (R ² = 0.956) and the percentage of PCR-verified transgenic plants (R ² = 0.671) indicate the superiority of the established ANN models over the classical stepwise multiple regression in predicting the percentage of putative (R ² = 0.313) and PCR-verified (R ²= 0.213) transgenic plants. The best combination of the multiple inputs analyzed in this investigation, to achieve maximum actual and predicted transgenic plants, was at OD ₆₀₀ = 0.8 for the LB4404 strain of Agrobacterium × 300 μmol/L acetosyringone × 20 min immersion time. According to the sensitivity analysis of ANN models, the Agrobacterium strain was the most important influential parameter in Agrobacterium-mediated transformation of tobacco. The prediction efficiency of the developed model was confirmed by the data series of Agrobacterium-mediated transformation of an important medicinal plant with low transformation efficiency. The results of this study are pivotal to model and predict the transformation of other important Agrobacterium-recalcitrant plant genotypes and to increase the transformation efficiency by identifying critical parameters. This approach can substantially reduce the time and cost required to optimize multi-factorial Agrobacterium-mediated transformation strategies.

Protective Effect of γ-Aminobutyric Acid Against Chilling Stress During Reproductive Stage in Tomato Plants Through Modulation of Sugar Metabolism, Chloroplast Integrity, and Antioxidative Defense Systems

Despite the role of γ-aminobutyric acid (GABA) in plant tolerance to chilling stress having been widely discussed in the seedling stage, very little information is clear regarding its implication in chilling tolerance during the reproductive stage of the plant. Here, we investigated the influence of GABA (1 and 2mM) as a foliar application on tomato plants (Solanum lycopersicum L. cv. Super Marmande) subjected to chilling stress (5°C for 6h/day) for 5 successive days during the flowering stage. The results indicated that applied GABA differentially influenced leaf pigment composition by decreasing the chlorophyll a/b ratio and increasing the anthocyanin relative to total chlorophyll. However, carotenoids were not affected in both GABA-treated and non-treated stressed plants. Root tissues significantly exhibited an increase in thermo-tolerance in GABA-treated plants. Furthermore, applied GABA substantially alleviated the chilling-induced oxidative damage by protecting cell membrane integrity and reducing malondialdehyde (MDA) and H₂O₂. This positive effect of GABA was associated with enhancing the activity of phenylalanine ammonia-lyase (PAL), catalase (CAT), superoxide dismutase (SOD), and ascorbate peroxidase (APX). Conversely, a downregulation of peroxidase (POX) and polyphenol oxidase (PPO) was observed under chilling stress which indicates its relevance in phenol metabolism. Interesting correlations were obtained between GABA-induced upregulation of sugar metabolism coinciding with altering secondary metabolism, activities of antioxidant enzymes, and maintaining the integrity of plastids' ultrastructure Eventually, applied GABA especially at 2mM improved the fruit yield and could be recommended to mitigate the damage of chilling stress in tomato plants.

Bee Venom-A Potential Complementary Medicine Candidate for SARS-CoV-2 Infections

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is characterized by severe cytokine storm syndrome following inflammation. SARS-CoV-2 directly interacts with angiotensin-converting enzyme 2 (ACE-2) receptors in the human body. Complementary therapies that impact on expression of IgE and IgG antibodies, including administration of bee venom (BV), have efficacy in the management of arthritis, and Parkinson's disease. A recent epidemiological study in China showed that local beekeepers have a level of immunity against SARS-CoV-2 with and without previous exposure to virus. BV anti-inflammatory properties are associated with melittin and phospholipase A2 (PLA2), both of which show activity against enveloped and non-enveloped viruses, including H1N1 and HIV, with activity mediated through antagonist activity against interleukin-6 (IL-6), IL-8, interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α). Melittin is associated with the underexpression of proinflammatory cytokines, including nuclear factor-kappa B (NF-κB), extracellular signal-regulated kinases (ERK1/2), and protein kinase Akt. BV therapy also involves group III secretory phospholipase A₂ in the management of respiratory and neurological diseases. BV activation of the cellular and humoral immune systems should be explored for the application of complementary medicine for the management of SARS-CoV-2 infections. BV "vaccination" is used to immunize against cytomegalovirus and can suppress metastases through the PLA2 and phosphatidylinositol-(3,4)-bisphosphate pathways. That BV shows efficacy for HIV and H1NI offers opportunity as a candidate for complementary therapy for protection against SARS-CoV-2.

Endophytic Streptomyces laurentii Mediated Green Synthesis of Ag-NPs with Antibacterial and Anticancer Properties for Developing Functional Textile Fabric Properties

Improvement of the medical textile industry has received more attention recently, especially with widespread of microbial and viral infections. Medical textiles with new properties, such as bacterial pathogens self-cleaning, have been explored with nanotechnology. In this study, an endophytic actinomycetes strain of Streptomyces laurentii R-1 was isolated from the roots of the medicinal plant Achillea fragrantissima. This is used as a catalyst for the mediated biosynthesis of silver nanoparticles (Ag-NPs) for applications in the textile industry. The biosynthesized Ag-NPs were characterized using UV-vis spectroscopy, Fourier transform infrared (FT-IR), transmission electron microscopy (TEM), and X-ray Diffraction (XRD), which confirmed the successful formation of crystalline, spherical metal nanoparticles. The biosynthesized Ag-NPs exhibited broad-spectrum antibacterial activity. Our data elucidated that the biosynthesized Ag-NPs had a highly cytotoxic effect against the cancerous caco-2 cell line. The selected safe dose of Ag-NPs for loading on cotton fabrics was 100 ppm, regarding their antibacterial activity and safe cytotoxic efficacy. Interestingly, scanning electron microscope connected with energy dispersive X-ray spectroscopy (SEM-EDX) of loaded cotton fabrics demonstrated the smooth distribution of Ag-NPs on treated fabrics. The obtained results highlighted the broad-spectrum activity of nano-finished fabrics against pathogenic bacteria, even after 5 and 10 washing cycles. This study contributes a suitable guide for the performance of green synthesized NPs for utilization in different biotechnological sectors.

Communities of Fungi in Black Cherry Stumps and Effects of Herbicide

So far, there have been no studies on fungal communities in Prunus serotina (black cherry) wood. Our objectives were to characterize fungal communities from P. serotina wood and to evaluate effects of glyphosate (Glifocyd 360 SL) used on P. serotina stumps on abundance, species richness and diversity of those communities. In August 2016, in the Podanin Forest District, stumps of black cherry trees left after felling were treated with the herbicide. Control stumps were treated with water. Wood discs were cut from the surface of the stumps in May and July-August 2017. Eight treatment combinations (2 herbicide treatments × 2 disc sizes × 2 sample times) were tested. Sub-samples were pooled and ground in an acryogenic mill. Environmental DNA was extracted with a Plant Genomic DNA Purification Kit. The ITS1, 5.8S rDNA region was used to identify fungal species, using primers ITS1FI2 5'-GAACCWGCGGARGGATCA-3' and 5.8S 5'-CGCTGCGTT CTTCATCG-3'. The amplicons were sequenced using the Illumina system. The results were subjected to bioinformatic analysis. Sequences were compared with reference sequences from the NCBI database using the BLASTn 2.8.0 algorithm. Abundance of fungi was defined as the number of Operational Taxonomic Units (OTUs), and diversity as the number of species in a sample. Differences between the number of OTUs and taxa were analyzed using the chi-squared test (χ2). Diversity in microbial communities was compared using diversity indices. A total of 54,644 OTUs were obtained. Culturable fungi produced 49,808 OTUs (91.15%), fungi not known from culture had 2571 OTUs (4.70%), non-fungal organisms had 1333 (2.44%) and organisms with no reference sequence in NCBI, 934 OTUs (1.71%). The total number of taxa ranged from 120 to 319. Fungi in stump wood were significantly more abundant in July-August than in May, in stumps >5 cm diameter than in stumps <5 cm diameter, in glyphosate-treated than in untreated stumps when sampled in May, and in untreated than in glyphosate-treated stumps when sampled in July-August. Species richness was significantly greater in July-August than in May, and in stumps >5 cm diameter than in stumps <5 cm diameter, either treated or untreated, depending on size. Herbicides can therefore affect the abundance and diversity of fungal communities in deciduous tree wood. The greater frequency of Ascomycota in herbicide-treated than in untreated stumps indicates their greater tolerance of glyphosate.