Search Results (40)

Rice wine, as a traditional fermented beverage, has its quality and flavor influenced by a combination of multiple factors. This review provides an overview of the key aspects of rice wine production, including raw material selection and processing, the regulation of quality by brewing techniques, the mechanisms of microbial community interaction during fermentation, and the types and formation mechanisms of major compounds in rice wine (including flavor compounds and non-volatile components). The study highlights that different raw materials and processing methods significantly impact the fundamental flavor profile of rice wine, while fermentation conditions and dynamic changes in microbial communities determine its flavor complexity and stability. Additionally, this review examines various factors affecting the quality and flavor of rice wine, such as fermentation environment, microbial metabolism, and control of harmful substances, and summarizes modern research and technological advancements, emphasizing the potential of digital and intelligent technologies in enhancing the quality and safety of rice wine. Finally, future research directions are proposed to promote modernization and quality improvement of the rice wine industry. Full article

Geothermal resources are significant natural resources for achieving carbon neutrality. In this study, we collected eight groups of geothermal water samples from a Sichuan sedimentary basin. Major and trace elements were measured for hydrochemical analysis. SO₄²⁻ and Ca²⁺ are the major anion and cation, respectively, in geothermal waters with the hydrochemical type Ca–SO₄. The dissolution of calcite and gypsum, silicate weathering and positive cation exchange were responsible for hydrochemical processes. Saturation indices showed the unsaturated affinity of geothermal waters. Carbonate scaling would be the main problem during geothermal exploitation. The water quality index indicated that most of the geothermal water samples, except G3 and G8, were suitable for drinking purposes. The poor water quality of the G3 and G8 samples was attributed to elevated Na⁺ and K⁺ concentrations. The weights of affecting factors followed the order of NH₄⁺ (3.803) > Cl⁻ (2.823) > Na⁺ (2.677) > pH (2.224) > Ca²⁺ (1.506) > SO₄²⁻ (1.169) > F⁻ (1.127) > Mg²⁺ (0.850) > TDS (0.808). The results of this study provide an important insight for geothermal exploitation in sedimentary basins worldwide. Full article

In this work, the generalized finite difference method (GFDM), a popular meshless numerical method, is employed for predicting the thermal and mechanical behavior of an electrothermal micro-actuator. Based on the concept of GFDM and discretization on the computational domain, the discrete forms of the thermal and mechanical governing equations are derived, respectively. With the help of the incremental load method, the discrete form from the electrothermal analysis is solved precisely and the temperature distribution is obtained. Meanwhile, combining this approach with the discrete control equation derived from the natural boundary condition, its displacement is also evaluated. The convergence of the temperature by different iterative methods is tested and compared. The computational stability and efficiency (CPU time) in these two analyses are also given in this study. To further investigate the accuracy of the solutions, experiments to capture temperature and FEM analysis are conducted. Regardless of the imperfect boundary condition, the temperature distribution calculated by the GFDM shows great agreement with that obtained by experiment and FEM. A similar phenomenon can be also found in the comparison between the displacements evaluated by the GFDM and FEM, respectively. Full article

Photoacoustic (PA) imaging is a non-invasive imaging technique with high optical resolution and acoustic penetration depth, which has been widely used in medical and clinical researches. As an important part in functional PA imaging, photoacoustic mechanical imaging (PAMI) has great potential in visualizing and understanding the local development of pathological process. This review provides lots of PA breakthroughs which have been made in elasticity detection, viscosity detection, and viscoelasticity detection through PAMI techniques. The current research problems, challenges and future development directions were discussed. Full article

The development of soybean (Glycine max) is regulated by the photoperiod, with genes related to photoperiod sensitivity primarily focused on the flowering time. However, their roles in post-flowering reproductive development and the mechanisms by which the photoperiod affects them are not yet determined. In this study, we found that pod formation is sensitive to the photoperiod. Long-day conditions tended to extend the time from flowering to pod formation, and the first wave of flowers tended to fall off. Additionally, the photoperiod affected the pistil morphology; under short-day conditions, the stigma had a curved hook-like structure that facilitated better interaction with the filaments when pollen was released, ultimately influencing the timing of pod formation. Photoperiod-insensitive mutants, lacking E1 family and Evening Complex (EC) genes, showed no difference in the pod formation time under long-day or short-day conditions. Hormone content analysis and transcriptome data analysis indicated that various hormones, reactive oxygen species (ROS) burst pathway signals, and the application of sucrose solution in vitro might influence floral organ abscission. Full article

The helical anchor foundation is driven into the soil under the combined action of torque and vertical pressure. The installation process involves a significant deformation of the soil, which is difficult to simulate numerically using the traditional finite element method. As a meshless method, Smoothed Particle Hydrodynamics (SPH) is very suitable for simulating large deformation problems. In this paper, the SPH meshless method and traditional finite element method are used to simulate the installation and pulling process of helical anchor foundations in sandy soil. The variations in installation force, installation torque, ultimate uplift capacity, and torque correlation factor under different advancement ratios were studied. The research results indicate that using a low advancement ratio for installation can significantly reduce the installation force and torque of the helical anchor and positively affect the ultimate uplift capacity. Moreover, the torque correlation factor is also influenced by the advancement ratio. Using the torque correlation factor value obtained from the “pitch matching” installation to predict the ultimate uplift capacity at other advancement ratios may result in an overestimation. Full article

Hydrogen safety remains a paramount concern in pipeline transportation. Once hydrogen leaks and ignites, it quickly escalates into a jet fire incident. The substantial thermal radiation released poses significant risks of fire and explosion. Therefore, studying the thermal radiation characteristics of hydrogen jet fires and developing accurate prediction models are crucial for establishing relevant safety standards. To address the oversimplified consideration of weighted coefficients in thermal radiation prediction models, this study investigated the thermal radiation characteristics of hydrogen jet fire by carrying out experiments and numerical simulations. The results reveal the significant impacts of the leakage diameter and pressure on thermal radiation. Increases in both the leakage diameter and pressure lead to a rapid escalation in the thermal radiation release, highlighting their critical importance in establishing safety standards for hydrogen pipeline transportation. Additionally, this study optimized the weight coefficients in the multi-point source prediction model based on temperature distribution along the flame axis. The optimized model was validated through comparison with experimental data. After optimization, the prediction error of the multi-point source radiation model was reduced from 19.5% to 13.9%. This model provides significant support for accurately evaluating the risk of hydrogen jet fire. Full article

The accurate instance segmentation of individual crop plants is crucial for achieving a high-throughput phenotypic analysis of seedlings and smart field management in agriculture. Current crop monitoring techniques employing remote sensing predominantly focus on population analysis, thereby lacking precise estimations for individual plants. This study concentrates on maize, a critical staple crop, and leverages multispectral remote sensing data sourced from unmanned aerial vehicles (UAVs). A large-scale SAM image segmentation model is employed to efficiently annotate maize plant instances, thereby constructing a dataset for maize seedling instance segmentation. The study evaluates the experimental accuracy of six instance segmentation algorithms: Mask R-CNN, Cascade Mask R-CNN, PointRend, YOLOv5, Mask Scoring R-CNN, and YOLOv8, employing various combinations of multispectral bands for a comparative analysis. The experimental findings indicate that the YOLOv8 model exhibits exceptional segmentation accuracy, notably in the NRG band, with bbox_mAP50 and segm_mAP50 accuracies reaching 95.2% and 94%, respectively, surpassing other models. Furthermore, YOLOv8 demonstrates robust performance in generalization experiments, indicating its adaptability across diverse environments and conditions. Additionally, this study simulates and analyzes the impact of different resolutions on the model’s segmentation accuracy. The findings reveal that the YOLOv8 model sustains high segmentation accuracy even at reduced resolutions (1.333 cm/px), meeting the phenotypic analysis and field management criteria. Full article

Remote sensing images (RSIs) are widely used in various fields due to their versatility, accuracy, and capacity for earth observation. Direct application of RSIs to harvest optimal results is generally difficult, especially for weak information features in the images. Thus, extracting the weak information in RSIs is reasonable to promote further applications. However, the current techniques for weak information extraction mainly focus on spectral features in hyperspectral images (HSIs), and a universal weak information extraction technology for RSI is lacking. Therefore, this study focused on mining the weak information from RSIs and proposed the deep multi-order spatial–spectral residual feature extractor (DMSRE). The DMSRE considers the global information and three-dimensional cube structures by combining low-rank representation, high-order residual quantization, and multi-granularity spectral segmentation theories. This extractor obtains spatial–spectral features from two derived sequences (deep spatial–spectral residual feature (DMSR) and deep spatial–spectral coding feature (DMSC)), and three RSI datasets (i.e., Chikusei, ZY1-02D, and Pasture datasets) were employed to validate the DMSRE method. Comparative results of the weak information extraction-based classifications (including DMSR and DMSC) and the raw image-based classifications showed the following: (i) the DMSRs can improve the classification accuracy of individual classes in fine classification applications (e.g., Asphalt class in the Chikusei dataset, from 89.12% to 95.99%); (ii) the DMSC improved the overall accuracy in rough classification applications (from 92.07% to 92.78%); and (iii) the DMSC improved the overall accuracy in RGB classification applications (from 63.25% to 63.6%), whereas DMSR improved the classification accuracy of individual classes on the RGB image (e.g., Plantain classes in the Pasture dataset, from 32.49% to 39.86%). This study demonstrates the practicality and capability of the DMSRE method to promote target recognition on RSIs and presents an alternative technique for weak information mining on RSIs, indicating the potential to extend weak information-based applications of RSIs. Full article

Nitrogen is one of the important factors restricting the development of sesame planting and industry in China. Cultivating sesame varieties tolerant to low nitrogen is an effective way to solve the problem of crop nitrogen deficiency. To date, the mechanism of low nitrogen tolerance in sesame has not been elucidated at the transcriptional level. In this study, two sesame varieties Zhengzhi HL05 (ZZ, nitrogen efficient) and Burmese prolific (MD, nitrogen inefficient) in low nitrogen were used for RNA-sequencing. A total of 3964 DEGs (differentially expressed genes) and 221 DELs (differentially expressed lncRNAs) were identified in two sesame varieties at 3d and 9d after low nitrogen stress. Among them, 1227 genes related to low nitrogen tolerance are mainly located in amino acid metabolism, starch and sucrose metabolism and secondary metabolism, and participate in the process of transporter activity and antioxidant activity. In addition, a total of 209 pairs of lncRNA-mRNA were detected, including 21 pairs of trans and 188 cis. WGCNA (weighted gene co-expression network analysis) analysis divided the obtained genes into 29 modules; phenotypic association analysis identified three low-nitrogen response modules; through lncRNA-mRNA co-expression network, a number of hub genes and cis/trans-regulatory factors were identified in response to low-nitrogen stress including GS1-2 (glutamine synthetase 1–2), PAL (phenylalanine ammonia-lyase), CHS (chalcone synthase, CHS), CAB21 (chlorophyll a-b binding protein 21) and transcription factors MYB54, MYB88 and NAC75 and so on. As a trans regulator, lncRNA MSTRG.13854.1 affects the expression of some genes related to low nitrogen response by regulating the expression of MYB54, thus responding to low nitrogen stress. Our research is the first to provide a more comprehensive understanding of DEGs involved in the low nitrogen stress of sesame at the transcriptome level. These results may reveal insights into the molecular mechanisms of low nitrogen tolerance in sesame and provide diverse genetic resources involved in low nitrogen tolerance research. Full article

Fusarium crown rot (FCR) in wheat is a prevalent soil-borne disease worldwide and poses a significant threat to the production of wheat (Triticum aestivum) in China, with F. pseudograminearum being the dominant pathogen. Currently, there is a shortage of biocontrol resources to control FCR induced by F. pseudograminearum, along with biocontrol mechanisms. In this study, we have identified 37 strains of biocontrol bacteria displaying antagonistic effects against F. pseudograminearum from over 8000 single colonies isolated from soil samples with a high incidence of FCR. Among them, QY43 exhibited remarkable efficacy in controlling FCR. Further analysis identified the isolate QY43 as Pseudomonas aeruginosa, based on its colony morphology and molecular biology. In vitro, QY43 significantly inhibited the growth, conidial germination, and the pathogenicity of F. pseudograminearum. In addition, QY43 exhibited a broad spectrum of antagonistic activities against several plant pathogens. The genomics analysis revealed that there are genes encoding potential biocontrol factors in the genome of QY43. The experimental results confirmed that QY43 secretes biocontrol factor siderophores and pyocyanin. In summary, QY43 exhibits a broad spectrum of antagonistic activities and the capacity to produce diverse biocontrol factors, thereby showing substantial potential for biocontrol applications to plant disease. Full article

Dongbei Suaicai (DBSC) has a complicated microbial ecosystem in which the composition and metabolism of microbial communities during the process have not been well explored. Here, combined metagenomic and metaproteomic technology was used to reveal the taxonomic and metabolic profiles of DBSC. The results showed that firmicutes and proteobacteria were the prevalent bacteria in phylum and Pseudomonas, while Weissella, Pediococcus, and Leuconostoc were the prevalent genus. The vital metabolic pathways were involved in glycolysis/gluconeogenesis [path: ko00010], as well as pyruvate metabolism [path: ko00620], fructose and mannose metabolism [path: Ko00051], glycine, and serine and threonine metabolism [path: Ko00260]. Moreover, the key proteins (dps, fliC, tsf, fusA, atpD, metQ, pgi, tpiA, eno, alaS, bglA, tktA, gor, pdhD, aceE, and gnd) in related metabolized pathways were enriched during fermentation. This study will aid in facilitating the understanding of the fermentation mechanisms of DBSC. Full article

This study designed a control system for the automatic unloading and replenishment of baskets based on the cooperative detection of photoelectric sensors and pressure sensors based on analyzing the structure of the 4UM-120D electric leafy vegetable harvester. The goal of this study was to increase the operation efficiency of leafy vegetable harvesters and decrease the work intensity of operators. A control system for the automatic unloading and replenishment of baskets based on the cooperative detection of a photoelectric sensor and pressure sensor was designed and constructed after an analysis of the operating principle and system components of automatic basket unloading and basket replenishment control at the rear of the harvester. The bench test results showed that the bottom photoelectric sensor and top photoelectric sensors 1 and 2 on the touch screen were not lit and the pressure sensor value was displayed as −0.00075531 kg, after pressing the system start button on the touch screen. On the touch screen, only the basket feeding motor was on: the transverse conveyor motor and the basket unloading motor were not, indicating that there was no collection basket on the unloading basket conveyor belt at this time and that the basket feeding motor was conveying an empty basket to the unloading basket conveyor belt. At 26 s, on the touch screen, only the top photoelectric sensor 2 was not on: the top photoelectric sensor 1 and the bottom photoelectric sensor were on and the pressure sensor value was shown as 1.38488 kg. Only the transverse conveyor motor lit up on the touch screen, the basket unloading motor and the basket feeding motor did not light up, indicating that the leafy vegetables temporarily stored in the transverse conveyor belt started to fall into the collection basket at this time and had not yet reached the expected capacity of the collection basket. At 43 s, the bottom photoelectric sensor and top photoelectric sensors 1 and 2 were lit on the touch screen and the pressure sensor value was shown as 2.37229 kg. On the touch screen, only the basket unloading motor lit up: the transverse conveyor motor and the basket feeding motor were not lit up, indicating that the collection basket capacity had reached the expected capacity at this time and the unloading was in progress. At 83 s, the bottom photoelectric sensor and top photoelectric sensors 1 and 2 were not lit on the touch screen and the pressure sensor value was displayed as −0.0040102 kg. On the touch screen, only the basket feeding motor lit up: the transverse conveyor motor and the basket unloading motor did not light up, indicating that the collection basket with the expected capacity had been unloaded to the ground, and the basket feeding motor was transporting empty baskets to the basket unloading conveyor belt. Through bench simulation tests, it was determined that the control system for the automatic unloading and replenishment of baskets based on the cooperative detection control strategy of the photoelectric sensor and pressure sensor reduced the probability of misjudgment and misoperation and improved system performance. This was conducted with the probability of system misjudgment and misoperation serving as the main evaluation index. The simulation results demonstrated that the control system for the automatic unloading and replenishment of baskets based on a photoelectric sensor and pressure sensor cooperative detection control strategy could be error-free judgment and avoid misoperation, effectively improving the stability, accuracy, and rapidity of the system. The study’s findings could suggest a strategy to lessen the workload of operators and increase the operational effectiveness of harvesters for leafy vegetables. Full article

Fusarium pseudograminearum is one of the major fungal pathogens that cause Fusarium crown rot (FCR) worldwide and can lead to a substantially reduced grain yield and quality. Transcription factors play an important role in regulating growth and pathogenicity in plant pathogens. In this study, we identified a putative Zn(II)₂Cys₆ fungal-type domain-containing transcription factor and named it FpUme18. The expression of FpUME18 was induced during the infection of wheat by F. pseudograminearum. The ΔFpume18 deletion mutant showed defects in growth, conidial production, and conidial germination. In the responses to the cell wall, salt and oxidative stresses, the ΔFpume18 mutant inhibited the rate of mycelial growth at a higher rate compared with the wild type. The staining of conidia and mycelia with lipophilic dye FM4-64 revealed a delay in endocytosis when FpUME18 was deleted. FpUME18 also positively regulated the expression of phospholipid-related synthesis genes. The deletion of FpUME18 attenuated the pathogenicity of wheat coleoptiles. FpUME18 also participated in the production of the DON toxin by regulating the expression of TRI genes. Collectively, FpUme18 is required for vegetative growth, conidiation, stress response, endocytosis, and full virulence in F. pseudograminearum. Full article

Diamond needs to have a perfectly smooth surface due to the growing requirements in the fields of electronic semiconductors, optical windows and high-fidelity loudspeakers. However, the polishing of diamonds is highly challenging due to their exceptional hardness and chemical stability. In this study, a new polishing slurry is prepared for the proposed photocatalysis-assisted chemical mechanical polishing (PCMP) approach to obtain an ultra-smooth surface for large-area diamond. The analyses and experimental findings revealed the significance of the photocatalyst, abrasive, electron capture agent and pH regulator as essential components of the PCMP slurry. TiO₂ with a 5 nm pore size and P25 TiO₂ possess improved photocatalysis efficiency. Moreover, diamond removal is smooth under the acidic environment of H₃PO₄ due to the high oxidation–reduction potential (ORP) of the slurry, and, during the methyl orange test, P25 TiO₂ exhibits reasonable photocatalytic effects. Moreover, in 8 h, a smooth surface free of mechanical scratches can be obtained by reducing the surface roughness from Ra 33.6 nm to Ra 2.6 nm. Full article