Rice bakanae disease is a soil-borne disease mainly caused by Fusarium fujikuroi, which seriously damages the yield and quality of rice. Phenamacril targets Myosin-5, thereby inhibiting its ATPase activity to exert an antifungal effect, demonstrating significant bioactivity against Fusarium species. However, the resistance of Fusarium fujikuroi field populations to phenamacril in Jiangsu Province in recent years remains unclear. In this study, a total of 223 Fusarium fujikuroi isolates were collected in Jiangsu Province from 2022 to 2023, with the resistance frequency increase from 25.88 % to 49.28 %. Additionally, a novel mutation type (S420I) in FfMyosin-5 was identified and confirmed by genetic transformation. The compound fitness index (CFI) revealed that the fitness of FfMyosin5(S420I) point mutants (1 x 10(5) < CFI <= 2 x 10(5)) was significantly lower than sensitive strain (CFI = 10.26 x 10(5)) in terms of mycelial growth rate, conidia production and conidia germination. In summary, the S420I mutation in FfMyosin-5 induces resistance to phenamacril while also decreased the fitness of Fusarium fujikuroi.

Ginger is a significant ethnobotanical and pharmacological crop consisting of potential bioactive constituents responsible for their nutraceutical value, they can have anti-inflammatory, antiobesity, antidiabetic, antinausea, antimicrobial, pain alleviation, antitumor, antioxidant and protective effects on respiratory disease, and agerelated disease. Ginger possesses a substantial value, but its production and general quality are greatly harmed by various biotic and abiotic stressors, to which it is highly susceptible. Fungi are the most damaging disease-causing agents, one of the devastating fungal pathogens in ginger is Fusarium spp., a soil and seed-borne pathogen resulting in poor production, poor quality, and decreased economic returns to the farmers. It infects ginger in every stage of development and each plant part even during post-harvest storage. This review emphasizes a comprehensive understanding of the nutraceutical value of ginger compounds, and Fusarium disease in ginger with its pathogenicity. Moreover, this review elaborates on an improvement of ginger yield by the management of the Fusarium pathogen through the biological and biotechnological approach.

The macroscopic mechanical properties of granular systems largely depend on the complex mechanical responses of force chains at the mesoscopic level. This study offers an alternative to rapidly identify and predict force chain distributions under different stress states. 100 sets of gradation curves that effectively represent four typical continuous gradation distributions are constructed. Numerical specimens corresponding to these gradation curves are generated using the discrete element method (DEM), and a dataset for deep neural network training is established via biaxial compression numerical simulations. The relationship between particle distribution characteristics and force chain structure is captured by the Pix2Pix conditional generative adversarial network (cGAN). The effectiveness of the generated force chain images in reproducing both particle gradation and spatial distribution characteristics is verified through the extraction and analysis of pixel probability distributions across different color channels, along with the computation of texture feature metrics. In addition, a GoogLeNet-based prediction model is constructed to demonstrate the accuracy with which the generated force chain images characterize the macroscopic mechanical properties of granular assemblies. The results indicate that the Pix2Pix network effectively predicts and identifies force chain distributions at peak stress for different gradation

Ground subsidence is a common urban geological hazard in several regions worldwide. The settlement of loess fill foundations exhibits more complex subsidence issues under the coupled effects of geomechanical and seepage-driven processes. This study selected 21 ascending Sentinel-1 A radar images from April 2023 to October 2024 to monitor the loess fill foundation in Shaanxi, China. To minimize errors caused by the orbital phase and residual flat-earth phase, this research combined PS-InSAR technology with the three-threshold method to improve the SBAS-InSAR processing workflow, thereby exploring time-series deformation of the loess fill foundation. Compared with conventional SBAS-InSAR technology, the improved SBAS-InSAR technique provided more consistent deformation time-series results with leveling data, effectively capturing the deformation characteristics of the fill foundation. Additionally, geographic information system (GIS) spatial analysis techniques and statistical methods were employed to analyze the overall characteristics and spatiotemporal evolution of the ground surface deformation in the study area. On the other hand, the major drivers of the subsidence in the study area were also discussed based on indoor experiments and engineering geological data. The results showed gradual and temporal shifts of the subsidence center toward areas with the maximum fill depths. In addition, two directions of uneven subsidence were observed within the fill foundation study area. The differences in the fill depth and soil properties caused by the building foundation construction were the main factors contributing to the uneven settlement of the foundations. Foundation deformation was also positively and negatively affected by surface water infiltration. This study integrates remote sensing and engineering geological data to provide a scientific basis for accurately monitoring and predicting loess fill foundation settlement. It also offers practical guidance for regional infrastructure development and geological hazard prevention.

Forest management and tree felling in the stand change the structural characteristics, which causes changes in the microclimate conditions. The microclimate is a key in sustainable forest management because soil temperature and moisture regimes regulate nutrient cycling in forest ecosystems. The aim of this research was to determine the changes in air and soil temperatures in pedunculate oak forest stands in different stages of shelterwood that stimulate natural regeneration. The research was conducted in pedunculated oak forests in Spa & ccaron;va area. The microclimatic parameters were measured in a mature old forest stand without shelterwood cutting and in stands with preparatory cut, seed cut, and final cut. The intensity of shelterwood had an impact on the amplitudes and values of air and soil temperatures. The highest average air temperature was in the stand with a preparatory cut. Extreme values of air and soil temperatures were measured in the stands with a final cut. The highest air and soil temperature amplitudes were in the stand with a final cut, with the exception of most of the winter, when the highest soil temperature amplitude was in the stand with a seed cut. The highest number of icy, cold, and hot days was in the stand with a final cut. SARIMA models establish that the difference between microclimatic parameters is not accidental.

Background Fungal infection predominantly damages agricultural practices, and conventional chemical fungicides and insecticides are applied to control it, which extensively harms human health and the environment. Some bacterial species can control fungus by lysing its outer chitin layer.Objectives The present research aimed to isolate microorganisms capable of producing chitinase, thus acting as a highly effective biocontrol agent in combating fungal phytopathogens.Methods Two chitinase-producing bacterial strains were successfully isolated and screened from soil samples from a fish market environment. The process involved the aseptic collection of soil samples, followed by serial dilution to facilitate microorganism isolation. The bacterium exhibited optimal extracellular chitinase enzyme production following a 72-h incubation period at a temperature of 30 degrees C in a chitinase detection medium containing 0.5% chitin. Validation of chitinase production was confirmed through a clear zone assay, thus verifying its chitinase-producing capacity.Results Among the various isolated strains, isolates S3C1 and S3C3 demonstrated the highest chitinase activity, leading to their selection for further investigation. Comprehensive morphological and biochemical tests were conducted on these two isolates to assess their characteristics and capabilities. These tests established that both isolates were gram-negative, rod-shaped bacteria. Through genetic sequencing of the 16S rRNA gene, both organisms were identified as Klebsiella variicola exhibiting a remarkable similarity of 99% with S3C1 and S3C3 respectively. The bacteria exhibited maximum chitinase synthesis at optimal circumstances, which were determined to be a temperature of 30 degrees C and a pH of 7, after a 48-h incubation period. The bacteria exhibited robust antifungal activity during bioassays, demonstrating their capability to suppress the growth of fungal pathogens (specifically, Fusarium oxysporum) in vitro.Conclusion This research suggests a promising alternative to synthetic fungicides in agricultural practices, fostering a sustainable approach to disease management.

Ongoing climate warming and increased human activities have led to significant permafrost degradation on the Qinghai-Tibet Plateau (QTP). Mapping the distribution of active layer thickness (ALT) can provide essential information for understanding this degradation. Over the past decade, InSAR (Interferometric synthetic aperture radar) technology has been utilized to estimate ALT based on remotely-sensed surface deformation information. However, these methods are generally limited by their ability to accurate extract seasonal deformation and model subsurface water content of active layer. In this paper, an ALT inversion method considering both seasonal deformation from InSAR and smoothly multilayer soil moisture from ERA5 is proposed. Firstly, we introduce a ground seasonal deformation extraction model combining RobustSTL and InSAR, and the deformation extraction accuracy by considering the deformation characteristics of permafrost are evaluated, proving the effectiveness of RobustSTL in extracting seasonal deformation of permafrost. Then, using ERA5 soil moisture products, a smoothed multilayer soil moisture model for ALT inversion is established. Finally, integrating the seasonal deformation and multilayer soil moisture, the ALT can be estimated. The proposed model is applied to the Yellow River source region (YRSR) with Sentinel-1A images acquired from 2017 to 2021, and the ALT retrieval accuracy is validated with measured data. Experimental results show that the vertical deformation rate of the study area generally ranges from -30 mm/year to 20 mm/year, with seasonal deformation amplitude ranging from 2 mm to 30 mm. The RobustSTL method has the highest accuracy in extracting seasonal deformation of permafrost, with an RMSE (root mean square error) of 0.69 mm, and is capable of capturing the freeze-thaw characteristics of the active layer. The estimated ALT of the YRSR ranges from 49 cm to 450 cm, with an average value of 145 cm. Compared to the measured data, the proposed method has an average error of 37.5 cm, which represents a 21 % improvement in accuracy over existing methods.

随着全球气温升高，冰川不断消融，冰湖溃决现象频发，尤其在西藏地区发生频率较高，给当地人民造成巨大生命财产损失。另外，冰湖作为内陆水系统的主要组成部分之一，其面积变化与气候变化和人类活动密切相关，关注冰湖演化对保护周边地区的人类安全和监测地区生态变化有理论和实践意义。本文提出基于SAR极化增强与形态学运算的水陆边界提取方法对冰湖进行高精度自动识别，以青藏高原娘约错冰湖为研究区，对2018—2021年冰湖进行动态变化提取，并结合气候和地形等因素进行联合分析。结果表明，娘约错冰湖附近没有典型的冰川融水，其主要补给源为地表径流和大气降水，属于稳定性湖泊。其面积增长趋势缓慢，地形因素是其稳定的主要原因，对于下游的鲁朗镇和川藏铁路没有冰湖溃决的危险。

随着全球气温升高，冰川不断消融，冰湖溃决现象频发，尤其在西藏地区发生频率较高，给当地人民造成巨大生命财产损失。另外，冰湖作为内陆水系统的主要组成部分之一，其面积变化与气候变化和人类活动密切相关，关注冰湖演化对保护周边地区的人类安全和监测地区生态变化有理论和实践意义。本文提出基于SAR极化增强与形态学运算的水陆边界提取方法对冰湖进行高精度自动识别，以青藏高原娘约错冰湖为研究区，对2018—2021年冰湖进行动态变化提取，并结合气候和地形等因素进行联合分析。结果表明，娘约错冰湖附近没有典型的冰川融水，其主要补给源为地表径流和大气降水，属于稳定性湖泊。其面积增长趋势缓慢，地形因素是其稳定的主要原因，对于下游的鲁朗镇和川藏铁路没有冰湖溃决的危险。

随着全球气温升高，冰川不断消融，冰湖溃决现象频发，尤其在西藏地区发生频率较高，给当地人民造成巨大生命财产损失。另外，冰湖作为内陆水系统的主要组成部分之一，其面积变化与气候变化和人类活动密切相关，关注冰湖演化对保护周边地区的人类安全和监测地区生态变化有理论和实践意义。本文提出基于SAR极化增强与形态学运算的水陆边界提取方法对冰湖进行高精度自动识别，以青藏高原娘约错冰湖为研究区，对2018—2021年冰湖进行动态变化提取，并结合气候和地形等因素进行联合分析。结果表明，娘约错冰湖附近没有典型的冰川融水，其主要补给源为地表径流和大气降水，属于稳定性湖泊。其面积增长趋势缓慢，地形因素是其稳定的主要原因，对于下游的鲁朗镇和川藏铁路没有冰湖溃决的危险。