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The deformation of open-pit mine slopes is influenced by various factors such as geological structure, hydrogeological conditions, mining activities, etc., making the prediction model complex. It is difficult to accurately capture all influencing factors. At present, a large number of monitoring devices are deployed around the slope of open-pit mines to record real-time displacement data of open-pit mine slopes. The data has the features of high-dimensional, temporal correlation, and nonlinear. Traditional slope stability analysis methods cannot effectively predict slope deformation without knowing other conditions and only data, it is necessary to use a data-based model to predict the displacement data of open-pit mine slopes in advance for slope stability analysis. In order to solve the above problems, a deformation prediction model for open-pit mine slopes based on the golden jackal optimized multilayer perception machine (GJO-MLP) is proposed. Each agent in GJO is independent of each other and can accelerate the training process of optimizing MLP through parallel computing. GJO can combine the nonlinear modeling and feature extraction capabilities of MLP, making the optimized MLP more advantageous in dealing with complex problems. To test the feasibility and effectiveness of GJO-MLP, GJO-MLP is compared and analyzed with ant colony algorithm optimization based MLP (ACO-MLP), gravity search algorithm optimization based MLP (GSA-MLP), and differential evolution algorithm optimization based MLP (DE-MLP). The simulation results on six datasets show that under the same experimental conditions, GJO-MLP shows better optimization performance compared to the other three algorithms. The slope deformation prediction model based on GJO-MLP is applied to the slope deformation prediction of Baorixile open-pit mine and Huapingzi slope deformation prediction. The results show that under the same conditions, compared to the other three algorithms, the slope deformation prediction model based on GJO-MLP not only show better predictive performance in predicting slope deformation data, but also has better feasibility and robustness.

Peanut web blotch is an important leaf disease caused by Phoma arachidicola, which seriously affects the quality and yield of peanuts. However, the molecular mechanisms of peanut resistance to peanut web blotch are not well understood. In this study, a transcriptome analysis of the interaction between peanut (Arachis hypogaea) and P. arachidicola revealed that total 2989 (779 up- and 2210 down-regulated) genes were all differentially expressed in peanut leaves infected by P. arachidicola at 7, 14, 21 days post inoculation. The pathways that were strongly differentially expressed were the flavone or isoflavone biosynthesis pathways. In addition, two 2-hydroxy isoflavanone synthase genes, IFS1 and IFS2, were strongly induced by P. arachidicola infection. Overexpression of the two genes enhanced resistance to Phytophthora parasitica in Nicotiana benthamiana. Knockout of AhIFS genes in peanut reduced disease resistance to P. arachidicola. These findings demonstrated that AhIFS genes play key roles in peanut resistance to P. arachidicola infection. Promoter analysis of the two AhIFS genes showed several defense-related cis-elements distributed in the promoter region. This study improves our understanding of the molecular mechanisms behind resistance of peanut infection by P. arachidicola, and provides important information that could be used to undertake greater detailed characterization of web blotch resistance genes in peanut. [ABSTRACT FROM AUTHOR]

In order to solve the problem of unmanned truck transportation scheduling in open-pit mines, the minimum sum of fuel cost, fixed start-up cost, breakdown maintenance cost, and network base station construction and maintenance cost are taken as the objective functions. The mining amount of mining station, crushing amount of crushing station, truck number and truck transportation workload are taken as the constraint conditions. The optimization model of unmanned truck transportation scheduling in open-pit mines is established. To solve the problem of imbalance between global exploration and local mining ability in the tunicate swarm algorithm, an improved tunicate swarm algorithm (ITSA) based on Singer mapping and adaptive updating mechanism of parameter position is proposed. And it is applied to solve the optimization model of unmanned truck transportation scheduling in open-pit mines. Singer mapping is introduced to enhance the distribution of the initial tunicate swarm in the solution space and accelerate the compression of the solution space, thus improving the convergence speed of the algorithm. Through the adaptive updating mechanism of parameter position, the positions of the tunicate and the optimal tunicate are adjusted to increase the search range of the solution space. Therefore, the algorithm jumps out of the local optimization. The simulation results show that ITSA has better convergence precision, convergence speed and stability compared with the four population intelligent optimization algorithms of grey wolf optimization algorithm (GWO), whale optimization algorithm (WOA), atom search optimization algorithm (ASO) and tunicate swarm algorithm (TSA). In the unimodal benchmark function, the evaluation indexes of ITSA are far better than those of the other four algorithms, which shows that ITSA has better local mining capacity. In the multi-peak benchmark function, the evaluation indexes of ITSA show better optimization performance, which indicates that ITSA has better global exploration performance. The practical application scenario verification shows that ITSA has faster convergence speed and higher convergence precision when used for solving the unmanned truck transportation scheduling optimization model. And ITSA reduces the truck transportation cost and transportation distance.

Peanut leaf spot is a worldwide disease whose prevalence poses a major threat to peanut yield and quality, and accurate prediction models are urgently needed for timely disease management. In this study, we proposed a novel peanut leaf spot prediction method based on an improved long short-term memory (LSTM) model and multi-year meteorological data combined with disease survey records. Our method employed a combination of convolutional neural networks (CNNs) and LSTMs to capture spatial–temporal patterns from the data and improve the model's ability to recognize dynamic features of the disease. In addition, we introduced a Squeeze-and-Excitation (SE) Network attention mechanism module to enhance model performance by focusing on key features. Through several hyper-parameter optimization adjustments, we identified a peanut leaf spot disease condition index prediction model with a learning rate of 0.001, a number of cycles (Epoch) of 800, and an optimizer of Adma. The results showed that the integrated model demonstrated excellent prediction ability, obtaining an RMSE of 0.063 and an R 2 of 0.951, which reduced the RMSE by 0.253 and 0.204, and raised the R 2 by 0.155 and 0.122, respectively, compared to the single CNN and LSTM. Predicting the occurrence and severity of peanut leaf spot disease based on the meteorological conditions and neural networks is feasible and valuable to help growers make accurate management decisions and reduce disease impacts through optimal fungicide application timing. [ABSTRACT FROM AUTHOR]

This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). The primary objective of this method is to create an effective data dimensionality reduction technique for eliminating redundant, irrelevant, and noisy features within high-dimensional datasets. Drawing inspiration from the Chinese idiom "Chai Lang Hu Bao," hybrid algorithm mechanisms, and cooperative behaviors observed in natural animal populations, we amalgamate the GWO algorithm, the Lagrange interpolation method, and the GJO algorithm to propose the multi-strategy fusion GJO-GWO algorithm. In Case 1, the GJO-GWO algorithm addressed eight complex benchmark functions. In Case 2, GJO-GWO was utilized to tackle ten feature selection problems. Experimental results consistently demonstrate that under identical experimental conditions, whether solving complex benchmark functions or addressing feature selection problems, GJO-GWO exhibits smaller means, lower standard deviations, higher classification accuracy, and reduced execution times. These findings affirm the superior optimization performance, classification accuracy, and stability of the GJO-GWO algorithm. [ABSTRACT FROM AUTHOR]

Peanut root rot, caused by Fusarium spp., is a devastating fungal disease. As part of a program to obtain a biocontrol agent to control peanut root rot in the field, a bacterial strain LY-1 capable of inhibiting the growth of the fungus in vitro was isolated from rhizosphere soil samples collected from wild mint by agar disk dilution and dual-culture assay. Strain LY-1 was identified as Bacillus subtilis based on morphological characteristics, 16S rDNA, and gyrA sequence analyses. The bacterial suspension and cell-free culture filtrate of LY-1 could significantly inhibit the growth of Fusarium oxysporum, Fusarium proliferatum and Fusarium solani, but volatile organic compounds from the cultures had only a weak effect on mycelial growth. The percentage inhibition of 20% concentration of the cell-free culture filtrate of LY-1 on conidium production of each of the three Fusarium species was greater than 72.38%, and the percentage inhibition by the culture filtration on the germination of conidia of the three species was at least 62.37%. The production of extracellular enzyme activity by LY-1 was studied in functional assays, showing protease, cellulase, amylase, chitinase, and β-1,3-glucanase activity, while LY-1 contained a gene encoding iturin, an antifungal lipopeptide. In addition, under pot culture in a greenhouse, culture filtrate of LY-1 significantly promoted the growth of peanut, increasing the fresh and dry mass of the plant by 30.77% and 27.27%, respectively, in comparison with the no-filtrate control. The culture filtrate of LY-1 increased the resistance of peanut plants to F. oxysporum, with the biocontrol efficiency reaching 44.71%. In conclusion, B. subtilis LY-1, a plant-growth-promoting rhizobacterium, was able to protect peanuts from Fusarium spp. infection. [ABSTRACT FROM AUTHOR]

There are environmental problems such as pollutant emission in the construction and service of road asphalt pavement. In order to explore the hazards of road asphalt to the environment, the types of pollutants from the construction and use of road asphalt pavement are analyzed. The various harmful components of pavement asphalt materials and their influencing factors are discussed. The corresponding pollution inhibition measures are introduced. The existing research work of asphalt pavement pollution is analyzed and suggestions for future research are proposed.

This paper proposes a novel hybrid algorithm, named Multi-Strategy Hybrid Harris Hawks Tunicate Swarm Optimization Algorithm (MSHHOTSA). The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. Firstly, inspired by the idea of the neighborhood and thermal distribution map, the hyperbolic tangent domain is introduced to modify the position of new tunicate individuals, which can not only effectively enhance the convergence performance of the algorithm but also ensure that the data generated between the unknown parameters and the old parameters have a similar distribution. Secondly, the nonlinear convergence factor is constructed to replace the original random factor c1 to coordinate the algorithm's local exploitation and global exploration performance, which effectively improves the ability of the algorithm to escape extreme values and fast convergence. Finally, the swarm update mechanism of the HHO algorithm is introduced into the position update of the TSA algorithm, which further balances the local exploitation and global exploration performance of the MSHHOTSA. The proposed algorithm was evaluated on eight standard benchmark functions, CEC2019 benchmark functions, four engineering design problems, and a PID parameter optimization problem. It was compared with seven recently proposed metaheuristic algorithms, including HHO and TSA. The results were analyzed and discussed using statistical indicators such as mean, standard deviation, Wilcoxon's rank sum test, and average running time. Experimental results demonstrate that the improved algorithm (MSHHOTSA) exhibits higher local convergence, global exploration, robustness, and universality than BOA, GWO, MVO, HHO, TSA, ASO, and WOA algorithms under the same experimental conditions. [ABSTRACT FROM AUTHOR]

Pore-forming toxins (PFTs) are effective tools for pathogens infection. By disrupting epithelial barriers and killing immune cells, PFTs promotes the colonization and reproduction of pathogenic microorganisms in their host. In turn, the host triggers defense responses, such as endocytosis, exocytosis, or autophagy. Bacillus thuringiensis (Bt) bacteria produce PFT, known as crystal proteins (Cry) which damage the intestinal cells of insects or nematodes, eventually killing them. In insects, aminopeptidase N (APN) has been shown to act as an important receptor for Cry toxins. Here, using the nematode Caenorhabditis elegans as model, an extensive screening of APN gene family was performed to analyze the potential role of these proteins in the mode of action of Cry5Ba against the nematode. We found that one APN, MNP-1, participate in the toxin defense response, since the mnp-1(ok2434) mutant showed a Cry5Ba hypersensitive phenotype. Gene expression analysis in mnp-1(ok2434) mutant revealed the involvement of two protease genes, F19C6.4 and R03G8.6, that participate in Cry5Ba degradation. Finally, analysis of the transduction pathway involved in F19C6.4 and R03G8.6 expression revealed that upon Cry5Ba exposure, the worms up regulated both protease genes through the activation of the FOXO transcription factor DAF-16, which was translocated into the nucleus. The nuclear location of DAF-16 was found to be dependent on mnp-1 under Cry5Ba treatment. Our work provides evidence of new host responses against PFTs produced by an enteric pathogenic bacterium, resulting in activation of host intestinal proteases that degrade the PFT in the intestine. Author summary: Pore-forming toxins (PFTs) have a crucial role in the pathogenesis of microbial pathogens. Meanwhile, hosts mediate different strategies to resist PFTs at the cellular level, such as endocytosis, exocytosis, autophagy, and MAPK or inflammasome signaling pathways. Here we show that the nematode Caenorhabditis elegans respond to PFTs inducing their proteolysis by up regulating intestinal proteases through the induction of FOXO transcription factor DAF-16 that showed nuclear location. Our results indicate that animals not only trigger defense mechanisms after PFTs intoxication at the cellular level, but also could eliminate PFTs in the intestine lumen, an effective additional strategy for animals to resist PFTs, especially those produced by enteric bacterial pathogens. Since, the FOXO transcription factor DAF-16 is conserved from nematodes to mammals, it is possible that the degradation of PFT by modulating intestinal proteases may be a common defense strategy against bacterial infections. [ABSTRACT FROM AUTHOR]

This article reports the first occurrence of Sordaria macrospora causing collar rot of peanut in Shandong province, China. The study describes the symptoms observed on peanut plants, the isolation and identification of the fungus, and the pathogenicity testing conducted. The research was supported by various funding sources, and the sequence data has been deposited in GenBank. This finding expands our knowledge of the distribution and impact of S. macrospora on peanut crops in China. [Extracted from the article]

Feature selection (FS) can eliminate many redundant, irrelevant, and noisy features in high-dimensional data to improve machine learning or data mining models' prediction, classification, and computational performance. We proposed an improved whale optimization algorithm (IWOA) and improved k-nearest neighbors (IKNN) classifier approaches for feature selection (IWOAIKFS). Firstly, WOA is improved by using chaotic elite reverse individual, probability selection of skew distribution, nonlinear adjustment of control parameters and position correction strategy to enhance the search performance of the algorithm for feature subsets. Secondly, the sample similarity measurement criterion and weighted voting criterion based on the simulated annealing algorithm to solve the weight matrix M are proposed to improve the KNN classifier and improve the evaluation performance of the algorithm on feature subsets. The experimental results show: IWOA not only has better optimization performance when solving benchmark functions of different dimensions, but also when used with IKNN for feature selection, IWOAIKFS has better classification and robustness. [ABSTRACT FROM AUTHOR]

Aspergillus niger is a very destructive pathogen causing severe peanut root rot, especially in the seeding stage of peanuts (Arachis hypogaea), and often leading to the death of the plant. Protein lysine 2-hydroxyisobutyrylation (Khib) is a newly detected post-translational modification identified in several species. In this study, we identified 5041 Khib sites on 1,453 modified proteins in A. niger. Compared with five other species, A. niger has conserved and novel proteins. Bioinformatics analysis showed that Khib proteins are widely distributed in A. niger and are involved in many biological processes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that Khib proteins were significantly enriched in many cellular compartments and pathways, such as ribosomes and proteasome subunits. A total of 223 Khib proteins were part of the PPI network, thus, suggesting that Khib proteins are associated with a large range of protein interactions and diverse pathways in the life processes of A. niger. Several identified proteins are involved in pathogenesis regulation. Our research provides the first comprehensive report of Khib and an extensive database for potential functional studies on Khib proteins in this economically important fungus. [ABSTRACT FROM AUTHOR]

Peanut southern blight caused by Sclerotium rolfsii is known to cause significant economic losses to peanut production worldwide. The bacterial strain LX11 isolated from the peanut (Arachis hypogaea) rhizosphere was identified as Bacillus pumilus based on its phenotypic features, 16S ribosomal RNA and β-subunit of DNA gyrase (gyrB) sequence. LX11 showed significant antimicrobial activities against S. rolfsii. The treatment application of LX11 against S. rolfsii was shown to reach over 65% in field trials. LX11 may be useful as a potential biocontrol strain for southern blight of peanut. [ABSTRACT FROM AUTHOR]

Background: Plant pathogenic fungi of the genus Fusarium infect a wide array of crops and produce numerous health-threatening mycotoxins. Recently, we found that larvae of the common pest of stored products Tenebrio molitor preferably fed on grains colonized with Fusarium proliferatum. We draw the hypothesis that the increased attractiveness of infected grains for mealworms facilitates dispersal of the fungus. In this work we examined the dissemination of F. proliferatum and further Fusarium spp. by adults of T. molitor. Results: Mealworm beetle Tenebrio molitor transmitted Fusarium species F. avenaceum, F. culmorum, F. poae, and F. proliferatum to wheat grains with varying efficiency. F. proliferatum was disseminated most efficiently: 20 days after feeding on Fusarium cultures, the beetles still transmitted F. proliferatum to most grains exposed to feeding. The transmission of F. culmorum gradually declined over time and the transmission of the other Fusarium spp. ceased completely 20 d after beetles feeding of fungal cultures. Propagules of F. proliferatum and F. culmorum were traceable in beetles' feces for 20 days while no colonies of F. poae and F. avenaceum were detectable after 5 days. Because F. proliferatum was transmitted by mealworms most efficiently, this species was further investigated. Mealworm beetles T. molitor preferred feeding on grains colonized with F. proliferatum as compared to uninfected grains. Male beetles infected with F. proliferatum transmitted the fungus by copulation. Conclusions: Efficient dissemination of F. proliferatum by mealworm beetle together with the feeding preference of the beetle for grains colonized with F. proliferatum show that the chemical phenotype of the fungus responsible for the enhanced attractiveness of infected grains is subjected to positive selection. This indicates that adaptation of F. proliferatum to transmission by insects involved an alteration of insects' feeding preferences. [ABSTRACT FROM AUTHOR]

The misalignment in the orbital angular momentum- (OAM-) based system would distort the radiation patterns of twisted beams carrying OAM, consequently making the OAM-based communication infeasible. To tackle the misalignment problem, a radio OAM steering technique based on a uniform circular array (UCA) is illustrated. Subsequently, simulations are conducted to explore the influence of the OAM steering on the OAM mode quality and transmission performance. Furthermore, UCAs working at Ka-band with formulated feeding networks are designed and fabricated to analyze the performance of the OAM steering. The influences of OAM steering on mode quality and orthogonality are then evaluated in the experiment. Overall, the analyses of OAM steering technique are beneficial for the development of radio OAM study. [ABSTRACT FROM AUTHOR]

To our knowledge, this is the first report of I F. neocosmosporiellum i causing foot rot in peanut in Shandong Province, China. Keywords: Fusarium neocosmosporiellum; Peanut foot rot; China EN Fusarium neocosmosporiellum Peanut foot rot China 1059 1060 2 08/18/21 20210801 NES 210801 Manlin Xu and Xia Zhang contribute equally to the paper From 2018 to 2020, foot rot was observed on peanut ( I Arachis hypogaea i L.) in Linyi City and Qingdao City, Shandong Province, China. [Extracted from the article]

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F. proliferatum or F. poae-colonized ones suggesting that T. molitor can tolerate or metabolize those toxins. [ABSTRACT FROM AUTHOR]

Species of Fusarium have significant agro-economical and human health-related impact by infecting diverse crop plants and synthesizing diverse mycotoxins. Here, we investigated interactions of grain-feeding Tenebrio molitor larvae with four grain-colonizing Fusarium species on wheat kernels. Since numerous metabolites produced by Fusarium spp. are toxic to insects, we tested the hypothesis that the insect senses and avoids Fusarium-colonized grains. We found that only kernels colonized with F. avenaceum or Beauveria bassiana (an insect-pathogenic fungal control) were avoided by the larvae as expected. Kernels colonized with F. proliferatum, F. poae or F. culmorum attracted T. molitor larvae significantly more than control kernels. The avoidance/preference correlated with larval feeding behaviors and weight gain. Interestingly, larvae that had consumed F. proliferatum- or F. poae-colonized kernels had similar survival rates as control. Larvae fed on F. culmorum-, F. avenaceum- or B. bassiana-colonized kernels had elevated mortality rates. HPLC analyses confirmed the following mycotoxins produced by the fungal strains on the kernels: fumonisins, enniatins and beauvericin by F. proliferatum, enniatins and beauvericin by F. poae, enniatins by F. avenaceum, and deoxynivalenol and zearalenone by F. culmorum. Our results indicate that T. molitor larvae have the ability to sense potential survival threats of kernels colonized with F. avenaceum or B. bassiana, but not with F. culmorum. Volatiles potentially along with gustatory cues produced by these fungi may represent survival threat signals for the larvae resulting in their avoidance. Although F. proliferatum or F. poae produced fumonisins, enniatins and beauvericin during kernel colonization, the larvae were able to use those kernels as diet without exhibiting increased mortality. Consumption of F. avenaceum-colonized kernels, however, increased larval mortality; these kernels had higher enniatin levels than F. proliferatum or F. poae-colonized ones suggesting that T. molitor can tolerate or metabolize those toxins. [ABSTRACT FROM AUTHOR]

In 2020, I Arachis hypogaea i grown in a greenhouse showed leaf lesions and a 20% disease incidence rate. A pathogenicity test was conducted using 10, 2-week-old seedlings by spraying leaves with an aqueous ascospore suspension (10 SP 6 sp spore mL SP -1 sp ), and control plants were sprayed with water. Leaf lesions began as chlorotic lesions near the margins and progressed to necrotic lesions with chlorotic halos. [Extracted from the article]

Keywords: Cylindrocladium black rot; Cylindrocladium parasiticum; Pathogenicity EN Cylindrocladium black rot Cylindrocladium parasiticum Pathogenicity 1079 1079 1 08/18/21 20210801 NES 210801 Xia Zhang and Manlin Xu contribute equally to the paper In 2017, a peanut disease resembling Cylindrocladium black rot (CBR) was found in Guiyang city, Guizhou province, China. For pathogenicity assay, two-week-old peanut (Luhua No.8) seedlings were inoculated with two mycelial plugs (8 mm in diameter) in a growth chamber (30 °C in the day and 25 °C at night, a 12-h photoperiod and 80% RH). [Extracted from the article]

Four peanut seedlings were spray-inoculated with conidia suspension (1.0 × 10 SP 6 sp conidia per mL), and sterile distilled water was used as control (three replicates) in a growth chamber (light culture at 30 °C for 12 h and dark culture at 25 °C for 12 h, 80% RH). Keywords: Peanut grey blight; Alternaria alternata; Molecular identification EN Peanut grey blight Alternaria alternata Molecular identification 677 677 1 05/06/21 20210501 NES 210501 Xia Zhang and Manlin Xu contributed equally to this work. [Extracted from the article]

• The antifungal bacterium, S. marcescens SerEW01 isolated from soil. • S. marcescens had significant inhibitory effects against mycelial growth of F. proliferatum. • S. marcescens significantly inhibited fumonisins production of F. proliferatum. • S. marcescens can synthesize chitinase to degrade the cell wall of the mycelia. Fumonisins are a family of hepatotoxic and nephrotoxic mycotoxins produced mainly by Fusarium verticillioides and F. proliferatum. F. proliferatum is an important pathogen colonizing an extraordinarily broad range of host plants worldwide and causing serious economic losses in agriculture, which has drawn our research attention. In order to manage F. proliferatum and its secondary metabolites in crop products and animal feed, the antifungal bacterium Serratia marcescens SerEW01 was isolated from the cuticle of earthworms. The strain strongly inhibited the germination of F. proliferatum conidia and mycelial growth, and suppressed fumonisins accumulation. S. marcescens SerEW01 has the capacity to synthesize chitinases, which degrade the cell walls of fungal mycelia. This research will enrich the resources of antifungal microorganisms and also provide a basis for the biological control of Fusarium proliferatum and fumonisins contamination management to enhance both the yield and quality of crop products and to ensure food and feed safety. [ABSTRACT FROM AUTHOR]