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The combination of digital finance and financial inclusion can better meet the needs of those who have little access to financial services. This paper investigated the differences in the determinants and mechanisms of digital financial inclusion development between urban and rural areas. The sample consists of 1607 counties in China from 2014 to 2019, and uses the fixed-effect model and panel threshold technique. The empirical results indicate that: (1) The industrial economy and governmental intervention are the common determinants of urban and rural digital financial inclusion development, in which the degree is different. At the same time, secondary education is only a determinant in rural areas. (2) Industrial upgrading and indirect finance play a mediating role in the determinants of digital financial inclusion, but indirect finance is only significant for urban areas. (3) There is a threshold effect in the financial development-digital financial inclusion relationship. Under different financial development levels, the determinants of urban and rural digital financial inclusion show the discrepancy. With the development of digital financial inclusion under the trend of promoting innovative digital finance in China, these findings are expected to enhance access to financial services in urban and rural areas for more inclusive and sustainable futures. [ABSTRACT FROM AUTHOR]

Agricultural advancements have significantly impacted people's lives and their surroundings in recent years. The insufficient knowledge of the whole agricultural production system and conventional ways of irrigation have limited agricultural yields in the past. The remote sensing innovations recently implemented in agriculture have dramatically revolutionized production efficiency by offering unparalleled opportunities for convenient, versatile, and quick collection of land images to collect critical details on the crop's conditions. These innovations have enabled automated data collection, simulation, and interpretation based on crop analytics facilitated by deep learning techniques. This paper aims to reveal the transformative patterns of old Chinese agrarian development and fruit production by focusing on the major crop production (from 1980 to 2050) taking into account various forms of data from fruit production (e.g., apples, bananas, citrus fruits, pears, and grapes). In this study, we used production data for different fruits grown in China to predict the future production of these fruits. The study employs deep neural networks to project future fruit production based on the statistics issued by China's National Bureau of Statistics on the total fruit growth output for this period. The proposed method exhibits encouraging results with an accuracy of 95.56% calculating by accuracy formula based on fruit production variation. Authors further provide recommendations on the AGR-DL (agricultural deep learning) method being helpful for developing countries. The results suggest that the agricultural development in China is acceptable but demands more improvement and government needs to prioritize expanding the fruit production by establishing new strategies for cultivators to boost their performance. [ABSTRACT FROM AUTHOR]

Numerous methods have been used in the spatial prediction of soil salinity. However, the most suitable method is still unknown in arid irrigation regions. In this paper, 78 locations were sampled in salt-affected land caused by irrigation in an arid area in northern China. The geostatistical characteristics of the soil pH, Sodium Adsorption Ratio (SAR), Total Salt Content (TSC), and Soil Organic Matter (SOM) of the surface (0–20 cm) and subsurface (20–40 cm) layers were analyzed. The abilities of the Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and CoKriging (CK) interpolation methods were compared, and the Root Mean Square Error (RMSE) was used to justify the results of the methods. The results showed that the spatial distributions of the soil properties obtained using the different interpolation methods were similar. However, the surface layer exhibits more spatial heterogeneity than the subsurface layer. Based on the RSME, the nugget/sill value and range significantly affected which method was the most suitable. Lower nugget/sill values and lower ranges can be fitted using the IDW method, but higher nugget/sill values and higher ranges can be fitted using the OK method. These results provide a valuable reference for the prediction of soil salinity. [ABSTRACT FROM AUTHOR]

The aim of this study was to verify the applicability of the critical nitrogen concentration dilution curve (Nc) of wheat grown under different irrigation conditions in the field, and discuss the feasibility of using the N nutrition index (NNI) to optimize N fertilizer application. The high-yield, medium-protein wheat varieties Zhoumai 27 and Zhoumai 22 were used in field experiments in two different locations (Zhengzhou and Shangshui) in Huang-Huai, China. Plants were grown under rainfed and irrigation conditions, with five N application rates. Nc models of the leaves, stems, and whole plant were constructed, followed by establishment of an NNI model and accumulative N deficit model (Nand). As previous research reported, our results also showed that the critical N concentration and biomass formed a power function relationship (N = aDW−b). When the biomass was the same, the critical N concentration was higher under irrigation than rainfed treatment. Meanwhile, the fitting accuracy (R2) of the Nc model was also higher under irrigation than rainfed treatment in both sites, and was higher in the stems and whole plant. The NNI calculated using the Nc model increased with increasing N application, reflecting N deficiency. Moreover, there was a significant negative linear correlation between NNI and Nand, and both indices could be uniformly modeled between locations and water treatments. The accuracy of the Nand model was highest in the whole plant, followed by the leaves and stems. The models constructed in this paper provide a theoretical basis for accurate management of N fertilizer application in wheat production. [ABSTRACT FROM AUTHOR]

Thus far, knowledge network research has been quantitative research, emphasizing that in limited industries, knowledge creation increasingly strengthens through geographical proximity or institutional connections. Although it has been suggested that knowledge networks should be researched using dynamic rather than static methods, the dynamic process of knowledge networks according to spatiotemporal changes has not been sufficiently researched. This paper uses the Chinese wine industry case to conduct related research. The results show that, first of all, wine-related knowledge creation activities were carried out in the big cities that formed the early market in the mid-2000s, and the geographical conditions in which the spatial scope was expanded were in the places that gradually developed over time. Second, although the spatial scope of knowledge creation activities is expanding with the active participation of private enterprise networks, private enterprises and the overall knowledge creation process are relatively isolated. Finally, in terms of the process of knowledge creation related to wine, in the development of regional linkages organizations relate to the knowledge providers who provide the required information, and have little to do with the geographically close knowledge providers. [ABSTRACT FROM AUTHOR]

The growth rate of eucalyptus in the dry season was significantly lower than that in the wet season. However, the limiting factors of eucalyptus growth in the dry season are not clear. In this paper, through the continuous monitoring of the diameter growth and environmental factors of 5.5-year-old Eucalyptus urophylla S. T. Blake × E. grandis W. Hill ex Maiden in the dry season, the diameter growth characteristics of eucalyptus during the dry season were studied and the limiting factors of eucalyptus growth in the dry season were determined. The water and fertilizer management activities in the dry season were evaluated to verify the growth and water use characteristics of Eucalyptus urophylla × E. grandis in the dry season under the conditions of mitigation limiting factors and provide the basis for further increasing the growth rate of eucalyptus. The results show that the diameter fluctuation of Eucalyptus urophylla × E. grandis is cyclical and the diameter cumulative growth during the dry season monitoring is consistent with the Gompertz model. Atmospheric temperature and soil water content are the main factors limiting the growth of Eucalyptus urophylla × E. grandis in the dry season. Irrigation and fertilization in the dry season can significantly increase the growth of diameter at breast height (DBH) and biomass growth and significantly improve the water use efficiency in the dry season. [ABSTRACT FROM AUTHOR]