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As they represent an important form of agricultural operation, the sustainable development of family farms is not only an objective necessity for promoting comprehensive rural revitalization in China, but also an imperative strategy for accelerating the construction of agricultural power in China. Based on the survey data of 357 family grain farms in China, this paper uses a structural equation model to empirically analyze the relationship between market-oriented perceptions, organizational resilience, and the sustainable development of family grain farms. The results show that market-oriented perceptions have a significant positive impact on the sustainable development of family grain farms; additionally, organizational resilience plays a mediating role in the impact of market-orientation perceptions on the sustainable development of family grain farms. Based on this, the paper proposes a two-fold approach to the sustainable development of family farms: improving the level of market-orientation perceptions of family farmers and enhancing the organizational resilience of family grain farms. [ABSTRACT FROM AUTHOR]

Adaptive farming behavior is a key strategy for farmers to cope with climate change. This paper aims to explore the potential impacts of climate change information sources on farmers’ adaptive farming behavior. This paper clarifies the internal mechanism of three typical information sources, namely government departments, scientific research institutions and neighborhood communication, affecting farmers' adaptive farming behavior. Based on the sample data of 1200 farmers in the main wheat producing areas of Shaanxi Province, the theoretical conjecture is empirically tested. The results showed that the climate change information from government departments and scientific research institutions has a significant positive impact on farmers' adaptive farming behavior, but in the case of considering the three sources of information at the same time, the information source of scientific research institutions has the strongest positive impact on farmers' adaptive farming behavior. After farmers have access to climate change information exchanged by government departments, scientific research institutions and neighbors, their differences in climate change adaptive farming behavior mainly depend on their climate change cognition rather than subject trust factors. Formally organized climate change information represented by government departments and scientific research institutions has a more significant positive impact on farmers' adaptive farming behavior, but this impact depends largely on whether the information obtained by farmers can improve their climate change awareness. [ABSTRACT FROM AUTHOR]

The increased nitrogen fertilizer use has greatly boosted the agricultural production in China, however, imposed considerable environmental issues. Reducing nitrogen use in agriculture is inevitable for China to achieve the sustainable development goals. This paper established a partial equilibrium model to evaluate the reducing effects on nitrogen use under scenarios of nitrogen optimized utilization and nitrogen use efficiency improvement among seven crops and seven regions in China. Simulations revealed that: (1) nitrogen optimized utilization helps to reduce 7.73% agricultural nitrogen use in China, soybean turns to be the only exceptional crop that nitrogen use would be doubled; (2) nitrogen use could be continuously decreasing with the nitrogen use efficiency improvement, the reducing rates are 8.28% to 27.91% under 10% to 40% improvement scenarios; (3) among the crops, soybean and peanut have far greater reducing rates than other crops, maize is simulated as the least sensitive crop; (4) East, North and Central China, contribute over 60% of nitrogen use in China, while in Northeast China, nitrogen use performs the least sensitivity to the modelling scenarios. Therefore, this paper suggests that policies and incentives on nitrogen optimized utilization and nitrogen use efficiency improvement are necessary, and heterogeneities in both crops and regions indicate that flexible adjustment strategies of cropping structures in different regions should be taken into consideration towards less agricultural nitrogen use in China. [ABSTRACT FROM AUTHOR]

By utilizing the center of gravity-standard deviation ellipse, kernel density estimation, and GeoDetector, this paper analyzes the spatial distribution pattern of China's agricultural green TFP and the dynamic evolution law of its distribution in different regions based on the provincial-level related input-output data of China's agriculture from 2001 to 2020. It also investigates the factors that affect its spatial differentiation. We find that (1) China's agricultural green TFP, which has a long-term upward trend and an average annual growth rate of 3.21% between 2001 and 2020, is mostly fueled by technological advancements in the field of agriculture. (2) Agricultural green TFP tends to move eastnorthward, and its spatial distribution is gradually expanding, showing a northeast-southwest pattern. (3) Agricultural green TFP in the country as a whole and the three major food regions has increased over the study period, with absolute differences within the country gradually narrowing, and cities with higher agricultural green TFP within the regions approaching the average, and the polarization phenomenon easing. (4) The main determinants of the spatial divergence of green TFP in agriculture are the replanting index, agricultural output per capita, and the degree of financial support for agriculture. The strength of the interactions between the various factors is significantly greater than the explanatory power of any one factor. [ABSTRACT FROM AUTHOR]

Agricultural industry agglomeration is an important driving force for the green and high-quality development of agriculture. Based on the perspective of agricultural industry agglomeration, this paper discusses the impact of agricultural industry agglomeration on the level of green development of agriculture, which is of great significance for the realization of sustainable development of agriculture and the implementation of the “double carbon” goal. Based on the panel data of 30 provinces (municipalities) and autonomous regions in China from 2011 to 2020, the non-expected Super-SBM model and location entropy index method were used to measure the efficiency of agricultural green development and the level of agricultural industry agglomeration. The spatial Dubin model, tradition and spatial Markov chain were used to demonstrate the influence of agricultural industrial agglomeration on agricultural green development efficiency and its spatio-temporal dynamic evolution.The results showed that: (1) There was spatial autocorrelation in agricultural green development efficiency. Areas with higher agricultural green development efficiency will drive the improvement of agricultural green development efficiency in surrounding areas, with a positive spillover effect. (2) Industrial agglomeration can improve the efficiency of agricultural green development, and this enhancement has spatial spillover. (3) The influence of agricultural industrial agglomeration on agricultural green development efficiency and its spatial spillover have regional heterogeneity. The spillover effect of AIA to AGDE in the eastern region is greater than that in the central and western regions. Based on this, it is necessary to grasp the spatial correlation law of provincial agriculture, promote the sustainable development of regional agriculture, optimize the allocation of resources, and put forward policy implications for the improvement of agricultural green efficiency from the aspects of financial support, industrialization, human capital and urbanization. [ABSTRACT FROM AUTHOR]

The balance between agricultural development and maintenance of agro-ecological environment becomes a huge challenge because of global climate changes. Existing literature on the low-carbon pilot policy proposed by the government of China and whether the problems of agricultural development and agricultural environmental protection can be solved or not have not been reviewed. This paper analyzes the impact of low-carbon pilot policies on agricultural eco-efficiency by using SARAR model based on the data of 281 cities in China. Results show the spatial spillover effects between low-carbon pilot policies and agricultural eco-efficiency. The implementation of low-carbon pilot policy can improve agricultural eco-efficiency. Although restrained by agricultural economic development, this policy has disequilibrium effect on agricultural eco-efficiency, has a relatively large impact on agricultural eco-efficiency in western China and other poor areas, and promotes the reduction of agricultural carbon emission. The effect of the implementation of low-carbon pilot policy is affected by the initial agricultural economic development and urban economic conditions. This research aims to improve the agricultural eco-efficiency and enforce the green development of the agricultural economy via the perspective of the low-carbon pilot policy. [ABSTRACT FROM AUTHOR]

This paper studied the impact of new industrial activities on ecological security in agricultural and animal husbandry interlaced areas, and provided reference for eco-environmental protection and sustainable development. A pressure-state-response (PSR) assessment model was established in the case of Yanchi County, Ningxia Hui Autonomous Region. The comprehensive weights of the indexes were determined by AHP and entropy weight, and the ecological security status of agricultural and animal husbandry interlaced areas was evaluated. The results show that the index of pressure system fluctuated and decreased, and went through the stage from "Safe" to "Unsafe"; The index of the state system showed a rising trend, from "Extremely unsafe" to "Relatively safe", which showed the sensitivity characteristic; The response system index had been increasing year by year, and had stabilized at a "Safe" level in 2019;The overall ecosystem security index showed a fairly good development trend, with significant improvement in ecosystem functions in 2019. On the basis of the stable state system, we should ease the pressure index in the ecological security system of Yanchi County, control the scale of tourists, reduce the damage of farming and animal husbandry to the cultivated layer, and stabilize the population. [ABSTRACT FROM AUTHOR]

Low-carbon development has recently become a growing trend in agricultural modernization. It will provide beneficial guidance for exploring driving factors of agricultural carbon emissions in Hebei Province, a typical agricultural region, and formulate relevant policy on its reduction. Calculating carbon emissions in Hebei from 1995 to 2014 demonstrated that energy and land use accounted for more than 90% of agricultural carbon emissions, and there was an increasing tendency overall with a peak value in 2010 and, to a certain extent lately, a slight decline. This paper employed transformed Kaya identity in light of local actual conditions for selecting eight influencing factors. Meanwhile, the extended STIRPAT model and ridge regression were used to make regression analysis. Results showed that contributing factors were efficiency, agricultural import, urbanization, agricultural mechanization, and population, whose 1% increase caused 0.1852%, 0.1663%, 0.1597%, 0.1573%, and 0.1329% increases in carbon emissions, respectively, while 1% growth in industry structure and agricultural affluence were responsible for 0.1475%, and changing the elastic coefficient of (0.1314-0.2958lnA)% decrease in carbon emissions, respectively, where A represented agricultural output value per capita. Furthermore, there existed an inverted U-shaped EKC between economic progress and carbon emissions. Given the above conclusions, policy recommendations were provided for effectively achieving agricultural carbon emissions reductions. [ABSTRACT FROM AUTHOR]