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To solve the problem of the insufficient driving force and low adoption rate of conservation tillage adoption and to enhance the effect of industrial organization in influencing technology diffusion, this paper explored the relationship and the mechanism of perceived organizational support and inter-temporal choice in the adoption of conservation tillage by using micro-research data from 725 melon farmers in the Shaanxi and Shanxi provinces in China and by applying the experimental economics method to obtain the inter-temporal choices of the farmers. This paper also analyzed farmers' risk preferences' moderating effect on the relationship between inter-temporal choice and conservation tillage. Additionally, it examined the impact of perceived organizational support on the differentiation of different conservation tillage technologies. The study found that perceived organizational support significantly contributes to adopting zero tillage and minimum tillage, and water-saving irrigation. Perceived organizational support was not conducive to farmers' adoption of furrow and ridge tillage. The impact of perceived organizational support on technology adoption is heterogeneous, depending on the differences in the size of the family's cultivated land. The inter-temporal choice of farmers significantly impedes the adoption of conservation tillage. The increase in risk preference helps alleviate the hindering effect of inter-temporal choice on farmers' adoption of conservation tillage. Perceived organizational support can promote the adoption of conservation tillage by reducing farmers' inter-temporal choices. Inter-temporal choice is an essential mechanism by which perceived organizational support affects the adoption of conservation tillage. Compared with the existing studies, this paper incorporates the technology-attribute-induced inter-temporal choice of farmers into the impact analysis framework and considers the relationship between perceived organizational support, inter-temporal choice, and the adoption of conservation tillage and the mechanism of its action. The findings of the study provide a theoretical basis for the enrichment of incentive mechanisms for the adoption of conservation tillage, which is of great significance for the improvement of the tool for the integration of small farmers in developing countries into the industrial activities of the new agricultural business central bodies and for promoting the diffusion of conservation tillage in agriculture. [ABSTRACT FROM AUTHOR]

Accurate medium- and long-term runoff prediction models play crucial guiding roles in regional water resources planning and management. However, due to the significant variation in and limited amount of annual runoff sequence samples, it is difficult for the conventional machine learning models to capture its features, resulting in inadequate prediction accuracy. In response to the difficulties in leveraging the advantages of machine learning models and limited prediction accuracy in annual runoff forecasting, firstly, the variational mode decomposition (VMD) method is adopted to decompose the annual runoff series into multiple intrinsic mode function (IMF) components and residual sequences, and the spectral clustering (SC) algorithm is applied to classify and reconstruct each IMF. Secondly, an annual runoff prediction model based on the adaptive particle swarm optimization–long short-term memory network (APSO-LSTM) model is constructed. Finally, with the basis of the APSO-LSTM model, the decomposed and clustered IMFs are predicted separately, and the predicted results are integrated to obtain the ultimate annual runoff forecast results. By decomposing and clustering the annual runoff series, the non-stationarity and complexity of the series have been reduced effectively, and the endpoint effect of modal decomposition has been effectively suppressed. Ultimately, the expected improvement in the prediction accuracy of the annual runoff series based on machine learning models is achieved. Four hydrological stations along the upper reaches of the Fen River in Shanxi Province, China, are studied utilizing the method proposed in this paper, and the results are compared with those obtained from other methods. The results show that the method proposed in this article is significantly superior to other methods. Compared with the APSO-LSTM model and the APSO-LSTM model based on processed annual runoff sequences by single VMD or Wavelet Packet Decomposition (WPD), the method proposed in this paper reduces the RMSE by 40.95–80.28%, 25.26–57.04%, and 15.49–40.14%, and the MAE by 24.46–80.53%, 16.50–59.30%, and 16.58–41.80%, in annual runoff prediction, respectively. The research has important reference significance for annual runoff prediction and hydrological prediction in areas with data scarcity. [ABSTRACT FROM AUTHOR]

The food crisis has increased demand for agricultural resources due to various factors such as extreme weather, energy crises, and conflicts. A solar greenhouse enables counter-seasonal winter cultivation due to its thermal insulation, thus alleviating the food crisis. The root temperature is of critical importance, although the mechanism of soil thermal environment change remains uncertain. This paper presents a comprehensive study of the soil thermal environment of a solar greenhouse in Jinzhong City, Shanxi Province, employing a variety of analytical techniques, including theoretical, experimental, and numerical simulation, and deep learning modelling. The results of this study demonstrate the following: During the overwintering period, the thermal environment of the solar greenhouse floor was divided into a low-temperature zone, a constant-temperature zone, and a high-temperature zone; the distance between the low-temperature boundary and the southern foot was 2.6 m. The lowest temperature in the low-temperature zone was 11.06 °C and the highest was 19.05 °C. The floor in the low-temperature zone had to be heated; the lowest value of the constant-temperature zone was 18.29 °C, without heating. The minimum distance between the area of high temperature and the southern foot of the solar greenhouse was 8 m and the lowest temperature reading was 19.29 °C. The indoor soil temperature tended to stabilise at a depth of 45 cm, and the lowest temperature reading at a horizontal distance of 1400 mm from the south foot was 19.5 °C. The Fluent and LSTM models fitted well and the models can be used to help control soil temperature during overwintering in extreme climates. The research can provide theoretical and data support for the crop areas and the heating of pipelines in the solar greenhouse. [ABSTRACT FROM AUTHOR]

Carbon storage services play an important role in maintaining ecosystem stability. Land use/cover change (LUCC) is the main factor leading to changes in ecosystem carbon storage. Understanding the impact of LUCC on regional carbon storage changes is crucial for protecting regional ecosystems and promoting sustainable socio-economic development. This paper selects Shanxi province as the study area and explores the spatial and temporal evolution characteristics of carbon storage in Shanxi province based on the InVEST model and univariate spatial autocorrelation. The results show that the total carbon storage in Shanxi Province in 2000, 2010, and 2020 is 513.51 × 104 t C, 513.46 × 104 t C, and 509.29 × 104 t C, respectively. High carbon storage areas are distributed in forest and grassland land types, while low carbon storage areas are widely distributed in building land in urban metropolitan areas. Shanxi Province is mainly dominated by farmland, which has decreased by 3448.60 km2 in the past 20 years. Grassland has decreased by 1588.31 km2 and the area of building land has increased by 4205.73 km2. Due to the influence of carbon conversion among different land use types, the total carbon storage loss of Shanxi Province in the past 20 years was 4.21 × 104 t C. The transfer of farmland resulted in an increase in carbon stock of 14.46 × 104 t C. The transfer of grassland resulted in an increase of 17.15 × 104 t C, while the transfer of forest resulted in a decrease of 41.44 × 104 t C. The increase in land use types with low carbon density and the decrease in land use types with high carbon density led to the decrease in carbon storage in Shanxi Province. Furthermore, social factors were more likely to influence the carbon storage than natural factors, and the influence of social factors was often negative. On this basis, regional development countermeasures were proposed for the current situation of carbon storage in Shanxi Province and provide a scientific basis for Shanxi Province to achieve the carbon neutrality target. [ABSTRACT FROM AUTHOR]

Encouraging the use of conservation tillage technology is a highly effective approach to safeguarding soil health, improving the environment, and promoting sustainable agricultural development. With the mounting concerns surrounding climate change, developing conservation tillage methods that facilitate sustainable agricultural growth has become an imperative both in China and around the world. While it is widely recognized that adapting to climate change is crucial in agriculture, there is limited research on evaluating the risks, discovering resilience, measuring farmers' perceptions on climate change, and exploring how tillage technology can be adjusted in the context of small-scale farming in China to foster sustainable development. Using research data from smallholder farmers in the Shaanxi and Shanxi provinces of China, this paper aims to explore the impact of climate change perceptions on farmers' adoption of conservation tillage technologies based on an ordered Probit model. We found that farmers tend to refrain from embracing conservation tillage technology due to the presence of unclear and conflicting perceptions regarding climate change. Focus on short-term profitability and inadequate preparation hinder them from prioritizing adaptation. We recognized several measures that could help farmers adapt and thrive within the agricultural sector. Furthermore, we have validated the need for self-system moderation in promoting farmers' adoption of conservation tillage technology. By utilizing such tools and resources, farmers can comprehend the gravity of climate change's impact on agricultural productivity and, more importantly, channel their efforts towards fortifying resilience to extreme weather conditions and long-term climate risks, thus fortifying agricultural sustainability. [ABSTRACT FROM AUTHOR]

Rainfall erosivity, which signifies the inherent susceptibility of soil erosion induced by precipitation, plays a fundamental role in formulating a comprehensive soil loss equation (RUSLE). It stands as a crucial determinant among the foundational factors considered in a comprehensive soil loss equation's establishment. Nonetheless, the prediction and quantification of future alterations in rainfall erosivity under the influence of global warming have been relatively limited. In this study, climate change was widely evaluated and 10 preferred global climate models in the Loess Plateau were selected by using the data sets of 27 models simulating climate change and the CN05.1 data set provided by the latest CMIP6. The monthly precipitation forecast data were obtained by using the delta downscaling method. Combined with trend analysis, significance test, and coefficient of variation, the annual rainfall erosivity during 1961–2100 under four SSP scenarios was analyzed and predicted. Among the 27 GCM models used in this paper, the most suitable climate models for simulating monthly precipitation in the Loess Plateau were CMCC-CM2-SR5, CMCC-ESM2, TaiESM1, EC-Earth3, EC-Earth-Veg-LR, INM-CM4-8, CAS-ESM2-0, EC-Earth-Veg, ACCESS-ESM1-5, and IPSL-CM6A-LR. In comparison to the base period (1961–1990), during the historical period (1961–2014), the average annual rainfall erosivity on the Loess Plateau amounted to 1259.64 MJ·mm·hm−2·h−1·a−1, showing an insignificant downward trend. In the northwest of Ningxia, Yulin City and Yanan City showed a significant upward trend. In the future period (2015–2100), the annual rainfall erosivity continues to constantly change and increase. The potential average increase in rainfall erosivity is about 13.48–25.86%. In terms of spatial distribution, most areas showed an increasing trend. Among these regions, the majority of encompassed areas within Shanxi Province, central Shaanxi, and Inner Mongolia increased greatly, which was not conducive to soil and water conservation and ecological environment construction. This study offers a scientific reference for the projected future erosivity characteristics of the Loess Plateau. [ABSTRACT FROM AUTHOR]

To investigate the contents of carbon, nitrogen, and phosphorus in tea plantation soils and their ecological stoichiometric characteristics, as well as their response to environmental factors in high-latitude regions of China, soil samples from 0 to 20 cm depth were collected from tea plantations at different altitudes and cultivation years in the main tea-producing areas of Shaanxi Province. These samples were used to determine the soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents and to calculate their stoichiometric ratios. The findings revealed the following: the average soil SOC and TN content in tea gardens were 13.15 and 1.30 g·kg−1, respectively, exceeding the national soil average. These values met the Class I tea garden fertility standards. However, the average soil TP content, at 0.45 g·kg−1, fell below the national soil average, meeting the Class II tea garden fertility standards. In tea gardens, the average ratios of carbon to nitrogen (C:N), carbon to phosphorus (C:P), and nitrogen to phosphorus (N:P) in the soil were 10.42, 30.98, and 3.32, respectively. These ratios were all lower than the national soil average, indicating relatively high phosphorus availability but nitrogen deficiency in tea garden soils. As altitude increased, there was a decline in soil SOC content, C N, and C P ratios, followed by a subsequent increase. No significant changes were seen in TN, TP, and N P ratio in the soil, but there was an increase in SOC content, TN content, and C P ratio during cultivation. The N-to-P ratio initially increased before decreasing, while the C-to-N ratio decreased before increasing. Soil TP content did not change significantly. The study recommends careful nitrogen fertilizer application in tea garden management to balance nitrogen and phosphorus. [ABSTRACT FROM AUTHOR]

Extreme drought and flood events, as well as their combined events, pose significant challenges to global sustainable socio-economic development and ecological health. However, the impact of dry–wet combination events (DWCEs) on vegetation vulnerability remains to be investigated. The Loess Plateau (LP) was selected as the study area to explore the response time of vegetation to precipitation index changes by optimal correlation coefficient; then, the impact of different DWCEs on vegetation vulnerability under moderate and severe scenarios was analyzed; finally, a vegetation loss probability model was constructed based on the copula function and Bayesian framework, to quantify the vegetation loss probability under DWCEs stress. The results indicate that: (1) normalized difference vegetation index (NDVI) shows an upward trend in spring, summer, and autumn, with the proportion of areas are 90.5%, 86.2%, and 95.4%, respectively, and show an insignificant trend in winter; (2) the response time of vegetation to precipitation index changes tends to be one or two seasons; (3) moderate scenarios have more influence than severe scenarios, dry-to-wet events (DWEs), wet-to-dry events (WDE) and continuous dry events (CDE) in spring-summer have a significant impact on summer vegetation of Ningxia and Shanxi, and WDE and CDE have a higher impact on autumn vegetation. (4) in terms of the probability of vegetation loss, DWE, and CDE cause higher losses to summer vegetation, while WDE and CDE cause higher losses to autumn vegetation. This study quantifies the impact of adjacent seasonal DWCE stress on future vegetation vulnerability. [ABSTRACT FROM AUTHOR]

Forests are vital for terrestrial ecosystems, providing crucial functions like carbon sequestration and water conservation. In the Yellow River Basin, where 70% of forest coverage is concentrated in the middle reaches encompassing Sichuan, Shaanxi, and Shanxi provinces, there exists significant potential for coal production, with nine planned coal bases. This study centered on Jincheng City, Shanxi Province, a representative coal mining area in the Yellow River Basin, and combined the MSPA analysis method and MCR model to generate the five-period forest ecological network of Jincheng City from 1985 to 2022 under the background of coal mining and calculate the degree centrality, closeness centrality, betweenness centrality, and eigenvector centrality; the correlation between the four centralities and carbon sequestration ability is further explored. Simultaneously, employing the RAND-ESU algorithm for motif identification within forest ecological networks, this study integrates the ecological policies of the research area with the specific conditions of the coal mining region to optimize the forest ecological network in Jincheng City. Findings reveal the following. (1) Forest ecological spatial networks: Forest ecological networks exhibit robust overall ecological connectivity in the study area, with potential ecological corridors spanning the region. However, certain areas with high ecological resistance hinder connectivity between key forest ecological nodes under the background of coal mining. (2) Correlation between topological indices and carbon sequestration ecological services: From 1985 to 2022, the carbon sequestration capacity of Jincheng City's forest source areas increased year by year, and significant positive correlations were observed between degree centrality, betweenness centrality, eigenvector centrality with carbon sequestration ecological services, indicating a strengthening trend over time. (3) Motif Recognition and Ecological Network Optimization: During the study, four types of motifs were identified in the forest ecological network of Jincheng City based on the number of nodes and their connections using the RAND-ESU network motif algorithm. These motifs are 3a, 4a, 4b, and 4d (where the number represents the number of nodes and the letter represents the connection type). Among these, motifs 3a and 4b play a crucial role. Based on these motifs and practical considerations, network optimization was performed on the existing ecological source areas to enhance the robustness of the forest ecological network. [ABSTRACT FROM AUTHOR]

There is a huge reservation of loess in the Shanxi mining area in China, which has great potential for preparing supplementary cementitious materials. Loess was modified via mechanical and thermal activation, and the pozzolanic activity was evaluated using an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). Moreover, the workability of grouting materials prepared using modified loess was assessed. The experimental results revealed that the number of ultrafine particles gradually increased with the grinding time, enhancing the grouting performance. The coordination number of Al decreased upon the breakage of the Al–O–Si bond post-calcination at 400 °C, 550 °C, 700 °C, and 850 °C. Moreover, the breaking of the Si–O covalent bond produced Si-phases, and the pozzolanic activity of loess increased. Furthermore, the modified loess was hydrated with different cement proportions. With increasing grinding time, the overall setting time increased until the longest time of 14.5 h and the fluidity of the slurry decreased until the lowest fluidity of 9.7 cm. However, the fluidity and setting time decreased with increasing calcination temperature. The lowest values were 12.03 cm and 10.05 h. With the increase in pozzolanic activity, more ettringite was produced via hydration, which enhanced the mechanical properties. The maximum strength of the hydrated loess after grinding for 20 min reached 16.5 MPa. The strength of the hydrated loess calcined at 850 °C reached 21 MPa. These experimental findings provide theoretical support for the practical application of loess in grouting. [ABSTRACT FROM AUTHOR]

This study systematically investigates the impact of pre-stretching amount (PSA) on the acceleration, motion status, and screening efficiency of the Flip-flow screen plate (FFSP). Initially, a nonlinear spring-multi-body model of the FFSP is established. Subsequently, the acceleration signals at the midpoint of the FFSP under various PSAs are measured and analyzed. The nonlinear stiffness coefficient of FFSP along the vertical direction is then determined and it is found that simplifying the nonlinear spring-multi-body system to a nonlinear spring-tri-body system under the experimental conditions can maintain the calculation error of FFSP's acceleration within 30%. Phase and Poincaré mapping diagrams of the FFSP under different PSAs are subsequently created to illustrate the impact of PSA on the motion status of the FFSP. Finally, screening experiments are performed to study the optimal PSA for a kind of bituminous coal from Shanxi province. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the characteristics of the combined application of organic fertilizer and inorganic fertilizer using different tillage methods to delay the senescence of maize leaves. The yield and activities of GDH, CAT, APX, GR, and GSH enzymes in maize leaves were measured at different growth stages by using two tillage methods, three organic and inorganic combined applications (P1, P2, and P3), and four control treatments. (1) During the growth period, the R + S and R treatments were P1 treatments, with the highest enzyme activities noted for GDH, CAT, APX, GR, and GSH, which were 36.79–103.22% higher than those of CK. (2) The average yield of all R + S treatments was higher than that of R treatments, and the average yield of P1 treatment was the highest under R + S, which was 13,663.79 kg hm−2, which was 6.39%, 7.90%, and 14.67% higher than that of P2, P3, and CK, respectively, which was lower than that of R. The yield of P1 treatment was 2.53% higher. (3) There was a significant positive correlation between APX activity, CAT activity, GR activity, GDH activity, GSH activity, grain number per ear, ear length, and 100-grain weight of maize leaves at the grain filling stage, and a significant negative correlation between bald tip length and yield. The treatment details had the strongest enzyme activity and the highest yield when using the rotary tillage + subsoiling (R + S) P1 method, which was the most suitable tillage method and the best fertilizer ratio combination, which could be demonstrated and popularized in a large area in the dry farming area of spring maize in Shanxi Province. [ABSTRACT FROM AUTHOR]

Strong soil erosion and increasing human activities have made Loess Plateau areas ecologically fragile regions. Constructing the ecological security pattern (ESP) is imperative to maintain their ecosystem functions and sustainable development. However, it is still challenging to establish the ESP in such an unstable and scattered ecological environment. In this study, we take Shanxi Province, which suffers severe ecological problems in Loess Plateau areas, as an example to construct the ESP in a pattern of "source-resistance-corridor". The proposed methods include the following steps: (1) potential ecological sources are selected with important ecosystem functions based on contributions of soil and water conservation, habitat quality, and carbon storage; (2) ecological sources are determined by considering core areas at the landscape scale based on morphological spatial pattern analysis (MSPA) along with stability based on dynamic assessment on previous sources; (3) the comprehensive resistance surface is constructed by multiple resistance factors and remotely sensed nighttime light data; (4) ecological corridors are simulated and extracted based on circuit theory. As a result, the proposed ESP in our study area mainly includes 13,592 km2 of ecological sources, 8519.64 km of ecological corridors, and 277 ecological nodes. Meanwhile, an ecological framework of "two axes, three belts, and three zones" was proposed based on the optimization and reorganization of ecological components within the ESP. Our research lays a methodological and practical foundation for regional ESP construction and sustainable development in Loess Plateau areas. [ABSTRACT FROM AUTHOR]

Bromus japonicus is a common monocot weed that occurs in major winter wheat fields in the Huang–Huai–Hai region of China. Pyroxsulam is a highly efficient and safe acetolactate synthase (ALS)-inhibiting herbicide that is widely used to control common weeds in wheat fields. However, B. japonicus populations in China have evolved resistance to pyroxsulam by different mutations in the ALS gene. To understand the resistance distribution, target-site resistance mechanisms, and cross-resistance patterns, 208 B. japonicus populations were collected from eight provinces. In the resistant population screening experiment, 59 populations from six provinces showed different resistance levels to pyroxsulam compared with the susceptible population, of which 17 B. japonicus populations with moderate or high levels of resistance to pyroxsulam were mainly from the Hebei (4), Shandong (4) and Shanxi (9) Provinces. Some resistant populations were selected to investigate the target site-resistance mechanism to the ALS-inhibiting herbicide pyroxsulam. Three pairs of primers were designed to amplify the ALS sequence, which was assembled into the complete ALS sequence with a length of 1932 bp. DNA sequencing of ALS revealed that four different ALS mutations (Pro-197-Ser, Pro-197-Thr, Pro-197-Phe and Asp-376-Glu) were found in 17 moderately or highly resistant populations. Subsequently, five resistant populations, QM21-41 with Pro-197-Ser, QM20-8 with Pro-197-Thr and Pro-197-Phe, and QM21-72, QM21-76 and QM21-79 with Asp-376-Glu mutations in ALS genes, were selected to characterize their cross-resistance patterns to ALS inhibitors. The QM21-41, QM20-8, QM21-72, QM21-76 and QM21-79 populations showed broad-spectrum cross-resistance to pyroxsulam, mesosulfuron–methyl and flucarbazone–sodium. This study is the first to report evolving cross-resistance to ALS-inhibiting herbicides due to Pro-197-Phe mutations in B. japonicus. [ABSTRACT FROM AUTHOR]

Based on the 'three highs and one low' geological conditions of high gas pressure, high gas content, high ground stress, and low permeability in deep coal seams, this study proposes a dual method of hydraulic fracturing of key layers of overlying rock layers combined with pre-extraction of gas via large-diameter caving boreholes. The aim is to unload and dissipate the coal seam by fracturing the overlying key strata, allowing the stress and energy from the excavation working face to be transmitted and transferred to the deep coal seam. Additionally, large-diameter drilling effectively increases the effective drainage radius of the coal seam, resulting in a shorter extraction time. To validate this approach, a fracturing model and a gas extraction model were established for the key layers of the overlying rock layer using the engineering background of the 15,111 excavation working face of a mine in Shanxi. FLAC3D software v.6.0 was utilized to simulate the stress and energy changes of the coal seam before and after fracturing of the key layers, while COMSOL software v.6.0 was used to analyze the gas migration conditions, permeability, and effective drainage radius changes before and after drilling and caving drilling. The findings, combined with the engineering test results, conclude that key strata fracturing combined with large-diameter caving can effectively increase the permeability of coal seams and improve gas extraction. This study serves as a theoretical basis for guiding the design of gas drainage technology under the effects of coal seam pressure relief and permeability enhancement. [ABSTRACT FROM AUTHOR]

Simple Summary: Caprine arthritis encephalitis is an infectious disease caused by the caprine arthritis encephalitis virus (CAEV). This virus can impair the quality of goat's milk, lamb, and other goat products. Most goats are latently infected with this virus and become long-term carriers, so the development of a rapid and accurate diagnostic method is necessary. Therefore, we constructed a TaqMan real-time quantitative polymerase chain reaction (RT-qPCR) assay and used it to detect CAEV in sheep in eastern China. We found that the prevalence of CAEV infection in sheep in eastern China was 0.77%. This method yields positive results when testing positive references and negative results when testing negative controls or other viruses. The consistency of these results was confirmed through repeating the experiment multiple times. It demonstrated excellent sensitivity, specificity, and reproducibility and holds great promise for its potential application in clinical and field samples in the future. Caprine arthritis encephalitis is an infectious disease caused by the caprine arthritis encephalitis virus that infects goats, sheep, and other small ruminants. An outbreak of CAEV could be extremely harmful to the goat farming industry and could cause severe economic losses. We designed specific primers and probes for the gag gene and established a TaqMan real-time quantitative polymerase chain reaction assay. This method's correlation coefficient (R2) was >0.999, and the sensitivity of the assay to the plasmid-carried partial gag gene was approximately 10 copies/µL, 1000 times higher than that of conventional PCR. No specific fluorescence was detected for other sheep viruses. Using this method, we tested 776 asymptomatic sheep blood samples and 4 neurodegenerative sheep brain samples from six farms in eastern China, and the positivity rate was 0.77% (6/780). The gag gene was partially sequenced in the three positive samples and compared with the sequences from other representative strains in GenBank. The results revealed that all three strains belonged to the B1 subtype and were most closely related to the strains from Shanxi and Gansu, previously isolated in China, with their homology ranging from 97.7% to 98.9%. These results suggest that the designed RT-qPCR assay can be used to detect subclinical CAEV in sheep and that the virus is still present in eastern China. [ABSTRACT FROM AUTHOR]

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964–2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha−1 yr−1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008–2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region [ABSTRACT FROM AUTHOR]

The pollution of agricultural soil by heavy metals is a significant environmental issue that has a serious impact on human health and food security. This study focused on investigating the presence of heavy metal pollution in sewage-irrigated soils in Taiyuan city. A total of 110 soil samples were analyzed for the presence of As, Hg, Cd, Pb, Cr, Cu and Zn. The results showed that the concentrations of these metals ranged from 0.06 to 26.74 mg/kg for As, 0.00 to 0.84 mg/kg for Hg, 0.03 to 0.69 mg/kg for Cd, 44.32 to 100.09 mg/kg for Pb, 9.85 to 42.19 mg/kg for Cr, 13.38 to 53.72 mg/kg for Cu, and 42.77 to 145.47 mg/kg for Zn. The average concentrations of these metals were found to be below the risk values specified in the "Soil environmental quality (GB15618-2018)", except for As and Cd in three sampling points in Xiaodian District. The heavy metal pollution in these areas can be attributed to various sources, such as industrial activities, the use of fertilizers and pesticides, and the irrigation process. According to the geo–accumulation index, the agricultural soil in the Taiyuan irrigation area was found to be uncontaminated by Zn, Cr, Cu, and As, and lightly contaminated by Cd, Hg, and Pb. The Nemerow Pollution Index indicated that the soil at all sampling points exhibited a slight level of pollution. Moreover, the ecological risk assessment indicated that all heavy metals posed a slight level of pollution. The findings of this study provide a scientific basis for the development of effective policies and measures for soil environmental protection and pollution control. [ABSTRACT FROM AUTHOR]

In this study, the trajectory mapping domain-filling technology, which can provide more reliable statistical estimates of long-lived gas concentrations in a broader geographical area based on limited station data, is used to map the CO2 concentration data of six ground observation stations to the entire Shanxi Province. The technology combines a dynamical model of the atmosphere with trace gas observations, combining forward and backward trajectories to greatly expand the information on long-lived CO2 gas concentrations over a trajectory path. The mapped results show good agreement with the observation results, which reveals the generalizability of the trajectory mapping domain-filling technology. The results show that the spatio-temporal distribution characteristics of CO2 concentration in the entire Shanxi region is significant: during the five years, the provincial average CO2 concentration exhibits an overall increasing trend. The CO2 concentration increases from the north to the south across the province. Influenced by the economic growth rate and COVID-19, there are differences in the annual variation characteristics of the CO2 concentration across the entire province, with the highest year-on-year growth in 2019 and a year-on-year decrease in 2020. The increasing rate of the CO2 concentration in the northern low-value areas is faster than that in the southern high-value areas. Overall, there is a decreasing trend in the CO2 concentration growth from the north to the south in the entire province. There are seasonal differences in the CO2 concentration distribution across the entire province. The CO2 concentration and amplitude are higher in autumn and winter than they are in spring and summer. This study can provide scientific support and methodological reference for the spatio-temporal distribution characteristics analysis of GHGs at the provincial–regional scale, as well as at the national and global scales. [ABSTRACT FROM AUTHOR]

Limited studies have demonstrated that inorganic arsenic exposure is positively associated with serum vitamin D levels, although the correlation between urinary arsenic species and serum vitamin D has not been investigated in areas of water-borne arsenicosis. A cross-sectional study of 762 participants was conducted in Wenshui Country, Shanxi Province, a water-borne arsenicosis area. The results showed a positive relationship between urinary arsenic species (inorganic arsenic (iAs), methylarsonic acid (MMAV), dimethylarsinic acid (DMAV) and serum 25(OH)D. Log-binomial regression analysis indicated a 0.4% increase in the risk of vitamin D excess for every 1-unit increment in the Box–Cox transformed urinary DMAV after adjustment for covariates. After stratifying populations by inorganic arsenic methylation metabolic capacity, serum 25(OH)D levels in the populations with iAs% above the median and primary methylation index (PMI) below the median increased by 0.064 ng/mL (95% CI: 0.032 to 0.096) for every one-unit increase in the Box–Cox transformed total arsenic (tAs) levels. Serum 25(OH)D levels increased by 0.592 ng/mL (95% CI: 0.041 to 1.143) for every one-unit rise in the Box–Cox transformed iAs levels in people with skin hyperkeratosis. Overall, our findings support a positive relationship between urinary arsenic species and serum 25(OH)D. It was recommended that those residing in regions with water-borne arsenicosis should take moderate vitamin D supplements to avoid vitamin D poisoning. [ABSTRACT FROM AUTHOR]

Trichome plays an important role in heat dissipation, cold resistance, water absorption, protection of leaves from mechanical damage, and direct exposure to ultraviolet rays. It also plays an important role in the photosynthesis, transpiration, and respiration of plants. However, the genetic basis of trichome traits is not fully understood in wheat. In this study, wheat DH population (Hanxuan 10 × Lumai 14) was used to map quantitative trait loci (QTL) for trichome traits in different parts of flag leaf at 10 days after anther with growing in Zhao County, Hebei Province, and Taigu County, Shanxi Province, respectively. The results showed that trichome density (TD) was leaf center > leaf tip > leaf base and near vein > middle > edge, respectively, in both environments. The trichome length (TL) was leaf tip > leaf center > leaf base and edge > middle > near vein. Significant phenotypic positive correlations were observed between the trichome-related traits of different parts. A total of 83 QTLs for trichome-related traits were mapped onto 18 chromosomes, and each one accounted for 2.41 to 27.99% of the phenotypic variations. Two QTL hotspots were detected in two marker intervals: AX-95232910~AX-95658735 on 3A and AX-94850949~AX-109507404 on 7D. Six possible candidate genes (TraesCS3A02G406000, TraesCS3A02G414900, TraesCS3A02G440900, TraesCS7D02G145200, TraesCS7D02G149200, and TraesCS7D02G152400) for trichome-related traits of wheat leaves were screened out according to their predicted expression levels in wheat leaves. The expression of these genes may be induced by a variety of abiotic stresses. The results provide the basis for further validation and functional characterization of the candidate genes. [ABSTRACT FROM AUTHOR]