In this study, the DEA–Malmquist index method was used to measure the total factor productivity of citrus in seven major mandarin-producing provinces and seven major tangerine-producing provinces in China from 2006 to 2020. Moran’s I index was used to test the spatial correlation of total factor productivity of mandarin and tangerine, and its σ convergence and β convergence characteristics were explored using coefficient of variation and spatial panel models. The results show that from the perspective of time series evolution, the growth rate of total factor productivity of mandarin and tangerine in China slowed down year by year after reaching the maximum value in 2008. Technological progress was the main factor affecting the total factor productivity of citrus. The total factor productivity growth of tangerine was more stable than that of mandarin, and the pure technical efficiency index and scale efficiency change index of mandarin and tangerine were not stable. From the perspective of regional differences, the total factor productivity of China’s main citrus-producing provinces all indicated positive growth, showing an increasing trend from east to west. The drivers of growth were mainly technological progress and scale efficiency. The regional differences in total factor productivity growth for mandarin were more obvious than for tangerine. The total factor productivity of mandarin and tangerine showed obvious spatial correlation characteristics; the positive spatial spillover effect was significant; and there were σ convergence, absolute β convergence, and conditional β convergence. Regional disparities in citrus industry development can be more objectively reflected by convergence analysis that takes spatial factors, economic and social factors, and other factors into account.

In this study, the transcendental logarithmic cost function model was used to measure the rate of technological progress in seven major mandarin-producing regions and seven major tangerine-producing regions in China from 2006 to 2021. The modified gravity model was used to establish spatial correlation networks. The social network analysis method was used to analyze the characteristics of the overall network structure and the individual network structure of the spatial correlation networks of citrus-production technology progress, and the quadratic assignment procedure was used to analyze the factors influencing the spatial network. The results show the production of Chinese mandarins and tangerines is in the stage of technological progress in general, but the rate of progress is slowing down gradually, and the rate of mandarin-production technology progress is higher than that of tangerine-production technology progress. In terms of the overall network structure characteristics, the spatial networks of technological progress related to Chinese mandarin and tangerine production are becoming increasingly dense and complex, with obvious spatial spillover effects, but the network structure is relatively loose, and the polarization of the tangerine network is more serious. In terms of individual network structure characteristics, the relatively economically developed eastern regions have a higher status in terms of the spatial correlation network and a stronger role in controlling and dominating the resource elements needed for citrus-production technology progress. Education, informatization, economic development, innovation support, and financial support are important factors influencing the formation of the spatial association network of citrus-production technology progress in China.

This article constructs an evaluation index system for the development of nutrition-sensitive agriculture in China and measures the development level of nutrition-sensitive agriculture using the entropy method, based on the panel data of 31 provinces from 2000 to 2022. The Dagum Gini coefficient is employed to analyze the magnitude and sources of regional differences in the development level between the whole country and the four major regions. The Kernel density estimation method is applied to describe the dynamic evolutionary characteristics of the development level in different regions. Furthermore, this study delves into the σ convergence and β convergence characteristics of the development level. The results show the following: (a) The level of nutrition-sensitive agricultural development at the national level and in the four major regions has been rising year by year, with a clear spatial pattern of “high in the east and low in the west”. (b) There are significant regional differences at the national level and in the four major regions, which tend to widen. (c) The dynamic evolution characteristics of the development level of nutrition-sensitive agriculture in various regions differ greatly, with polarization in the national, eastern, western and northeastern regions. (d) There is no σ convergence in the development level of nutrition-sensitive agriculture in the country or in the four major regions, but there is absolute β convergence and conditional β convergence in all of them, with the northeastern and central regions having faster convergence speeds; the “catching-up effect” is obvious. The report concludes by outlining the policy ramifications for implementing a methodical and comprehensive strategy approach to support regionally coordinated development plans for leapfrogging and upgrading.

The integration of the agricultural product market is of great significance to reducing price fluctuations and improving social welfare. In this study, we employ the relative price method to measure the integration of the agricultural product market in 31 Chinese provinces from 2003 to 2022. We use the Dagum–Gini coefficient and its decomposition and the σ convergence and β convergence models to analyze regional variations, time trends, and convergence. It is found that the degree of integration of the Chinese agricultural product market did not increase continuously but fluctuated with increasing intensity. The spatial differentiation degree of agricultural market integration fluctuated. The integration degree of the agricultural product market has σ convergence, absolute β convergence, and conditional β convergence. The marginal contribution of this study is the systematic analysis of the dynamic evolution and convergence of the integration of the Chinese agricultural product market. In order to improve the integration degree of the agricultural product market, in this paper, we put forward policy suggestions from three aspects: strengthening policy support, optimizing resource allocation, and building agricultural product market information centers.