Broad-Spectrum Antimicrobial Activity of Synthetic Peptides GV185 and GV187.

Optimizing synthetic antimicrobial peptides for safe and enhanced activity against fungal and bacterial pathogens is useful for genetic engineering of plants for resistance to plant pathogens and their associated mycotoxins. Nine synthetic peptides modeled after lytic peptides tachyplesin 1, D4E1 from cecropin A, and protegrin 1 were added to germinated spores of fungal species Aspergillus flavus, Rhizopus stolonifer, Fusarium oxysporum f. sp. vasinfectum, F. verticillioides, F. graminearum, Claviceps purpurea, Verticillium dahliae, and Thielaviopsis basicola and bacterial cultures of Pseudomonas syringae pv. tabaci and Xanthomonas campestris pv. campestris at different doses and inhibitory dose response curves, and were modeled to assess antimicrobial activity. Peptides GV185 and GV187, modified from tachyplesin 1, had superior abilities to inhibit fungal and bacterial growth (50% inhibitory concentrations [IC50] ranging from 0.1 to 8.7 µM). R. stolonifer (IC50 = 8.1 µM), A. flavus (IC50 = 3.1 µM), and F. graminearum (IC50 = 2.2 µM) were less inhibited by GV185 and GV187 than all the remaining fungi (IC50 = 1.4 µM) and bacteria (IC50 = 0.1 µM). Of the remaining peptides, GV193, GV195, and GV196 (IC50 range of 0.9 to 6.6 µM) inhibited fungal growth of A. flavus, F. verticillioides, and F. graminearum less than GV185 and GV187 (IC50 range of 0.8 to 3.9 µM), followed by GV197 (IC50 range of 0.8 to 9.1 µM), whereas GV190 and GV192 inhibited poorly (IC50 range of 28.2 to 36.6 µM and 15.5 to 19.4 µM, respectively) and GV198 stimulated growth. GV185 and GV187 had slightly weaker hydrophobic and cationic residues than other tachyplesin 1 modified peptides but still had unexpectedly high lytic activity. Germinated fungal spores of R. stolonifer and F. graminearum exposed to these two peptides and D4E1 and AGM182 appeared wrinkled, with perforations near potential cytoplasmic leakage, which provided evidence of plasma membrane and cell wall lysis. We conclude that peptides GV185 and GV187 are promising candidates for genetic engineering of crops for resistance to plant-pathogenic bacteria and fungi, including A. flavus and aflatoxin contamination.

Changes in Bacterial Endophyte Community Following Aspergillus flavus Infection in Resistant and Susceptible Maize Kernels.

Aspergillus flavus (A. flavus)-mediated aflatoxin contamination in maize is a major global economic and health concern. As A. flavus is an opportunistic seed pathogen, the identification of factors contributing to kernel resistance will be of great importance in the development of novel mitigation strategies. Using V3-V4 bacterial rRNA sequencing and seeds of A. flavus-resistant maize breeding lines TZAR102 and MI82 and a susceptible line, SC212, we investigated kernel-specific changes in bacterial endophytes during infection. A total of 81 bacterial genera belonging to 10 phyla were detected. Bacteria belonging to the phylum Tenericutes comprised 86-99% of the detected phyla, followed by Proteobacteria (14%) and others (<5%) that changed with treatments and/or genotypes. Higher basal levels (without infection) of Streptomyces and Microbacterium in TZAR102 and increases in the abundance of Stenotrophomonas and Sphingomonas in MI82 following infection may suggest their role in resistance. Functional profiling of bacteria using 16S rRNA sequencing data revealed the presence of bacteria associated with the production of putative type II polyketides and sesquiterpenoids in the resistant vs. susceptible lines. Future characterization of endophytes predicted to possess antifungal/ anti-aflatoxigenic properties will aid in their development as effective biocontrol agents or microbiome markers for maize aflatoxin resistance.

An actin-depolymerizing factor from the halophyte smooth cordgrass, Spartina alterniflora (SaADF2), is superior to its rice homolog (OsADF2) in conferring drought and salt tolerance when constitutively overexpressed in rice.

Actin-depolymerizing factors (ADFs) maintain the cellular actin network dynamics by regulating severing and disassembly of actin filaments in response to environmental cues. An ADF isolated from a monocot halophyte, Spartina alterniflora (SaADF2), imparted significantly higher level of drought and salinity tolerance when expressed in rice than its rice homologue OsADF2. SaADF2 differs from OsADF2 by a few amino acid residues, including a substitution in the regulatory phosphorylation site serine-6, which accounted for its weak interaction with OsCDPK6 (calcium-dependent protein kinase), thus resulting in an increased efficacy of SaADF2 and enhanced cellular actin dynamics. SaADF2 overexpression preserved the actin filament organization better in rice protoplasts under desiccation stress. The predicted tertiary structure of SaADF2 showed a longer F-loop than OsADF2 that could have contributed to higher actin-binding affinity and rapid F-actin depolymerization in vitro by SaADF2. Rice transgenics constitutively overexpressing SaADF2 (SaADF2-OE) showed better growth, relative water content, and photosynthetic and agronomic yield under drought conditions than wild-type (WT) and OsADF2 overexpressers (OsADF2-OE). SaADF2-OE preserved intact grana structure after prolonged drought stress, whereas WT and OsADF2-OE presented highly damaged and disorganized grana stacking. The possible role of ADF2 in transactivation was hypothesized from the comparative transcriptome analyses, which showed significant differential expression of stress-related genes including interacting partners of ADF2 in overexpressers. Identification of a complex, differential interactome decorating or regulating stress-modulated cytoskeleton driven by ADF isoforms will lead us to key pathways that could be potential target for genome engineering to improve abiotic stress tolerance in agricultural crops.

Natural and targeted isovariants of the rice actin depolymerizing factor 2 can alter its functional and regulatory binding properties.

Actin depolymerizing factors (ADFs) are ubiquitous actin-binding proteins that play essential roles in maintaining cellular actin dynamics by depolymerizing/severing F-actin. Plant ADF isoforms show functional divergence via differential biochemical and cellular properties. We have shown previously that ADF2 of rice (OsADF2) and smooth cordgrass (SaADF2) displayed contrasting biochemical properties and stress response in planta. As a proof-of-concept that amino acid variances contribute to such functional difference, single amino acid mutants of OsADF2 were generated based on its sequence differences with SaADF2. Biochemical studies showed that the single-site amino acid mutations altered actin binding, depolymerizing, and severing properties of OsADF2. Phosphosensitive mutations, such as serine-6>threonine, changed the regulatory phosphorylation efficiency of ADF2 variants. The N-terminal mutations had greater effect on the phosphorylation pattern of OsADF2, whereas C-terminal mutations affected actin binding and severing. The presence of introduced mutations in isovariants of monocot ADF suggests that these residues are significant control points regulating their functional divergence, including abiotic stress response.

RNA interference-based silencing of the alpha-amylase (amy1) gene in Aspergillus flavus decreases fungal growth and aflatoxin production in maize kernels.

MAIN CONCLUSION: Expressing an RNAi construct in maize kernels that targets the gene for alpha-amylase in Aspergillus flavus resulted in suppression of alpha-amylase (amy1) gene expression and decreased fungal growth during in situ infection resulting in decreased aflatoxin production. Aspergillus flavus is a saprophytic fungus and pathogen to several important food and feed crops, including maize. Once the fungus colonizes lipid-rich seed tissues, it has the potential to produce toxic secondary metabolites, the most dangerous of which is aflatoxin. The pre-harvest control of A. flavus contamination and aflatoxin production is an area of intense research, which includes breeding strategies, biological control, and the use of genetically-modified crops. Host-induced gene silencing, whereby the host crop produces siRNA molecules targeting crucial genes in the invading fungus and targeting the gene for degradation, has shown to be promising in its ability to inhibit fungal growth and decrease aflatoxin contamination. Here, we demonstrate that maize inbred B104 expressing an RNAi construct targeting the A. flavus alpha-amylase gene amy1 effectively reduces amy1 gene expression resulting in decreased fungal colonization and aflatoxin accumulation in kernels. This work contributes to the development of a promising technology for reducing the negative economic and health impacts of A. flavus growth and aflatoxin contamination in food and feed crops.

Peanuts that keep aflatoxin at bay: a threshold that matters.

Aflatoxin contamination in peanuts poses major challenges for vulnerable populations of sub-Saharan Africa and South Asia. Developing peanut varieties to combat preharvest Aspergillus flavus infection and resulting aflatoxin contamination has thus far remained a major challenge, confounded by highly complex peanut-Aspergilli pathosystem. Our study reports achieving a high level of resistance in peanut by overexpressing (OE) antifungal plant defensins MsDef1 and MtDef4.2, and through host-induced gene silencing (HIGS) of aflM and aflP genes from the aflatoxin biosynthetic pathway. While the former improves genetic resistance to A. flavus infection, the latter inhibits aflatoxin production in the event of infection providing durable resistance against different Aspergillus flavus morphotypes and negligible aflatoxin content in several peanut events/lines well. A strong positive correlation was observed between aflatoxin accumulation and decline in transcription of the aflatoxin biosynthetic pathway genes in both OE-Def and HIGS lines. Transcriptomic signatures in the resistant lines revealed key mechanisms such as regulation of aflatoxin synthesis, its packaging and export control, besides the role of reactive oxygen species-scavenging enzymes that render enhanced protection in the OE and HIGS lines. This is the first study to demonstrate highly effective biotechnological strategies for successfully generating peanuts that are near-immune to aflatoxin contamination, offering a panacea for serious food safety, health and trade issues in the semi-arid regions.

Identification of candidate resistance genes of cotton against Aspergillus flavus infection using a comparative transcriptomics approach.

A comparative transcriptome analysis was performed using the genes significantly differentially expressed in cotton, corn and peanut in response to aflatoxin producing fungus Aspergillus flavus with an objective of identifying candidate resistance genes in cotton. Two-way analyses identified 732 unique genes to be differentially regulated by the fungus with only 26 genes common across all three crops that were considered candidate A. flavus resistance genes with an assumption that these genes have specific roles in conferring the resistance trait. Genes of membrane cellular component involved in DNA binding with involvement in defense responses were highly represented among the differentially expressed unique genes. Most (six) of these genes coded for 2-oxoglutarate (2OG) and Fe(II)-dependent oxygenase superfamily proteins. Genes encoding helix loop helix protein, alcohol dehydrogenase and UDP glycosylation transferase which were upregulated in response to both atoxigenic and toxigenic strains of A. flavus, could be potential resistance candidate genes for downstream functional manipulation to confer resistance.

MicroRNA (miRNA) profiling of maize genotypes with differential response to Aspergillus flavus implies zma-miR156-squamosa promoter binding protein (SBP) and zma-miR398/zma-miR394-F -box combinations involved in resistance mechanisms.

Maize (Zea mays), a major food crop worldwide, is susceptible to infection by the saprophytic fungus Aspergillus flavus that can produce the carcinogenic metabolite aflatoxin (AF) especially under climate change induced abiotic stressors that favor mold growth. Several studies have used "-omics" approaches to identify genetic elements with potential roles in AF resistance, but there is a lack of research identifying the involvement of small RNAs such as microRNAs (miRNAs) in maize-A. flavus interaction. In this study, we compared the miRNA profiles of three maize lines (resistant TZAR102, moderately resistant MI82, and susceptible Va35) at 8 h, 3 d, and 7 d after A. flavus infection to investigate possible regulatory antifungal role of miRNAs. A total of 316 miRNAs (275 known and 41 putative novel) belonging to 115 miRNA families were identified in response to the fungal infection across all three maize lines. Eighty-two unique miRNAs were significantly differentially expressed with 39 miRNAs exhibiting temporal differential regulation irrespective of the maize genotype, which targeted 544 genes (mRNAs) involved in diverse molecular functions. The two most notable biological processes involved in plant immunity, namely cellular responses to oxidative stress (GO:00345990) and reactive oxygen species (GO:0034614) were significantly enriched in the resistant line TZAR102. Coexpression network analysis identified 34 hubs of miRNA-mRNA pairs where nine hubs had a node in the module connected to their target gene with potentially important roles in resistance/susceptible response of maize to A. flavus. The miRNA hubs in resistance modules (TZAR102 and MI82) were mostly connected to transcription factors and protein kinases. Specifically, the module of miRNA zma-miR156b-nb - squamosa promoter binding protein (SBP), zma-miR398a-3p - SKIP5, and zma-miR394a-5p - F-box protein 6 combinations in the resistance-associated modules were considered important candidates for future functional studies.

Soil Biodegradation Resistance of Cotton Fiber Doped with Interior and Exterior Silver Nanoparticles.

Engineering fibers with nanomaterials is an effective way to modify their properties and responses to external stimuli. In this study, we doped cotton fibers with silver nanoparticles, both on the surface (126 ± 17 nm) and throughout the fiber cross section (18 ± 4 nm), and examined the resistance to soil biodegradation. A reagent-free one-pot treatment of a raw cotton fabric, where noncellulosic constituents of the raw cotton fiber and starch sizing served as reducing agents, produced silver nanoparticles with a total concentration of 11 g/kg. In a soil burial study spanning 16 weeks, untreated cotton underwent a sequential degradation process-fibrillation, fractionation, and merging-corresponding to the length of the soil burial period, whereas treated cotton did not exhibit significant degradation. The remarkable biodegradation resistance of the treated cotton was attributed to the antimicrobial properties of silver nanoparticles, as demonstrated through a test involving the soil-borne fungus Aspergillus flavus. The nonlinear loss behavior of silver from the treated cotton suggests that nanoparticle depletion in the soil depends on their location, with interior nanoparticles proving durable against environmental exposure.

Chemical composition, antifungal and insecticidal activities of Hedychium essential oils.

The antimicrobial properties of essential oils have been documented, and their use as "biocides" is gaining popularity. The aims of this study were to analyze the chemical composition and assess the biological activities of Hedychium essential oils. Oils from 19 Hedychium species and cultivars were analyzed by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) techniques. The antifungal and insecticidal activities of these oils were tested against Colletotrichum acutatum, C. fragariae, and C. gloeosporioides, and three insects, the azalea lace bug (Stephanitis pyrioides), the yellow fever mosquito (Aedes aegypti), and the red imported fire ant (Solenopsis invicta). Hedychium oils were rich in monoterpenes and sesquiterpenes, especially 1,8-cineole (0.1%-42%), linalool (<0.1%-56%), a-pinene (3%-17%), b-pinene (4%-31%), and (E)-nerolidol (0.1%-20%). Hedychium oils had no antifungal effect on C. gloeosporioides, C. fragariae, and C. acutatum, but most Hedychium oils effectively killed azalea lace bugs. The oils also show promise as an adult mosquito repellent, but they would make rather poor larvicides or adulticides for mosquito control. Hedychium oils acted either as a fire ant repellent or attractant, depending on plant genotype and oil concentration.

A Low-Cost, Portable Device for Detecting and Sorting Aflatoxin-Contaminated Maize Kernels.

Aflatoxin contamination of maize is a major food safety issue worldwide. The problem is of special significance in African countries because maize is a staple food. This manuscript describes a low-cost, portable, non-invasive device for detecting and sorting aflatoxin-contaminated maize kernels. We developed a prototype employing a modified, normalized difference fluorescence index (NDFI) detection method to identify potentially aflatoxin-contaminated maize kernels. Once identified, these contaminated kernels can be manually removed by the user. The device consists of a fluorescence excitation light source, a tablet for image acquisition, and detection/visualization software. Two experiments using maize kernels artificially infected with toxigenic Aspergillus flavus were implemented to evaluate the performance and efficiency of the device. The first experiment utilized highly contaminated kernels (71.18 ppb), while mildly contaminated kernels (1.22 ppb) were used for the second experiment. Evidently, the combined approach of detection and sorting was effective in reducing aflatoxin levels in maize kernels. With a maize rejection rate of 1.02% and 1.34% in the two experiments, aflatoxin reduction was achieved at 99.3% and 40.7%, respectively. This study demonstrated the potential of using this low-cost and non-invasive fluorescence detection technology, followed by manual sorting, to significantly reduce aflatoxin levels in maize samples. This technology would be beneficial to village farmers and consumers in developing countries by enabling safer foods that are free of potentially lethal levels of aflatoxins.

Comprehensive meta-analysis of QTL and gene expression studies identify candidate genes associated with Aspergillus flavus resistance in maize.

Aflatoxin (AF) contamination, caused by Aspergillus flavus, compromises the food safety and marketability of commodities, such as maize, cotton, peanuts, and tree nuts. Multigenic inheritance of AF resistance impedes conventional introgression of resistance traits into high-yielding commercial maize varieties. Several AF resistance-associated quantitative trait loci (QTLs) and markers have been reported from multiple biparental mapping and genome-wide association studies (GWAS) in maize. However, QTLs with large confidence intervals (CI) explaining inconsistent phenotypic variance limit their use in marker-assisted selection. Meta-analysis of published QTLs can identify significant meta-QTLs (MQTLs) with a narrower CI for reliable identification of genes and linked markers for AF resistance. Using 276 out of 356 reported QTLs controlling resistance to A. flavus infection and AF contamination in maize, we identified 58 MQTLs on all 10 chromosomes with a 66.5% reduction in the average CI. Similarly, a meta-analysis of maize genes differentially expressed in response to (a)biotic stresses from the to-date published literature identified 591 genes putatively responding to only A. flavus infection, of which 14 were significantly differentially expressed (-1.0 ≤ Log2Fc ≥ 1.0; p ≤ 0.05). Eight MQTLs were validated by their colocalization with 14 A. flavus resistance-associated SNPs identified from GWAS in maize. A total of 15 genes were physically close between the MQTL intervals and SNPs. Assessment of 12 MQTL-linked SSR markers identified three markers that could discriminate 14 and eight cultivars with resistance and susceptible responses, respectively. A comprehensive meta-analysis of QTLs and differentially expressed genes led to the identification of genes and makers for their potential application in marker-assisted breeding of A. flavus-resistant maize varieties.

Microbiota of maize kernels as influenced by Aspergillus flavus infection in susceptible and resistant inbreds.

Background: Nearly everything on Earth harbors a microbiome. A microbiome is a community of microbes (bacteria, fungi, and viruses) with potential to form complex networks that involve mutualistic and antagonistic interactions. Resident microbiota on/in an organism are determined by the external environment, both biotic and abiotic, and the intrinsic adaptability of each organism. Although the maize microbiome has been characterized, community changes that result from the application of fungal biocontrol strains, such as non-aflatoxigenic Aspergillus flavus, have not. Methods: We silk channel inoculated field-grown maize separately with a non-aflatoxigenic biocontrol strain (K49), a highly toxigenic strain (Tox4), and a combination of both A. flavus strains. Two maize inbreds were treated, A. flavus-susceptible B73 and A. flavus-resistant CML322. We then assessed the impacts of A. flavus introduction on the epibiota and endobiota of their maize kernels. Results: We found that the native microbial communities were significantly affected, irrespective of genotype or sampled tissue. Overall, bacteriomes exhibited greater diversity of genera than mycobiomes. The abundance of certain genera was unchanged by treatment, including genera of bacteria (e.g., Enterobacter, Pantoea) and fungi (e.g., Sarocladium, Meyerozyma) that are known to be beneficial, antagonistic, or both on plant growth and health. Conclusion: Beneficial microbes like Sarocladium that responded well to A. flavus biocontrol strains are expected to enhance biocontrol efficacy, while also displacing/antagonizing harmful microbes.

Putative Core Transcription Factors Affecting Virulence in Aspergillus flavus during Infection of Maize.

Aspergillus flavus is an opportunistic pathogen responsible for millions of dollars in crop losses annually and negative health impacts on crop consumers globally. A. flavus strains have the potential to produce aflatoxin and other toxic secondary metabolites, which often increase during plant colonization. To mitigate the impacts of this international issue, we employ a range of strategies to directly impact fungal physiology, growth and development, thus requiring knowledge on the underlying molecular mechanisms driving these processes. Here we utilize RNA-sequencing data that are obtained from in situ assays, whereby Zea mays kernels are inoculated with A. flavus strains, to select transcription factors putatively driving virulence-related gene networks. We demonstrate, through growth, sporulation, oxidative stress-response and aflatoxin/CPA analysis, that three A. flavus strains with knockout mutations for the putative transcription factors AFLA_089270, AFLA_112760, and AFLA_031450 demonstrate characteristics such as reduced growth capacity and decreased aflatoxin/CPA accumulation in kernels consistent with decreased fungal pathogenicity. Furthermore, AFLA_089270, also known as HacA, eliminates CPA production and impacts the fungus's capacity to respond to highly oxidative conditions, indicating an impact on plant colonization. Taken together, these data provide a sound foundation for elucidating the downstream molecular pathways potentially contributing to fungal virulence.

Multiplexed Host-Induced Gene Silencing of Aspergillus flavus Genes Confers Aflatoxin Resistance in Groundnut.

Aflatoxins are immunosuppressive and carcinogenic secondary metabolites, produced by the filamentous ascomycete Aspergillus flavus, that are hazardous to animal and human health. In this study, we show that multiplexed host-induced gene silencing (HIGS) of Aspergillus flavus genes essential for fungal sporulation and aflatoxin production (nsdC, veA, aflR, and aflM) confers enhanced resistance to Aspergillus infection and aflatoxin contamination in groundnut (<20 ppb). Comparative proteomic analysis of contrasting groundnut genotypes (WT and near-isogenic HIGS lines) supported a better understanding of the molecular processes underlying the induced resistance and identified several groundnut metabolites that might play a significant role in resistance to Aspergillus infection and aflatoxin contamination. Fungal differentiation and pathogenicity proteins, including calmodulin, transcriptional activator-HacA, kynurenine 3-monooxygenase 2, VeA, VelC, and several aflatoxin pathway biosynthetic enzymes, were downregulated in Aspergillus infecting the HIGS lines. Additionally, in the resistant HIGS lines, a number of host resistance proteins associated with fatty acid metabolism were strongly induced, including phosphatidylinositol phosphate kinase, lysophosphatidic acyltransferase-5, palmitoyl-monogalactosyldiacylglycerol Δ-7 desaturase, ceramide kinase-related protein, sphingolipid Δ-8 desaturase, and phospholipase-D. Combined, this knowledge can be used for groundnut pre-breeding and breeding programs to provide a safe and secure food supply.

Targeting the Aspergillus flavus p2c gene through host-induced gene silencing reduces A. flavus infection and aflatoxin contamination in transgenic maize.

Aspergillus flavus is an opportunistic fungal pathogen that infects maize and produces aflatoxins. Using biocontrol or developing resistant cultivars to reduce aflatoxin contamination has only achieved limited success. Here, the A. flavus polygalacturonase gene (p2c) was targeted for suppression through host-induced gene silencing (HIGS) to reduce aflatoxin contamination in maize. An RNAi vector carrying a portion of the p2c gene was constructed and transformed into maize B104. Thirteen out of fifteen independent transformation events were confirmed to contain p2c. The T2 generation kernels containing the p2c transgene had less aflatoxin than those without the transgene in six out of eleven events we examined. Homozygous T3 transgenic kernels from four events produced significantly less aflatoxins (P ≤ 0.02) than the kernels from the null or B104 controls under field inoculation conditions. The F1 kernels from the crosses between six elite inbred lines with P2c5 and P2c13 also supported significantly less aflatoxins (P ≤ 0.02) than those from the crosses with null plants. The reduction in aflatoxin ranged from 93.7% to 30.3%. Transgenic leaf (T0 and T3) and kernel tissues (T4) were also found to have significantly higher levels of p2c gene-specific small RNAs. Further, homozygous transgenic maize kernels had significantly less fungal growth (27~40 fold) than the null control kernels 10 days after fungal inoculation in the field. The calculated suppression of p2c gene expression based on RNAseq data was 57.6% and 83.0% in P2c5 and P2c13 events, respectively. These results indicate clearly that the reduced aflatoxin production in the transgenic kernels is due to RNAi-based suppression of p2c expression, which results in reduced fungal growth and toxin production.

Gradient boosting machine learning model to predict aflatoxins in Iowa corn.

Introduction: Aflatoxin (AFL), a secondary metabolite produced from filamentous fungi, contaminates corn, posing significant health and safety hazards for humans and livestock through toxigenic and carcinogenic effects. Corn is widely used as an essential commodity for food, feed, fuel, and export markets; therefore, AFL mitigation is necessary to ensure food and feed safety within the United States (US) and elsewhere in the world. In this case study, an Iowa-centric model was developed to predict AFL contamination using historical corn contamination, meteorological, satellite, and soil property data in the largest corn-producing state in the US. Methods: We evaluated the performance of AFL prediction with gradient boosting machine (GBM) learning and feature engineering in Iowa corn for two AFL risk thresholds for high contamination events: 20-ppb and 5-ppb. A 90%-10% training-to-testing ratio was utilized in 2010, 2011, 2012, and 2021 (n = 630), with independent validation using the year 2020 (n = 376). Results: The GBM model had an overall accuracy of 96.77% for AFL with a balanced accuracy of 50.00% for a 20-ppb risk threshold, whereas GBM had an overall accuracy of 90.32% with a balanced accuracy of 64.88% for a 5-ppb threshold. The GBM model had a low power to detect high AFL contamination events, resulting in a low sensitivity rate. Analyses for AFL showed satellite-acquired vegetative index during August significantly improved the prediction of corn contamination at the end of the growing season for both risk thresholds. Prediction of high AFL contamination levels was linked to aflatoxin risk indices (ARI) in May. However, ARI in July was an influential factor for the 5-ppb threshold but not for the 20-ppb threshold. Similarly, latitude was an influential factor for the 20-ppb threshold but not the 5-ppb threshold. Furthermore, soil-saturated hydraulic conductivity (Ksat) influenced both risk thresholds. Discussion: Developing these AFL prediction models is practical and implementable in commodity grain handling environments to achieve the goal of preventative rather than reactive mitigations. Finding predictors that influence AFL risk annually is an important cost-effective risk tool and, therefore, is a high priority to ensure hazard management and optimal grain utilization to maximize the utility of the nation's corn crop.

Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning.

Mycotoxin contamination of corn is a pervasive problem that negatively impacts human and animal health and causes economic losses to the agricultural industry worldwide. Historical aflatoxin (AFL) and fumonisin (FUM) mycotoxin contamination data of corn, daily weather data, satellite data, dynamic geospatial soil properties, and land usage parameters were modeled to identify factors significantly contributing to the outbreaks of mycotoxin contamination of corn grown in Illinois (IL), AFL >20 ppb, and FUM >5 ppm. Two methods were used: a gradient boosting machine (GBM) and a neural network (NN). Both the GBM and NN models were dynamic at a state-county geospatial level because they used GPS coordinates of the counties linked to soil properties. GBM identified temperature and precipitation prior to sowing as significant influential factors contributing to high AFL and FUM contamination. AFL-GBM showed that a higher aflatoxin risk index (ARI) in January, March, July, and November led to higher AFL contamination in the southern regions of IL. Higher values of corn-specific normalized difference vegetation index (NDVI) in July led to lower AFL contamination in Central and Southern IL, while higher wheat-specific NDVI values in February led to higher AFL. FUM-GBM showed that temperature in July and October, precipitation in February, and NDVI values in March are positively correlated with high contamination throughout IL. Furthermore, the dynamic geospatial models showed that soil characteristics were correlated with AFL and FUM contamination. Greater calcium carbonate content in soil was negatively correlated with AFL contamination, which was noticeable in Southern IL. Greater soil moisture and available water-holding capacity throughout Southern IL were positively correlated with high FUM contamination. The higher clay percentage in the northeastern areas of IL negatively correlated with FUM contamination. NN models showed high class-specific performance for 1-year predictive validation for AFL (73%) and FUM (85%), highlighting their accuracy for annual mycotoxin prediction. Our models revealed that soil, NDVI, year-specific weekly average precipitation, and temperature were the most important factors that correlated with mycotoxin contamination. These findings serve as reliable guidelines for future modeling efforts to identify novel data inputs for the prediction of AFL and FUM outbreaks and potential farm-level management practices.

Enhanced salt stress tolerance of rice plants expressing a vacuolar H+ -ATPase subunit c1 (SaVHAc1) gene from the halophyte grass Spartina alterniflora Löisel.

The physiological role of a vacuolar ATPase subunit c1 (SaVHAc1) from a halophyte grass Spartina alterniflora was studied through its expression in rice. The SaVHAc1-expressing plants showed enhanced tolerance to salt stress than the wild-type plants, mainly through adjustments in early stage and preparatory physiological responses. In addition to the increased accumulation of its own transcript, SaVHAc1 expression led to increased accumulation of messages of other native genes in rice, especially those involved in cation transport and ABA signalling. The SaVHAc1-expressing plants maintained higher relative water content under salt stress through early stage closure of the leaf stoma and reduced stomata density. The increased K(+) /Na(+) ratio and other cations established an ion homoeostasis in SaVHAc1-expressing plants to protect the cytosol from toxic Na(+) and thereby maintained higher chlorophyll retention than the WT plants under salt stress. Besides, the role of SaVHAc1 in cell wall expansion and maintenance of net photosynthesis was implicated by comparatively higher root and leaf growth and yield of rice expressing SaVHAc1 over WT under salt stress. The study indicated that the genes contributing toward natural variation in grass halophytes could be effectively manipulated for improving salt tolerance of field crops within related taxa.

Gradient boosting and bayesian network machine learning models predict aflatoxin and fumonisin contamination of maize in Illinois - First USA case study.

Mycotoxin contamination of corn results in significant agroeconomic losses and poses serious health issues worldwide. This paper presents the first report utilizing machine learning and historical aflatoxin and fumonisin contamination levels in-order-to develop models that can confidently predict mycotoxin contamination of corn in Illinois, a major corn producing state in the USA. Historical monthly meteorological data from a 14-year period combined with corresponding aflatoxin and fumonisin contamination data from the State of Illinois were used to engineer input features that link weather, fungal growth, and aflatoxin production in combination with gradient boosting (GBM) and bayesian network (BN) modeling. The GBM and BN models developed can predict mycotoxin contamination with overall 94% accuracy. Analyses for aflatoxin and fumonisin with GBM showed that meteorological and satellite-acquired vegetative index data during March significantly influenced grain contamination at the end of the corn growing season. Prediction of high aflatoxin contamination levels was linked to high aflatoxin risk index in March/June/July, high vegetative index in March and low vegetative index in July. Correspondingly, high levels of fumonisin contamination were linked to high precipitation levels in February/March/September and high vegetative index in March. During corn flowering time in June, higher temperatures range increased prediction of high levels of fumonisin contamination, while high aflatoxin contamination levels were linked to high aflatoxin risk index. Meteorological events prior to corn planting in the field have high influence on predicting aflatoxin and fumonisin contamination levels at the end of the year. These early-year events detected by the models can directly assist farmers and stakeholders to make informed decisions to prevent mycotoxin contamination of Illinois grown corn.