Anhui Province Research Articles

Spatio-temporal Characteristics and Influencing Factors of Carbon Sources/Sinks in the Yangtze River Delta Under Carbon Neutrality Target

Clarifying the dynamic relationship between carbon sources/sinks and urban development is crucial to achieving carbon neutrality and sustainable development in the region. This study used net ecosystem productivity （NEP） to evaluate the carbon sinks of the terrestrial ecosystem in the Yangtze River Delta （YRD） from 2005 to 2020. Geodetectors were used to explore the impact of urban expansion, socio-economic factors, and their interactions on carbon sources/sinks in the YRD and to evaluate the gap in achieving carbon neutrality in cities. The results showed that： ① In 2005-2020, the NEP contribution of the YRD was 69.13 Mt·a-1 and the loss of carbon sinks due to urban expansion was 1.97 Mt. The carbon emissions offset by carbon sinks were approximately 3% to 6%. ② The high carbon source areas were mainly distributed in the central and eastern YRD and the high carbon sink areas were primarily distributed in Zhejiang Province and southern Anhui Province. The forest-rich cities of Huangshan and Lishui, with smaller gaps between carbon emissions and carbon sinks, had the greatest potential for achieving carbon neutrality. Industrial or resource-based cities such as Xuzhou and Maanshan faced greater pressure to achieve carbon neutrality. Developed cities such as Shanghai and Suzhou had the largest carbon neutrality gap. ③ Urban expansion, economic and industrial agglomeration, high-density distribution of the population, and compact urban form were the key variables leading to the widening gap between carbon emissions and carbon sinks in the YRD. The increase in ecological space could effectively reduce carbon emissions. Urban expansion and socioeconomic development could be coupled with each other and have significant synergistic effects on carbon emissions.

A framework for flood inundation extraction based on microwave and optical remote sensing images

IntroductionEffective monitoring and evaluation of floodwaters are essential for disaster prevention and mitigation. The flood inundation range can be obtained by using traditional simulation methods, but these methods still have shortcomings. This work proposes an optimization method for traditional methods.MethodsThis study aims to introduce an effective solution for the rapid and accurate extraction of flood inundation areas, emphasizing the enhancement of extraction speed and dynamic monitoring throughout the flood event. The solution uses a normalized difference water index (NDWI), a refined threshold method, and a filtering process for microwave (radar) images. Sentinel-1 SAR (Synthetic Aperture Radar) and Sentinel-2 MSI (Multi-spectral Image) images served as the primary data sources. The Sentinel-2 images were preprocessed to extract pre-flood water bodies, while the Sentinel-1 SAR images were processed using the proposed filtering method to identify post-flood inundation areas.ResultsThe application and validation of this framework are demonstrated through the case of the 2020 flood event in Tongling, Anhui Province. The framework’s performance was validated through comparison with ground truth data, yielding high kappa accuracies of 98% for optical images and 89% for Synthetic Aperture Radar. The findings highlight the framework’s ability to capture high-accuracy changes in flood inundation areas and to characterize the dynamic process of flood inundation area changes.DiscussionThis study contributes to the field by enhancing the extraction speed and scope of water bodies from SAR images and improving the quality of microwave remote sensing data processing. It offers valuable insights for emergency rapid response and situational awareness in the context of extreme weather events and associated flood disasters.

Genomic characterization and tissue tropism variations of two porcine delta coronavirus strains isolated in China

The porcine delta coronavirus (PDCoV) is a member of the Delta coronavirus genus, which can lead to diarrhea, vomiting, and mortality in piglets. First detected in Hong Kong in 2012, PDCoV has since spread globally. In January 2024, two strains, CHN-ANHZ-2024 and CHN-JSSQ-2024, were isolated from diarrheal piglets in Anhui and Jiangsu provinces. Immunofluorescence assays, electron microscopy, and genome sequencing were performed. Genome analysis revealed that both PDCoV strains belonged to the Chinese lineage, exhibiting amino acid mutations in the S1 region compared to other strains within the lineage. Amino acid mutation at position 530L is uniquely associated with the Thai strain. Notably, CHN-JSSQ-2024 was identified as a recombinant strain of DH1 and CHN-AHHN-2024, with the recombination occurring in the S2 subunit. CHN-ANHZ-2024 caused severe diarrhea with an 80% mortality rate, whereas CHN-JSSQ-2024 resulted in mild diarrhea without mortality. Viral load analysis showed CHN-ANHZ-2024 primarily infecting the brain and kidneys, while CHN-JSSQ-2024 targeted the lungs, revealing notable differences in tissue tropism. We designed the RNA scope Probe-PDCoV-N to visualize viral RNA in the positively detected organs, viral RNA was detected in the brain, cerebellum, kidneys, and lungs of the infected piglets. This study highlights significant differences in the pathogenicity and organ tropism of two PDCoV strains. The CHN-ANHZ-2024 strain caused severe diarrhea and high mortality in piglets, while the CHN-JSSQ-2024 strain exhibited much milder symptoms. Additionally, the study elucidated notable differences in organ tropism between the strains, offering valuable insights into the epidemiological characteristics and pathogenic mechanisms of PDCoV. These findings provide a foundation for the development of targeted prevention and treatment strategies tailored to specific strains in the future.

Spatial correlation and urban collaborative governance of air pollution in Anhui province based on complex networks

To promote the greening of the economy and sustainable development, and to achieve a win-win situation for the economy and the environment.By constructing and analyzing the complex network, this study provides a new perspective for understanding the spatial and temporal dynamics of air pollution, and provides a scientific basis for formulating effective air quality improvement measures.This study investigated the seasonal evolution and spatial correlation of air pollutants and AQI in 16 cities in Anhui Province. A weighted undirected complex network for AQI was constructed based on the average correlation coefficients of AQI between different cities, using the ratio of the average correlation coefficient to the distance of the cities as weights. By analyzing the overall statistical characteristics, node importance of the network, and dividing the network into communities, the results show that the atmospheric environmental quality in Anhui Province has significantly improved from 2018 to 2023. Bengbu, Chuzhou, and Hefei occupy the core positions in the network correlation, exhibiting the strongest ability to spread air pollution. The relationship between GDP and AQI between different cities was analysed using the grey correlation method. By combining the results of community division, the correlation between GDP and AQI, and the consideration of policy factors, it is expected that this comprehensive analysis will provide more effective strategies for pollution management, such as optimising and upgrading the industrial structure, perfecting the synergistic management system of air pollution prevention and control among cities, and strengthening regional cooperation for coordinated urban development.

The association between outdoor artificial light at night exposure and antenatal depression and anxiety symptoms: A retrospective cohort study in China

BackgroundOutdoor artificial light at night (ALAN) has emerged as a significant source of environmental pollution, however its association with antenatal depression and anxiety symptoms has not been explored before. MethodsThis study was based on a cohort study conducted at the Maternal and Child Health Care Center in Ma’anshan City, Anhui Province, China, which ultimately included 1047 pregnant women. Depression and anxiety symptoms were evaluated utilizing the self-administered Patient Health Questionnaire (PHQ-9) and the 7-item Generalized Anxiety Scale (GAD-7), respectively. Exposure levels to outdoor ALAN were calculated utilizing satellite data and the participants’ usual addresses. Logistic regression and restricted cubic spline were used to assess the association between exposure to outdoor ALAN and depression and anxiety symptoms in pregnant women. ResultsAfter adjusting for confounding factors, high ALAN exposure during the pre-pregnancy period (ORdepression = 3.16, 95% CI: 1.14∼8.75; ORanxiety = 3.09, 95% CI: 1.51∼6.28) and first trimester (ORdepression = 2.90, 95% CI: 1.13∼7.45; ORanxiety = 3.11, 95% CI: 1.55∼6.25) were associated with increased risks of antenatal depression and anxiety symptoms. Restricted cubic spline analyses showed the above associations were not nonlinear. ConclusionOur study is the first to propose that exposure to high levels of outdoor ALAN three months before pregnancy and during the first trimester of pregnancy is a risk factor for antenatal depression and anxiety symptoms.

Characteristics of the Spatiotemporal Distribution of Influenza Incidence and Its Driving Factors Among Residents in Mainland China From 2004 to 2018.

Influenza is an acute respiratory infection that spreads rapidly and widely in densely populated areas with low vaccination coverage. The trends and drivers of the spatial and temporal dynamics of influenza incidence among residents of mainland China have not been systematically studied. This study comprehensively analyses the dynamics and spatial correlation of influenza using long-term scale data and spatial panel data. It then identifies the interactive process of socio-economic and natural elements on the incidence of influenza. The highest prevalence of influenza was found in the 0-4years age group in mainland China (mean prevalence, 67.56/100,000). In addition, influenza in mainland China shows seasonality, with fall and winter being the periods of high incidence. Between 2014 and 2017, influenza incidence was clustered in Hubei and Anhui provinces, and the spatial clustering was statistically significant (Z value>1.96, P<0.05). Moreover, the directionality of influenza onset continued to increase each year. Specifically, the clustering of influenza onset was stronger in the northwest-southeast direction than in the southwest-northeast direction between 2014 and 2018. The significant role of socioeconomic factors as a primary influence on influenza incidence, while their interaction with natural factors, such as air quality (NOx and PM2.5) and climatic conditions can exacerbate regional outbreaks. This study provides a novel perspective for better prevention and control of influenza disease among mainland Chinese residents.

How to Build a Rural Community to Develop High-Quality Rural Tourism: A Case Study of Innovative Development Strategies for Idle Rural Homesteads in China

In China, rural tourism development constitutes a significant strategy for integrating and utilizing rural resources to achieve rural prosperity. However, reconciling the interests of villagers, government entities, and market actors is difficult in practice, leading to potential pitfalls such as the erosion of rural characteristics, villagers’ rights, and sustainability. The establishment of rural communities in China’s current rural areas can effectively resolve conflicts of interest among diverse stakeholders and address bottlenecks in rural tourism development. However, there is still a lack of theoretical and practical exploration of the maintenance and value realization of rural communities. This study explores the impact of innovative strategies employed during rural tourism development on community growth through a case study of the village of Baifeng in the Anhui province. The results indicate that fostering a sense of community among stakeholders and supporting marginalized groups are the most significant values in the development of rural communities. In practice, effective collaboration and communication among stakeholders, mutual acceptance and conflict resolution, and the development of community emotions/consciousness can help rural communities achieve high-quality construction. This study offers valuable insights into the theoretical advancement of rural communities and represents an excellent case study for the research on rural revitalization and common prosperity.

Evaluating Agricultural Production Efficiency in Jiangsu and Anhui Provinces: A Three-Stage DEA and Malmquist Index Approach

This study assesses the agricultural production efficiency of Jiangsu and Anhui Provinces from 2018 to 2022, with a focus on the impact of the Yangtze River Delta Regional Integration Development Plan. Utilizing a three-stage Data Envelopment Analysis (DEA) model and the Malmquist index, the research controls for environmental factors and analyzes efficiency changes dynamically. The results indicate that Jiangsu achieved a higher rate of technological progress, with an average annual growth rate of 1.0066, which drove its overall productivity gains. In contrast, Anhui demonstrated substantial potential in scale efficiency, reflecting opportunities for future productivity improvements through optimized resource allocation. The regional integration plan appears to have played a pivotal role in advancing agricultural productivity in Jiangsu by facilitating technology-driven improvements. Findings suggest that while Jiangsu should continue to enhance its technological capabilities, Anhui could focus on harnessing its scale efficiency potential to bridge the productivity gap between the two provinces. These insights underscore the significance of regional integration policies in fostering balanced agricultural development, promoting both technological progress and scale efficiency across different regional contexts.

Urban Waterlogging Simulation and Disaster Risk Analysis Using InfoWorks Integrated Catchment Management: A Case Study from the Yushan Lake Area of Ma’anshan City in China

Under the dual pressures of climate change and urbanization, cities in China are experiencing increasingly severe flooding. Using the Yushan Lake area in Ma’anshan City, Anhui Province, as a case study, we employed the InfoWorks Integrated Catchment Management (ICM) hydraulic model to analyze the drainage and flood prevention system of the region and assess the current infrastructure for drainage and flood control. There are 117 pipelines with a return period lower than one year for stormwater and combined sewer systems, accounting for 12.3% of the total number of pipelines. The number of pipelines meeting the one-year but not the three-year return period standard is 700, representing 70.2%. Only 17.5% of the pipelines are capable of handling events exceeding the one-year standard. In simulating a 24 h, 30-year return period rainfall event, the results indicate that floodwater accumulation in the study area is predominantly between 0.15 m and 0.3 m. Most risk areas are classified as low risk, covering an area of 36.398 hectares, followed by medium and high-risk areas, which cover 8.226 hectares and 3.087 hectares, respectively. The Ma’anshan Yushan Lake area has, overall, certain flood control capabilities but faces flood risks during storms with return periods exceeding three years. This research offers valuable insights for improving urban flood management in Ma’anshan City through the development of a stormwater management model for the Yushan Lake area.

Purification of Vein Quartz Using a New Fluorine-Free Flotation: A Case from Southern Anhui Province, China

High-purity quartz is an emerging strategic material that has been extensively used in the semiconductor and photovoltaic fields. Taking vein quartz from southern Anhui Province as an example, raw materials were processed by ultrasonic scrubbing-desliming, magnetic separation, flotation, high-temperature calcination, water quenching, hot-press acid leaching, and deionized water cleaning to prepare high-purity quartz sand. At the same time, the microscopic structure, inclusions, phase, mineral morphology, water content in inclusions, and trace impurities of the gangue samples were analyzed using an optical microscope, a laser Raman spectrometer, an X-ray diffractometer, a scanning electron microscope, an infrared spectrum analyzer, and an inductively coupled plasma mass spectrometer. The results showed that feldspar and muscovite were the main impurities. After purification, the total amount of 13 impurities in quartz sand was reduced to 28.66 μg/g, and the contents of the main impurity elements Al, Na, and Fe were 12.81 μg/g, 12.80 μg/g, and 0.52 μg/g, respectively. The mass fraction of SiO2 increased from 99.06% to 99.9972%. This shows that flotation, high-temperature calcination, and hot-pressing acid leaching are the keys to obtaining high-purity quartz sand. Fluoride-free flotation with the new collector XK02 can effectively realize the deep separation of quartz and mineral impurities. High-temperature calcination can form more cracks on the surface of quartz sand particles, and the mixed acid enters the open crack channels to effectively remove impurities from the inclusions. This method provides technical support for the preparation of high-purity quartz sand with high value and for the efficient utilization of quartz ore.

Characteristics and Functions of Rhizosphere Bacterial Communities of Camelli sinensis cv. Shifocui with Cold Resistance Characteristics in Anhui Province, China.

The rhizosphere bacterial community of plants has a crucial effect on healthy plant growth, and each rhizosphere has a specific microbial community. Camellia sinensis cv. Shifocui (C. sinensis cv. Shifocui) is a tea plant distributed in the Dabie Mountains of Anhui Province. It has the characteristics of high yield, good quality, strong cold resistance, and a high amino acid content. This study was the first to use 16S rRNA high-throughput sequencing technology and bioinformatics methods to explore the characteristics and functions of the rhizosphere bacterial community of the cold-tolerant tea tree C. sinensis cv. Shifocui, providing an important basis for the development and utilization of rhizosphere microbial resources. The dominant phylum in the rhizosphere microbes of the C. sinensis cv. Shifocui rhizosphere microorganisms were Proteobacteria, Chloroflexi, Acidobacteriota, and Actinobacteria. Network analysis showed significant positive and negative correlations among the rhizosphere bacterial groups of C. sinensis cv. Shifocui, among which Candidatus _ Xiphinematobacter, Acidobacteriale, Bradyrhizobium, Subgroup _ 2, Candidatus_Udaeobacter, Gemmataceae, and Gaiellales were notable nodes in theinteraction networks. Functional prediction of FAPROTAX indicated that C. sinensis cv. Shifocui was rich in chemoheterotrophic, cellulose hydrolysis, and oxidative heterotrophic conditions, indicating that the dominant bacterial flora was enriched in its rhizosphere microbes and played an important role in plant growth and development. These results lay a foundation for exploring the mechanism of interaction between C. sinensis cv. Shifocui and rhizosphere microorganisms and provide a research basis for the development and utilization of tea plant microbial resources.

Progressive Conditional Generative Adversarial Network Optimized with Archimedes Optimization Algorithm Fostered Inheritance and Innovation of Huizhou Carving Culture

The past dynasties literature has very few records as the literature of the earlier ones is a novelty and the hereditary secret historical and cultural assets are now at risk. In this study, the inheritance and innovation of the Huizhou carving culture using a progressive conditional generative adversarial network enhanced using the Archimedes Optimization algorithm (HCC-PCGAN-AO) is proposed. Initially, the data are gathered using the onsite Huizhou culture website with three-dimensional data scanning technique. The progressive conditional generative adversarial network (PCGAN) is used to design the Huizhou carving. Then, the Archimedes Optimization algorithm (AOA) is proposed to optimize the Progressive PCGAN classifier, which precisely eliminates errors in the design. It demonstrates the 3D digital carving into architectural cultural property is required and achieves a essential role in preserving the advancing architectural cultural heritage. The proposed HCC-PCGAN-AO method attains 22.13%, 19.46% and 30.65% lower RMSE compared with the existing methods such as Inheritance and Protection of Temple Architectural Cultural Heritage utilizing in the Case of Three-Mountain Kings Ancestral Temple of Jiexi Lintian with Digital Media Technology (IPTA-CH-DMT), Research on Innovative design of tourism cultural and creative products from the perception of Huizhou intangible cultural heritage culture (RID-TCC-HICHC) and Research on the Inheritance along Development of Huizhou Culture in the Construction of New Countryside in Anhui Province (RID-HCC-NCAP) respectively.

Insight into Carbon Emissions in Economically Developed Regions Based on Land Use Transitions: A Case Study of the Yangtze River Delta, China

This study focused on the land use (LU) structure and carbon emissions (CEs) in the Jiangsu, Zhejiang, Anhui, and Shanghai provinces of the Yangtze River Delta (YRD) in China from 2000 to 2020, using the STIRPAT model and scenario analysis (SA). We conducted an analysis of the influence exerted by relevant factors on land use carbon emissions (LUCEs) and made forecasts regarding the diverse development scenarios of CE trends, aiming to provide methodological guidance for validating the effectiveness of existing policies in reducing CEs and offer direction for achieving the peak CO2 emissions target as soon as possible. It also constitutes a significant reference for the early realization of the peak CO2 emissions target. The results indicated the following: (1) Between 2000 and 2020, CEs resulting from LU in the YRD rose from 2.70 × 108 t to 9.10 × 108 t, marking an increase of 243.77%. In 2020, the built-up area was the predominant contributor to CEs, representing 99.15% of the overall carbon sources, whereas forests served as the main carbon sink, comprising 92.37% of the total carbon sinks (CSs) for that year. (2) For each percent increase in the parameters considered in this study, the corresponding increases in LU CO2 emissions were estimated to be: 1.932% (population), 0.241% (GDP per capita), −0.141% (energy intensity), 0.043% (consumption structure), 1.045% (industrial structure), and 0.975% (urbanization). (3) According to the existing policy framework and development plans, the YRD is expected to achieve peaking carbon dioxide emissions by 2030. If energy conservation and carbon reduction strategies are implemented, this peak could be achieved as early as 2025. However, if economic growth continues to depend primarily on fossil fuel consumption, the region may not hit its carbon peak until 2035. (4) The low-carbon scenario, which considers the needs of social progress alongside the intensity of carbon emission reductions, represents the most effective development strategy for reaching a carbon peak in LU within the YRD. Effectively managing population size and facilitating the upgrading of industrial structures are key strategies to hasten the achievement of peaking carbon dioxide emissions in the region.

Building and verifying a prediction model for deep vein thrombosis among spinal cord injury patients undergoing inpatient rehabilitation

ObjectiveTo explore the relevant variables that contribute to deep vein thrombosis (DVT) among spinal cord injury patients undergoing inpatient rehabilitation and to build and validate a nomogram model that predicts DVT risk. MethodsBy convenience sampling, 558 spinal cord injury patients who were hospitalized at a tertiary-level Grade A general hospital in Anhui Province, China, between January 2017 and March 2022 were chosen as the study subjects. They were split into two groups at random, one for training (n = 446) and the other for validation (n = 112). The ratio was 8:2. The clinical information of patients was gathered, including sociodemographic characteristics, data about disease characteristics, and examinations pertaining to laboratories. The related factors of DVT among spinal cord injury patients undergoing inpatient rehabilitation were analyzed using both univariate and multivariate logistic regression. Utilizing the variables identified by the multivariate logistic regression analysis, we constructed a predictive nomogram model with the aid of the R software. The model's predictive accuracy for assessing the risk of DVT was validated through the use of receiver operating characteristic (ROC) curves and calibration plots. ResultsProthrombin time (PT), D-dimer, age, and Caprini score were independent related factors for DVT among spinal cord injury patients undergoing inpatient rehabilitation, according to multivariate logistic regression analysis (OR > 1, P<0.05). This four variables selected by the multivariate logistic regression analysis was used to build a nomogram risk model, which was found to have strong predictive capacity for predicting the risk of DVT among spinal cord injury patients undergoing inpatient rehabilitation. The nomogram model's area under the ROC curve in the training group and validation group was 0.793 and 0.905, and the 95% confidence intervals were 0.750∼0.837 and 0.830∼0.980, separately, indicating good discrimination of the nomogram model. A good calibration of the model was shown by the calibration curve, which was well consistent between the model's predicted probability and the actual frequency of DVT in both the training and validation groups. ConclusionProthrombin time, D-dimer level, age and Caprini score are independent related factors for DVT among spinal cord injury patients undergoing inpatient rehabilitation. According to the variables mentioned previously, a nomogram model was constructed that can accurately and easily predict DVT risk among spinal cord injury patients undergoing inpatient rehabilitation. This facilitates the early identification of high-risk groups and the timely implementation of prevention, treatment, rehabilitation, and nursing strategies by clinical medical staff.

Research hotspots and paths of traditional houses in Huizhou, Anhui province, China: A visualization analysis using CiteSpace

As a representative of China&amp;rsquo;s vernacular architecture with unique forms and rich cultural connotations, Huizhou&amp;rsquo;s traditional dwellings have gained international recognition as a World Cultural Heritage site. These dwellings serve as a pi vital case study in exploring the dynamic relationship between globalization and local identity. This study employs CiteSpace software to visualize and analyze literature on traditional Huizhou houses published since 2000. We investigated publication trends and author and institutional collaboration networks and identified major research hotspots and their evolutionary paths at each stage by applying keyword co-occurrence, clustering, and emergence mapping. The results reveal three main phases in academic research on Huizhou traditional dwellings: from 2000 to 2010, studies primarily dissected architectural features and cultural connotations; from 2011 to 2020, research focused on the application of Huizhou&amp;rsquo;s traditional architectural and cultural symbols within contemporary design; and from 2021 to 2023, preliminary exploration began into the industrialized development and spatial narratives of Huizhou architectural elements. Although research on Huizhou&amp;rsquo;s traditional houses has yielded substantial insights, collaboration among authors and institutions remains limited, and theoretical innovation is insufficient. Future studies should prioritize multidisciplinary collaboration and quantitative analysis to advance the integration and sustainable development of theory and practice in this field.

Disability status investigation and risk prediction model for middle-aged and older adults in Anhui Province: A derivation and validation study.

This study investigated the disability status of middle-aged and older adults in Anhui Province, China, with a primary focus on physical disability, and constructed a nomogram to predict disability risk. Data was collected through a province-wide questionnaire survey conducted in 16 cities and counties from January to December 2021, involving 3386 participants aged 60 years and above. The abilities of daily living (ADL) scale assessed participants' comprehensive ability. Risk factors for disability were identified using least absolute shrinkage and selection operator and logistic regression, highlighting six independent factors: age, poor sleep quality, depression, malnutrition, stroke, and the number of comorbid chronic diseases. A nomogram prediction model was then established and validated internally and externally. The model demonstrated good fit according to the Hosmer-Lemeshow test and provided significant benefits across various thresholds, as shown by decision curve analysis. This nomogram accurately and quickly identifies high-risk groups, aiding in early intervention.

Four new species of leptonetid spiders (Araneae, Leptonetidae) from Anhui Province, China.

Four new species of leptonetid spiders from Anhui Province, China are recognized: Jingnetaqishan Tong, sp. nov. (♂♀), Jingnetawukuishan Tong, sp. nov. (♂), Leptonetelajingde Tong, sp. nov. (♂♀) and Rhyssoleptonetalishan Tong, sp. nov. (♂♀). An identification key to leptonetid spiders from Anhui is provided.

Tanshinone Content Prediction and Geographical Origin Classification of Salvia miltiorrhiza by Combining Hyperspectral Imaging with Chemometrics.

Hyperspectral imaging (HSI) technology was combined with chemometrics to achieve rapid determination of tanshinone contents in Salvia miltiorrhiza, as well as the rapid identification of its origins. Derivative (D1), second derivative (D2), Savitzky-Golay filtering (SG), multiplicative scatter correction (MSC), and standard normal variate transformation (SNV) were utilized to preprocess original spectrum (ORI). Partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) models were employed to discriminate 420 Salvia miltiorrhiza samples collected from Shandong, Hebei, Shanxi, Sichuan, and Anhui Provinces. The contents of tanshinone IIA, tanshinone I, cryptotanshinone, and total tanshinones in Salvia miltiorrhiza were predicted by the back-propagation neural network (BPNN), partial least square regression (PLSR), and random forest (RF). Finally, effective wavelengths were selected using the successive projections algorithm (SPA) and variable iterative space shrinkage approach (VISSA). The results indicated that the D1-PLS-DA model performed the best with a classification accuracy of 98.97%. SG-BPNN achieved the best prediction effect for cryptotanshinone (RMSEP = 0.527, RPD = 3.25), ORI-BPNN achieved the best prediction effect for tanshinone IIA (RMSEP = 0.332, RPD = 3.34), MSC-PLSR achieved the best prediction effect for tanshinone I (RMSEP = 0.110, RPD = 4.03), and SNV-BPNN achieved the best prediction effect for total tanshinones (RMSEP = 0.759, RPD = 4.01). When using the SPA and VISSA, the number of wavelengths was reduced below 60 and 150, respectively, and the performance of the models was all very good (RPD > 3). Therefore, the combination of HSI with chemometrics provides a promising method for predicting the active ingredients of Salvia miltiorrhiza and identifying its geographical origins.

Multiscale Spatiotemporal Variation Analysis of Regional Water Use Efficiency Based on Multifractals

Understanding the complex variations in water use efficiency (WUE) is critical for optimizing agricultural productivity and resource management. Traditional analytical methods often fail to capture the nonlinear and multiscale variations inherent in WUE, where multifractal theory offers distinct advantages. Given its limited application in WUE studies, this paper analyzes the spatiotemporal characteristics and influencing factors of the WUE in Anhui Province from 2001 to 2022 using a multifractal, multiscale approach. The results indicated that the WUE exhibited significant interannual variation, peaking in summer, especially in August (2.4552 gC·mm−1·m−2), with the monthly average showing an inverted “V” shape. Across different spatial and temporal scales, the WUE displayed clear multifractal characteristics. Temporally, the variation in fractal features between years was not prominent, while inter-seasonal variation was most complex in August during summer. Spatially, the most distinct multifractal patterns were observed in hilly and mountainous areas, particularly in regions with brown soil distribution. Rainfall was identified as the primary natural driver influencing regional WUE changes. This study aims to promote the sustainable use of water resources while ensuring the stability of agricultural production within protected farmlands.

Comparison of the Photosynthesis, Hydraulic Properties, and Anatomy of Pteroceltis tatarinowii Leaves Between a Limestone and a Cultivated Forest.

Pteroceltis tatarinowii Maxim is a famous paper-making tree endemic to China with a wide distribution. Leaves of this tree growing in different habitats show a certain plasticity, which is important for their ecological adaption. Here, the photosynthesis ability, hydraulic properties, and anatomy of P. tatarinowii leaves from a limestone forest (Langya Mountain) and a cultivated forest (Xiaoling Village) in Anhui province were compared. The results showed that leaves from Xiaoling Village had higher net photosynthesis rate and hydraulic conductivity, which were closely related to their higher vein density, stomatal density and palisade tissue thickness than leaves from Langya Mountain. However, lower leaf water potentials at turgor loss point and at 50% loss of conductivity, as well as a higher leaf hardness, for Langya Mountain leaves indicated their higher hydraulic safety and drought resistance than those of leaves from Xiaoling Village. This study reveals a hydraulic trade-off between efficiency and safety for P. tatarinowii leaves growing in distinct habitats. Further studies should include more habitats and different vegetation communities to clarify the ecological adaption so as to provide a scientific basis for the protection of this species.