Search Results (78)

Water scarcity, poor soil, and low water and fertilizer utilization are major challenges on agricultural production in the tableland region of China’s Loess Plateau. Optimizing tillage patterns and improving soil nutrient status can improve crop yield and water and fertilizer utilization efficiency. A field trial was initiated in 2005 to assess the impacts of various tillage and fertilization practices on dryland agricultural production. A split-plot design was used, with tillage practices (traditional tillage and no tillage) as the main plot treatment and fertilization management (no fertilization (CK), mineral nitrogen (N), mineral phosphorus (P), composted cow manure (M), a combination of mineral nitrogen and phosphorus (NP), and a combination of mineral nitrogen, phosphorus, and composted cow manure (NMP)) as the split-plot treatment. An experiment was conducted from 2022 to 2024. The NMP treatment resulted in lower bulk density, a lower three-soil-phase index, and higher mean weight diameter, geometric mean diameter, soil water storage, total nitrogen, and soil organic matter than the CK. In the no-tillage treatment, the crop roots were less effective at extracting water from the deep subsoil, leading to greater residual moisture at depth (especially in the 120–200 cm soil layer) and lower yield and water use efficiency than in traditional tillage. The grain yield and water use efficiency were 9.2% and 8.4% lower, respectively, under no tillage than under traditional tillage. The NMP under traditional tillage exhibited lower surface soil bulk density and a higher three-soil-phase index, mean weight diameter, geometric mean diameter, soil organic matter, total nitrogen, and water use efficiency than the unfertilized control, resulting in higher grain yields. The NMP under traditional tillage is recommended to increase grain yield and water use efficiency in wheat–maize rotation systems in the tableland region of China’s Loess Plateau. Future studies should analyze the deep root architecture and the effect of weed competition on soil water depletion. Full article

Objectives: This study aimed to reveal the prevalence, geographic variations, and determinants of pain among the Chinese older adult population and provide empirical strategies for pain management in older adults in China. Methods: A total of 21,346 Chinese residents aged ≥ 60 years from 31 provinces in mainland China participated in our survey. Standardized questionnaires were used to collect data on socioeconomic characteristics, lifestyle factors, and self-reported pain experiences. Multivariate logistic regression models were used to estimate the associations between individual socioeconomic status, chronic diseases, and pain. Results: The national prevalence of pain was 56.5% (95% CI: 55.9–57.1%), representing approximately 140 million Chinese older adults. The prevalence increased with aging and peaked at 80 years and older (61.00%, 95% CI: 59.30–62.70%). Women (62.36%, 95% CI: 61.47–63.25%), rural residents (61.27%, 95% CI: 60.34–62.20%), and those with no formal education (65.08%, 63.90–66.26%) had a higher prevalence than men (50.27%, 95% CI: 49.32–51.22%), urban residents (52.19%, 95% CI: 51.28–53.10%), and those with higher education levels, respectively. Provincial prevalence ranged from 38.98% in Shanghai to 72.75% in Gansu Province. The presence of chronic diseases significantly increased the odds of pain, with multimorbidity (three or more chronic diseases) showing the strongest association (OR = 11.380, 95% CI: 10.257–12.627). Conclusions and Implications: Pain was highly prevalent among older adults in China and varied geographically. Socioeconomic status, chronic diseases, and multimorbidity were strongly associated with pain prevalence. Our findings support prioritizing the reduction in gender and geographic disparities in China’s pain management strategies. An integrated approach addressing both pain and chronic diseases should be urgently established in China’s healthcare system for older adults. Full article

Traditional vernacular architecture is an important component of historical and cultural heritage, and the accurate identification of its construction period is of great significance for architectural heritage conservation, historical research, and urban–rural planning. However, traditional methods for period identification are labor-intensive, potentially damaging to buildings, and lack sufficient accuracy. To address these issues, this study proposes a deep learning-based method for classifying the construction periods of traditional vernacular architecture. A dataset of traditional vernacular architecture images from the Longzhong region of Gansu Province was constructed, covering four periods: before 1911, 1912–1949, 1950–1980, and from 1981 to the present, with a total of 1181 images. Through comparative analysis of three mainstream models—ResNet50, EfficientNet-b4, and Vision Transformer—we found that EfficientNet demonstrated optimal performance in the classification task, achieving Accuracy, Precision, Recall, and F1-scores of 85.1%, 81.6%, 81.0%, and 81.1%, respectively. These metrics surpassed ResNet50 by 1.4%, 1.3%, 0.5%, and 1.2%, and outperformed Vision Transformer by 8.1%, 9.1%, 9.5%, and 9.1%, respectively. To further improve feature extraction and classification accuracy, we propose the “local–global feature joint learning network architecture” (DualBranchEfficientNet). This dual-branch design, comprising a global feature branch and a local feature branch, effectively integrates global structure with local details and significantly enhances classification performance. The proposed architecture achieved Accuracy, Precision, Recall, and F1-scores of 89.6%, 87.7%, 86.0%, and 86.7%, respectively, with DualBranchEfficientNet exhibiting a 2.0% higher Accuracy than DualBranchResNet. To address sample imbalance, a hybrid triplet loss function (Focal Loss + Triplet Loss) was introduced, and its effectiveness in identifying minority class samples was validated through ablation experiments. Experimental results show that the DualBranchEfficientNet model with the hybrid triplet loss outperforms traditional models across all evaluation metrics, particularly in the data-scarce 1950–1980 period, where Recall increased by 7.3% and F1-score by 4.1%. Finally, interpretability analysis via Grad-CAM heat maps demonstrates that the DualBranchEfficientNet model incorporating hybrid triplet loss accurately pinpoints the key discriminative regions of traditional dwellings across different eras, and its focus closely aligns with those identified by conventional methods. This study provides an efficient, accurate, and scalable deep learning solution for the period identification of traditional vernacular architecture. Full article

The modernization of rural governance capacity (MRGC) is an important factor in enhancing the effectiveness of governance and promoting sustainable rural development. By interpreting the connotation of the MRGC, this study analyzes the dual structure of the rural organization system and its internal correlation based on the principle of system theory. The evaluation framework of the MRGC is constructed from the two dimensions of subject governance capacity (SGC) and inter-subject interaction force (IIF). Furthermore, an empirical study utilizing survey data from 15 towns, 248 villages, and 2579 villagers in Kang County, Gansu Province, China is conducted. The results show that Kang County’s overall MRGC, along with sub-dimensional SGC and IIF, remains at a moderate level. SGC manifests as balanced high performance and differentiated low performance. IIF variation is primarily driven by capability volatility. Regional analysis indicates that resource-rich areas exhibit higher SGC but carry greater systemic imbalance risks. Combined weights effectively rectify single-method biases in measurement design. Full article

Enhancing farmers’ digital literacy is both an inevitable requirement for adapting to the digital age and an important measure for promoting the sustainable development of livestock and poultry manure resource utilization. This study surveyed and obtained data from 1047 farm households in Ningxia and Gansu, two provinces in China that have long implemented livestock manure resource utilization policies, from December 2023 to January 2024, and employed the binary probit model to analyze how digital literacy influences farmers’ willingness to adopt two livestock manure resource utilization modes, as well as to analyze the moderating role of three policy regulations. This paper also explores the heterogeneous results in different village forms and income groups. The results are as follows: (1) Digital literacy significantly and positively impacts farmers’ willingness to adopt both the “household collection” mode and the “livestock community” mode. For every one-unit increase in a farmer’s digital literacy, the probability of farmers’ willingness to adopt the “household collection” mode rises by 22 percentage points, and the probability of farmers’ willingness to adopt the “livestock community” mode rises by 19.8 percentage points. After endogeneity tests and robustness checks, the conclusion still holds. (2) Mechanism analysis results indicate that guiding policy and incentive policy have a positive moderation effect on the link between digital literacy and the willingness to adopt the “household collection” mode. Meanwhile, incentive policy also positively moderates the relationship between digital literacy and the willingness to adopt the “livestock community” mode. (3) Heterogeneity analysis results show that the positive effect of digital literacy on farmers’ willingness to adopt two livestock manure resource utilization modes is stronger in “tight-knit society” rural areas and in low-income households. (4) In further discussion, we find that digital literacy removes the information barriers for farmers, facilitating the conversion of willingness into behavior. The value of this study is as follows: this paper provides new insights for the promotion of livestock and poultry manure resource utilization policies in countries and regions similar to the development process of northwest China. Therefore, enhancing farmers’ digital literacy in a targeted way, strengthening the promotion of grassroots policies on livestock manure resource utilization, formulating diversified ecological compensation schemes, and establishing limited supervision and penalty rules can boost farmers’ willingness to adopt manure resource utilization models. Full article

Agricultural modernization is the key path and core strategy for the transformation from traditional agriculture to modern agriculture, and it constitutes the cornerstone of China’s modernization system. Gansu Province is a typical ecologically fragile area, and a multi-ethnic province in the northwest of China. In recent years, through the application of efficient water-saving technologies, the industrialization of characteristic agriculture and institutional innovation, it has initially achieved the coordinated increase in production and ecological benefits. However, the lagging infrastructure and low efficiency of factor allocation still restrict its systematic transformation process. Based on the panel data of 14 prefectures and cities in Gansu Province from 2013 to 2022, this paper constructs an evaluation index system for agricultural modernization, and reveals the spatio-temporal evolution characteristics of agricultural modernization in Gansu Province. Further, this paper combines the Theil index and the obstacle degree model to analyze the regional differences and development bottlenecks of agricultural modernization in Gansu Province. The research finds that the overall level of agricultural modernization in Gansu Province has improved but is still in a stage of continuous development. Spatially, the western and central regions have a higher level of development, while the southern region is relatively lower. The time series analysis results show that the overall regional differences in agricultural modernization in Gansu Province have narrowed. From 2013 to 2018, the differences within the regions were dominant; after 2018, they were jointly affected by both within-region and between-region differences. The results of the obstacle factor analysis show that the modernization of agricultural industrial operation is the main obstacle factor, followed by the green modernization of agriculture. Based on these findings, this paper proposes suggestions such as strengthening regional coordination, enhancing production and operation capabilities, and promoting ecological construction. It is expected that, through the continuous development of the level of agricultural modernization, the coordinated development of agricultural modernization in Gansu Province can be promoted, and further, the well-being of the people can be enhanced, and the rural revitalization strategy can be advanced in depth. Full article

The energy consumption structure in underdeveloped rural areas of China has long been dominated by fossil fuels. Such a structure not only makes it difficult to improve the rural living environment but also hinders the stable development of the rural economy. For these regions, improving the living environment is one of the key tasks of China’s rural revitalization strategy. As a clean energy with huge potential, renewable energy can provide a convenient and low-cost solution for the transformation of the energy structure and the improvement of the living environment in these areas. This study takes Gansu Province, a typical underdeveloped region in China, as the research area and uses a multi-objective evaluation analysis model to evaluate the potential for renewable energy substitution at the county scale in rural areas of Gansu Province. Then, through the obstacle factor analysis model, the obstacle factors of the potential for renewable energy substitution are revealed, providing a basis for the scientific formulation of energy policies and the stable development of the rural economy in underdeveloped areas. This study found that the potential for renewable energy substitution in counties of Gansu Province is generally low and shows significant temporal and spatial differences. At the criterion level, the endowment of renewable energy resources constitutes the greatest obstacle, with an average obstacle degree of 8.91%, and shows an upward trend. At the factor level, the obstacle degree of the effective irrigated area is the highest, with an average obstacle degree of 9.29%, and the interannual variation is relatively stable. In addition, the average obstacle degrees of total agricultural machinery power and the number of rural populations are also relatively high. Finally, this paper puts forward policy suggestions, such as rationally planning the development model of renewable energy, coordinating regions to give full play to economic value, and innovatively developing to enhance development capacity, in order to provide reference for relevant decision-making. Full article

In artificial grassland systems, the extensive use of inorganic nitrogen (N) fertilizers has greatly enhanced grassland yields but also caused significant environmental issues. The combined use of biochar and N fertilizer is recognized as an effective and sustainable approach to reducing environmental risks while boosting crop production. However, the specific impacts of biochar and N on alfalfa yield, soil properties, and root morphology remain unclear. This study examined the effects of three biochar application rates (0, 10, 20 t hm⁻²) and four N application levels (0, 47, 94, 188 kg N hm⁻² yr⁻¹) on alfalfa growth and soil characteristics. Results revealed that biochar notably promoted root development and increased osmoregulatory substance content. It enhanced root biomass by improving root nodule count, root neck bud formation, and root neck diameter, while N application reduced root nodule numbers. Biochar and N application reduced soil bulk density by 0.8–10.5%, with biochar further increasing available phosphorus and potassium levels. Additionally, their combined use significantly elevated soil nitrate and ammonium concentrations. Overall, the synergy of biochar and nitrogen application enhances alfalfa yield by fostering better root growth and improving soil fertility. Full article

Background: The wine industry in arid area serves as a crucial livelihood source at the frontiers of anti-desertification and anti-poverty. By making use of a carbon footprint (CF) management system, formerly untapped climate values can be explored, embedded, and cherished to connect rural communities with the global goals of sustainable development. However, the current standards of CF management mainly represent the traditional wine grape growing areas of Europe, Oceania, and North America. Limited study of the arid areas in lower-income regions exists, which offers a kind of potential development knowledge regarding creating climate-related livelihoods. Methods: This paper attempts to construct a cradle-to-gate CF Life Cycle Assessment (LCA) framework based on the prominent emission factors in three GHG emission phases (raw material input, planting management, and transportation) of a wine grape variety, Cabernet Sauvignon (chi xia zhu), planted at the Eastern Foothills of the Helan Mountains in the Ningxia Hui Autonomous Region of China. Results: It is found that viticulture processes (instead of wine-making, bottling, or distribution) account for a larger proportion of GHG emissions in Ningxia. Due to the large amount of irrigation electricity usage, the less precipitation wine producers have, the larger CF they produce. By using organic fertilizer, the CF of Ningxia Cabernet Sauvignon, being 0.3403 kgCO₂e/kg, is not only lower than that of the drier areas in Gansu Province (1.59–5.7 kgCO₂e/kg) of Western China, but it is even lower than that of the Israel Negev Region (0.342 kgCO₂e/kg) that experiences more rainfall. Conclusions: The measurement of CF also plays a role in understanding low-carbon experience sharing. As the largest wine grape production area in China, CF analysis of the Ningxia region and its commercial value realization might practically fill in the knowledge gap for desert areas in developing countries. It is inspiring to know that by applying green agricultural technologies, the viticulture CF can be effectively reduced. For the potential exchanges in global carbon markets or trading regulations under the Carbon Border Adjustment Mechanism (CBAM), positive variations in CF and soil organic carbon (SOC) storage volume need to be considered within financial institutional design to lead to more participation toward SDGs. Full article

The building sector contributes approximately half of all carbon emissions. The heating stage accounts for the largest proportion of building carbon emissions. The focus on carbon-reduction strategies in rural areas could not be copied from urban buildings due to different heating modes limited by economic factors. The Gannan region in Gansu province was selected to carry out an on-site survey on heating conditions, including the heating modes, the energy used for heating, heating fees, residents’ satisfaction with heating, and the thermal environment of the typical building. The results showed that local rural residents burnt scattered coal for heating using primitive heating stoves with low efficiency, causing low air temperatures and high heating fees. The carbon emissions generated by heating reached 5743.28 kgCO₂e·m⁻². Several strategies for reducing carbon emissions were proposed, considering the economic benefits limited by rural economic development. A parameter of reduced carbon emissions per investment input was proposed to evaluate the carbon-reduction strategies. The results showed that biomass was the most economical way to reduce carbon emissions. Reduced carbon emissions per investment input reached 44.19 kgCO₂e·CNY⁻¹ with energy efficiency of 50%, followed by thermal insulation design of 32.31 kgCO₂e·CNY⁻¹, natural gas furnaces of 26.08 kgCO₂e·CNY⁻¹, and air-source heat pumps of 20.27 kgCO₂e·CNY⁻¹. In addition, carbon emissions generated by biomass were 12.4% and 24% of those caused by coal and natural gas supplying the same energy. Moreover, building insulation should be increased according to economic benefits. The optimum energy efficiency was 55% in Gannan. The results provided a reference for building low-carbon heating in rural areas, which could help achieve the low-carbon goal with low investments. Full article

Two United Nations Sustainable Development Goals highlight that energy supply, conversion, transmission, and consumption are primary contributors to climate change, accounting for 60% of global greenhouse gas emissions. Exploring the influencing factors on the intention and behavior of clean energy use in rural areas is a crucial step in achieving the “Dual Carbon” target and global sustainable development goals. The article constructed a theoretical analysis framework of “environmental knowledge—perceived value—use intention—use behavior”. Taking Gansu Province, a typical case area in northwest China, as a case study, data from 766 survey questionnaires were used to analyze the characteristics and impact mechanism of clean energy use behavior among residents. This article finds that rural household energy use is moving towards low-carbon goals, but traditional energy remains an important component, especially in winter heating scenarios. Only the use intention has a direct promoting effect on use behavior, with a regression coefficient of 0.108. Perceived value and use intention play a chain-mediating role between environmental knowledge and use behavior. Residents with higher income levels, higher education levels, and poorer health conditions are more likely to develop clean energy use intention and behavior. At the same time, government intervention measures also have a promoting effect. Finally, countermeasures and suggestions for improving the public’s level of clean energy utilization in underdeveloped areas were proposed. Full article

On 18 December 2023, a 6.2-magnitude earthquake struck Jishishan, affecting multiple counties and cities in Gansu and Qinghai Provinces. The seismic intensity of the meizoseismal area was VIII, resulting in extensive structural damage and building collapses. A damage assessment was conducted of the epicenter and surrounding high-intensity zones. To understand the typical structures and characteristics of the buildings that were damaged in these high-intensity zones, this study summarizes the characteristics of the damage to typical rural houses, compares the damage of the rural houses across different sites, and analyzes the causes behind these variations. The findings of the study indicate the following: (1) Timber and some brick–timber structures, due to their age, insufficient material strength, and lack of adequate connections between parts of the building, primarily experienced severe damage or total collapse, characterized by through-wall cracks, partial collapses, or complete collapses. (2) Brick–concrete structures predominantly suffered moderate to severe damage due to factors such as improper layout, uneven façades, and inadequate or incomplete seismic measures. The observed damage included significant wall cracks and extensive damage to two-story buildings. (3) Frame structures, mainly used for public facilities like schools, hospitals, and health centers, exhibited strong integrity and excellent seismic performance, resulting in minimal to no damage, with damage largely confined to non-load-bearing components. (4) The amplification effects of seismic waves in thick loess basin areas, slope sites, and the hanging wall effect of faults exacerbated structural damage to rural houses located in certain villages within the high-intensity areas. The results of this study can serve as a reference for post-disaster reconstruction and seismic retrofitting of buildings and contribute positively to enhancing the disaster resilience of rural housing. Full article

Implementing rural revitalization strategies requires understanding ecological revitalization, and improving farmers’ ecological awareness is crucial for promoting ecological revitalization. China’s rural ecological civilization construction is based on a theoretical foundation of Marxist ecological thought. This study examined the cultivation of ecological awareness among farmers in ecological revitalization using the literature, graphs, data statistics, and case analysis methods. A survey conducted in Gansu Province, in China, showed that more than 90% of people are satisfied with current ecosystem revitalization projects. The use of chemical fertilizer is decreasing every year, and the area of water-saving irrigation and soil erosion control has increased since implementing the Three-Year Action Plan for Rural Living Environment Improvement in 2018. The findings indicate the need for farmers to be more aware of general ecological concepts and economic development, and to participate more in ecological governance. Consequently, this study proposes policy measures such as strengthening ecological civilization ideological education, increasing investment in funds and technology, improving the relevant legal mechanisms to provide educational support for cultivating farmers’ ecological awareness, creating a cultural atmosphere, and building a solid institutional guarantee. The study has valuable implications for policymakers, industrialists, and academicians informing the development of strategies and interventions to promote farmers’ ecological awareness for rural ecological revitalization and sustainable development. Full article

Enhancing the livelihood resilience of livestock farmers in the old revolutionary base areas helps them to cope with the increasingly complex external risk shocks of recent years and promotes the sustainable development of regional agriculture. This study is based on survey data from 1047 livestock farmers in the Ningxia and Gansu provinces of the northwest old revolutionary base area. It incorporates the characteristics of livestock farmers and the elements of psychological capital into the sustainable livelihood analysis framework to construct a livelihood resilience index system. After measuring livelihood resilience, this paper uses a general linear regression model and a probit model to explore the impact and mechanism of digital literacy on the livelihood resilience of livestock farmers. The results show the following: (1) digital literacy has a significant positive effect on the livelihood resilience of livestock farmers, and the impact of different dimensions of digital literacy on different dimensions of livelihood resilience also varies. Additionally, this effect also shows the heterogeneity in different village clustering forms and different income groups. In areas inhabited by ethnic minorities and among moderate-income groups, the role of digital literacy on the livelihood resilience of livestock farmers is more significant. (2) The improvement of digital literacy has a significant positive impact on livelihood resilience through three different pathways: the “differential mode of association”, learning channels, and types of income. (3) Digital literacy has led to the psychological aspects of rural hollowing-out problems among livestock farmers, which is particularly evident in families with only one type of caregiving burden (either only left-behind elderly people or only left-behind children). This problem is more evident. Therefore, this paper poses that the advancement of agricultural and rural economic development in China should not only focus on the cultivation of farmers’ digital literacy but also accelerate the construction of digital infrastructure to ensure the long-term effective mechanism of improving digital literacy. At the same time, in the process of promoting digital rural areas, attention should be paid to the psychological isolation issues that the network era brings to farmers. Full article

Different fertilization measures affect the soil’s physical and chemical properties and bacterial community structure, which in turn affects the growth environment and yield of maize seed production. Therefore, rational fertilization measures are important in maintaining and improving soil fertility and promoting maize crop growth. Research on fertilization practices in maize fields for seed production can help to increase agricultural productivity while protecting and enhancing soil health and achieving sustainable agricultural development. To clarify the effects of different fertilization measures on soil bacterial communities in seed corn fields, 16S rRNA high-throughput sequencing technology and PICRUSt method were used to explore the soil under different fertilization measures (CK as control, effects of single application of liquid organic fertilizer (M), single application of bacterial agents (BF), and combined application of liquid organic fertilizer and bacterial agents (M + BF)) on soil bacterial community structure characteristics and ecological functions. Proteobacteria (20.14–25.30%), Actinobacteriota (18.21–20.47%), Actinobacteriota (13.55–22.00%), and Chloroflexi (14.24–17.59%) were the dominant phyla. Bacillus, RB41, Arthrobacter, and Sphingomonas were the dominant genera. M + BF treatment significantly increased the relative abundance of Planctomycetota. The relative abundance of Bacillus and PaeniBacillus in M treatment decreased considerably, while the relative abundance of Turicibacter increased significantly. The relative abundance of Sphingomonas was reduced considerably in M and M + BF treatments. The relative abundance of Subgroup 10 decreased significantly after BF and M + BF treatments. BF treatment significantly increased the relative abundance of Skermanella. Redundancy analysis showed that alkali-hydrolyzed nitrogen (p = 0.044) was the main environmental factor affecting soil bacterial communities under different fertilizer treatments. PICRUSt function prediction results showed that metabolism was the main functional component of bacteria, accounting for 78.45–78.94%. The abundance of functional genes for terpenoid and polyketone metabolism, the endocrine system, the excretory system, and the immune system of the soil bacterial community was significantly increased under M treatment, while the abundance of functional genes for the digestive system was decreased considerably. Different fertilizer cultivation measures changed soil bacterial community composition and ecological function in maize fields. These results can provide a theoretical reference for the study of bacterial community succession characteristics in maize fields and the determination of appropriate fertilizer cultivation measures. Full article