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Agriculture is increasingly facing major challenges such as climate change, scarcity of natural resources, and changing societal demands. To tackle these challenges, there is a pressing need to evolve towards more sustainable agricultural practices. As a result, sustainability stands among the most relevant topics in agricultural research worldwide, and countries along the Belt and Road (B&R) route are no exception. This paper selected 25 indicators from the five subsystems of population, society, economy, environment, and resources in order to build an evaluation index system of agricultural sustainable development capability, and then it used an improved entropy weight method, technique for ordering preference by similarity to an ideal solution (TOPSIS), and coordination degree method to measure the comprehensive capability and coordination of agricultural sustainable development of all countries along the B&R route from 2006 to 2015. First, according to the time dimension, the comprehensive score of sustainable development capability of agriculture along the B&R route: This had an average annual score of 0.3195 which initially decreased, then increased in a fluctuating manner, before finally falling again. Second, according to the spatial dimension, the average comprehensive score of agricultural sustainable development capability showed an evolutionary trend of high-low-high-low-high' from west to east, which showed an obvious basic spatial pattern of the W' type. Third, from the perspective of the subsystems of agriculture, although the coordination degree among subsystems in the main grain-producing areas increased continually from 2006 to 2015, the overall level of development needed to be further improved. In order to further clarify the main factors affecting the capability of agricultural sustainable development, this paper selected six explanatory variables: The level of economic development, financial expenditure for agriculture, agricultural foreign direct investment, agricultural labor force, the intensity of agricultural R&D investment, and the level of agricultural informatization. Then, geographically and temporally weighted regression was applied to evaluate the direction and degree of influences of selected factors on sustainability development capability of agriculture. The results showed that the regression coefficients of each variable in 53 countries were positive or negative, which indicated that the influencing factors of agricultural sustainable development capacity had the characteristics of geospatial nonstationarity.