Technological Progress In Agriculture Research Articles

How does the digital transformation of agriculture affect carbon emissions? Evidence from China’s provincial panel data

Agriculture is becoming a substantial contributor to carbon emissions in China, and the efficient reduction of agricultural carbon emissions (ACEs) has become a universal concern. Currently, the digital transformation of agriculture (DTA) provides a new way to reduce carbon emissions. However, questions regarding whether and how DTA suppresses ACEs remain the focus of both academic and practical attention; thus, they serve as the objectives of this study. Based on theoretical analyzes, the carbon emission reduction effect of DTA is empirically analyzed using panel data from 30 Chinese provinces between 2015 and 2021 with a benchmark regression model, mediating effect model and threshold effect model. The results show the following: (1) DTA significantly reduces ACEs. (2) DTA reduces ACEs through three paths: expanding the agricultural production scale, optimizing the agricultural industrial structure, and promoting agricultural technological progress. The agricultural industrial structure has the most considerable mediating effect, while the agricultural production scale expansion has the smallest effect. (3) The inhibitory effect of DTA on ACEs shows very distinct heterogeneity. DTA primarily reduces ACEs in eastern and nongrain production areas yet has an insignificant impact on other areas. In addition, the DTA has a significant inhibitory effect on ACEs from both fertilizers and diesel oil. (4) The inhibitory effect of DTA on ACEs is nonlinear rather than linear. There is a single threshold effect for the effect of DTA on ACEs, which is insignificant below the threshold and significantly negative above the threshold. Therefore, China’s central and local governments need to increase the level of DTA, encourage farmers to moderately expand the scale of their operations, emphasize the agricultural service industry, and enhance agricultural technological innovation to ultimately reduce ACEs.

The impact of green finance policy on land ecological security: City-level evidence from China

As the phenomenon of ecological degradation increases, there is a growing body of research related to green finance, but no papers evaluating the link between it and land ecological security. Thus, this research calculates land ecological security using data from 158 cities in China's major grain-producing regions from 2012 to 2020. Taking China's green finance policy as an example, it applies the synthetic difference-in-difference method to analyze green finance's impact on land ecological security. The conclusions show that, first, green financial policy implementation has contributed to the improvement of land ecological security by 0.154 units. This result still holds after a series of robustness tests such as parallel trend tests, dynamic effects tests, and placebo tests. Second, mechanism analysis finds that green finance affects land ecological security through three paths: agricultural scale management, agricultural technological progress, and eco-industrialization. Third, in terms of the sub-dimension of eco-industrialization, green finance promotes domestic tourism revenues, agriculture, forestry, and animal husbandry, while its impact on international tourism revenues and fisheries is not significant. The results herein confirm the role of green finance in securing ecological security of land. Future research will further enrich the indicator system of land ecological security as well as excavate the boundary conditions for green finance in order to promote land ecological security.

The Impacts and Spatial Characteristics of High-Standard Farmland Construction on Agricultural Carbon Productivity

Agricultural carbon productivity combines the dual attributes of reducing carbon emissions and stabilizing economic growth, and is a core aspect of the new era of low-carbon agricultural development. The construction of high-standard farmland is an important initiative to promote high-yield and high-efficiency agriculture, as well as environmentally sustainable development through land improvement in China. However, the impact of high-standard farmland construction on agricultural carbon productivity and its mechanisms is still in the process of being determined. In order to fill this gap, this study aims to construct a theoretical, analytical framework for the impact of high-standard farmland construction on agricultural carbon productivity. Based on the current situation of high-standard farmland construction and the characteristics of agricultural carbon productivity in China, this study used the panel data of 31 provinces, from 2003 to 2017 in China, to empirically examine the effects, mediating paths, and spatial characteristics of the construction of high-standard farmland on agricultural carbon productivity using a double fixed-effects regression model, a mediating-effects model, and a spatial econometric model. The results show that: (1) High-standard farmland construction has a positive effect on agricultural carbon productivity, with a direct effect coefficient of 0.139 after adding a series of control variables. (2) Furthermore, heterogeneity analysis shows that the impact of high-standard farmland construction on agricultural carbon productivity will vary greatly depending on the topographic characteristics of the studied area, the level of economic development, and whether it is a main grain-producing area. (3) Mechanism analysis shows that agricultural scale operation, agricultural planting structure, and agricultural technology progress all have partial mediating roles in the impact of high-standard farmland construction on agricultural carbon productivity, with mediating effect coefficients of 0.025, 0.024, and 0.013, respectively. (4) Agricultural carbon productivity has a spatial correlation, and for every 1% increase in the level of high-standard farmland construction, agricultural carbon productivity increases by 0.117%, with a direct effect of 0.074% and a spatial spillover effect of 0.043%. Our study explains the impact effects, mechanisms, and spatial spillover effects of high-standard farmland construction on agricultural carbon productivity from theoretical and empirical perspectives, thus deepening the literature on the relationship between high-standard farmland construction and agricultural carbon productivity, and providing a theoretical basis and practical references for improving agricultural carbon productivity from the perspective of high-standard farmland construction policy.

Agricultural and Manufacturing Pollution: Labor Health and Technology Progress

In this paper, we hold that it is the input of capital in agricultural production that is the main reason for agricultural pollution in developing countries under existing technical conditions. We try to integrate agricultural pollution into a general equilibrium model with environmental pollution caused by labor movement by setting up environmental "health factor" and undertake a comparative static analysis about the impacts of manufacturing and agricultural technology progress. The main conclusions of this article are that manufacturing and agricultural technology progress improve the environment under the model with agricultural pollution; however, the economic impacts of manufacturing and agricultural technology progress are different: manufacturing technology progress drops manufacturing output, while agricultural technology progress raises agricultural output.

The impact of technological advancements on carbon emissions in agriculture and rural areas

Rural agriculture is an essential aspect of carbon emission reduction and sequestration and also has the potential to achieve “carbon peak” and “carbon neutrality.” A DEA-Malmquist index model is used to estimate the technical progress of agriculture using panel data from 30 provinces from 2012 to 2021. The evolution trend and spatial correlation of agricultural and rural carbon emissions are measured based on the spatial and temporal dimensions. The dynamic panel spatial lag model was also used to empirically test the mechanism of agricultural technological progress affecting agricultural rural carbon emissions. The results show that: ① There are apparent evolutionary characteristics and spatial agglomeration of agricultural and rural carbon emissions, and carbon pollution between provinces shows a weakening trend ② Agricultural technological progress can effectively drive carbon emission reduction in agriculture and rural areas, and the improvement of the farmers’ income structure can effectively regulate the carbon emission reduction efficacy of the total factor productivity, technological efficiency, and technological upgrading ③ The negative spatial spillover effect of agricultural technological progress on carbon emissions is significant; when the introduction of the farmers’ income structure as an interaction term, the negative spatial spillover effect of agricultural technological progress is significant. The negative spatial spillover effect of agricultural technological progress on carbon emissions is significant; introducing farmers’ income structure as an interaction term weakens the negative spatial spillover effect.

The rebound effect of energy consumption and its determinants in China's agricultural production

With the facilitation of agricultural modernization, China's agricultural energy consumption continues to rise. This paper empirically tests the agricultural energy rebound effect and its influencing factors in China during 1999–2020. It is believed that the improvement of energy efficiency has not led to the expected energy-saving effect in agriculture due to the "Jevons paradox" of energy efficiency and energy consumption. The average energy efficiency of China's agricultural energy consumption was 0.446, and the average energy rebound effect was 68.9 %. The level of agricultural mechanization, the effective irrigated area of farmland and agricultural investment have a positive impact on the rebound effect of agricultural energy, and the direct effects are 0.062, 0.008 and 0.064, respectively, while agricultural labor force and energy price have a negative impact on the rebound effect of agricultural energy. In particular, technology spillover and scale spillover led by agricultural technology progress have strong negative space spillover effect. As it is argued, 1 % of agricultural technology progress can reduce 3.5 % of agricultural energy rebound effect in surrounding areas. In order to reduce the energy rebound effect, it is suggested to increase the subsidies to agricultural labors and rationally formulate regional differentiated energy regulation policies.

Technological progress in the function of productivity and sustainability of agriculture: The case of innovative countries and the Republic of Serbia

Bearing in mind the predictions of global population growth and the reduction of agricultural areas, followed by the depletion of non-renewable resources and environmental pollution, which leads to climate changes, it is necessary to implement sustainable solutions in the shortest possible time in agriculture, as one of the leading polluters. It is necessary to resolve the contradiction between increasing yields and preserving the environment. In this sense, modern technological solutions in agriculture should be applied, which will lead to an increase in productivity, i.e. creating a higher yield on the same or smaller areas. This can be achieved by optimizing the use of inputs in agriculture by introducing different solutions within precision agriculture. AI is one solution that needs to be developed and that leads to sustainable development. Adequate education, digital literacy and appropriate infrastructure are also required for its application. The goal of the research is to indicate the direction in which technological progress in agriculture should go and how the current technologies applied in agriculture reflect on the economic and sustainable development. With OLS panel regression concluded that only agricultural technologies that lead to increase productivity in agriculture have a positive impact on economic and sustainable development.

On the Non-linear Impact of Agricultural Technological Progress on Rural Revitalization

There are studies on the impact of agricultural technology progress on rural revitalization. Domestic scholars have initially studied the relationship between the two. Agricultural technological progress has a significant impact on rural revitalization, and rural revitalization is a nonlinear system. This paper will use the threshold variable model and the DLNM nonlinear lag model to deeply test the nonlinear impact of agricultural technological progress on rural revitalization, and at the same time explore whether there is a lagged impact, explore the path of rural revitalization using the mediation model, and put forward relevant policy suggestions.

Research on the Impact of Agricultural Trade on Agricultural Carbon Emissions in China

Based on the panel data of 31 provinces in mainland China from 2001 to 2020, this paper empirically examines the impact of agricultural trade on agricultural carbon emissions and its mechanism. The results show that agricultural trade has a significant inhibitory effect on agricultural carbon emissions, and its effects are heterogeneous, and the effect is more obvious in the central and western regions and non-grain-producing areas than in the eastern regions and major grain-producing areas. From the perspective of mechanism, agricultural technology progress is an important channel for agricultural trade to inhibit agricultural carbon emissions, and agricultural trade can inhibit agricultural carbon emissions by promoting agricultural technology progress. Based on this, it is proposed to actively promote the liberalization of agricultural trade, strengthen the exchange of agricultural low-carbon development experience among provinces and trade between agricultural products, and strengthen the progress of agricultural technology to achieve agricultural carbon reduction.

Can Land Transfer Promote Agricultural Green Transformation? The Empirical Evidence from China

As an important means of farmland policy, whether land transfer can promote agricultural green transformation is worthy of further study; however, related research is relatively rare. Based on the inter-provincial panel data from 2005 to 2020, this paper examines the influence of land transfer on agricultural green transformation and its underlying mechanism by using a two-way fixed effect model and an intermediary effect model. This study reveals significant findings as follows: (1) Land transfer substantially promotes agricultural green transformation. (2) Energy consumption is a major contributor to the growth of agricultural carbon emissions; however, land transfer can mitigate this by reducing energy consumption. (3) Land transfer can promote agricultural green transformation by fostering agricultural technology progress. (4) Further analysis reveals that land transfer in economically developed areas and the southeastern side of the “Hu-Huanyong Line” significantly enhances agricultural green transformation. Based on these findings, this paper suggests promoting land transfer while considering regional differences. Additionally, attention should be directed towards reducing energy consumption and encouraging agricultural technology’s progress.

Total-Factor Energy Efficiency and Its Driving Factors in China’s Agricultural Sector: An Empirical Analysis of the Regional Differences

Improving agricultural energy efficiency is essential in reducing energy consumption and achieving agricultural sustainable development. This paper aims to measure the agricultural total-factor energy efficiency in China rather than the partial-factor energy efficiency while taking full account of regional heterogeneity and to investigate the driving factors of agricultural total-factor energy efficiency. The empirical results showed that the average value of agricultural total-factor energy efficiency is 0.814 in China, and the technological gap ratio is 0.853. The regional difference in agricultural total-factor energy efficiency was quite obvious. Higher agricultural energy inputs are associated with higher agricultural total-factor productivity. The total value of potential agricultural energy savings in 30 provinces of China reached 1704.41 billion tons of standard coal. In terms of the absolute amount of agricultural energy saving, the amount was largest in the low-energy-input area, which was 113.87 million tons of standard coal, accounting for 66.81% of the total potential saving amount. Furthermore, we used the Tobit model to analyze the influencing factors of agricultural total-factor energy efficiency. We found that the proportion of agriculture to GDP has a positive impact on agricultural total-factor energy efficiency, while the per capita income of farmers, fiscal support for agriculture, the illiteracy rate of farmers, agricultural labor input, and agricultural capital stock have a negative impact on agricultural total-factor energy efficiency. Finally, we proposed policy implications in terms of agricultural technological progress, agricultural infrastructure, technical training, etc.

Effects of Land Transfer on Agricultural Carbon Productivity and Its Regional Differentiation in China

Facing the realistic threat of natural environment deterioration and frequent extreme weather, improving agricultural carbon productivity has become an objective requirement for achieving the goal of double carbon and for promoting the high-quality development of agriculture. As an important path toward improving land-use efficiency and promoting agricultural technological progress, land transfer has a potential positive effect on improving agricultural output and inhibiting agricultural carbon emissions. Based on the current situation of land transfer and the characteristics of agricultural carbon productivity in China, this study used the panel data of 30 provinces, from 2006 to 2019, in China to empirically test the relationship between land transfer and agricultural carbon productivity via the spatial Durbin model. The results show that (1) land transfer has a positive effect on agricultural carbon productivity; (2) agricultural carbon productivity has a spatial correlation, and the impact of land transfer on agricultural carbon productivity has a spillover effect; and (3) there are regional differences in the impact of land transfer on agriculture carbon productivity. Based on the results of the study, this paper puts forward policy recommendations from three aspects through which to optimize land transfer and enhance agricultural carbon productivity.

Design of centrifugal radial fans using regression analysis methods

With the development of scientific and technological progress in agriculture, the use of operational and mathematical modelling for effective solution of problems and resource conservation in the field of agricultural engineering is relevant. Therefore, the purpose of the study was to determine the optimal parameters of the centrifugal radial fan of a pneumatic precision seed drill by constructing a new mathematical model of the process of its operation. This was achieved by applying mathematical modelling methods when planning multi-factor experiments. As a result, a complex of automated experiments has been defined, which leads to a significant increase in the productivity of scientific work. A statistical representation of the experiment is established, which allows moving to a multi-factor active experiment, in which it is possible to separate the influence of factors from the noise background and make a transition to statistical methods for analysing the results. This allowed predicting the optimal characteristics of the centrifugal radial fan of the precision seed drill. In the course of this study, a new regression equation was compiled in the form of a first-degree polynomial, which determines the influence of each of the factors on the magnitude and value of the response. The coefficients of the polynomial are determined, the significance of the coefficients is estimated, and the adequacy of the proposed model is checked. After obtaining the regression equation, it became possible to graphically construct the dependence of the response function on impact factors. A fractional factor experiment was also performed, which determined the values of the parameters of the object’s state for all possible combinations of levels of variation of the factors Xi. Based on the established functional relationship between the output parameter of the fan, a regression equation of the following form is obtained: Pv=Pv(n, ß1, ß2, z). This predicted the receipt of the total pressure Pv (Pa), when setting different values of independent quantities n, ß1, ß2 and z. The application of the obtained analytical dependencies significantly simplified the determination of optimal design parameters of pneumatic systems for the development and construction of modern technical seed drills

Agricultural credit scale and agricultural green production efficiency: a Metafrontier-Malmquist-Luenberger and panel Tobit approach

The agricultural credit scale plays a crucial role in improving the agricultural green production efficiency (AGPE) in China. This paper selected the panel data of 30 provinces in China from 2009 to 2020 and used the Metafrontier-Malmquist-Luenberger index to calculate the agricultural green production efficiency. On this basis, this paper uses the Panel Tobit model to analysis the impact of agricultural credit scale on AGPE. The main conclusions are as follows: 1) From 2009 to 2020, the average AGPE in 30 provinces was 4.2%, and agricultural technology progress was the main driving factor for AGPE growth. 2) The agricultural credit scale significantly promotes AGPE, and the impact of the agricultural credit scale on AGPE presents a significant inverted U-shape. 3) The impact of the agricultural credit scale on AGPE in eastern, central, and western regions is significantly heterogeneous. 4) AGPE has significant spatial spillover effects. This paper believes that improving agricultural green production efficiency requires paying attention to the important role played by the scale of agricultural credit.

Output response of non‐point source pollutants and its driving mechanisms of different arable land use patterns

AbstractThe irrational use of arable land has caused increased nutrient loss and aggravated non‐point source (NPS) pollution. This natural process has a significant socioeconomic origin. However, because of the inconsistency between the simulation scale of NPS pollution mechanism models and the statistical calibre of socioeconomic factors, the quantitative expression of the relationship between socioeconomic development, arable land use, and NPS pollutant output needs further exploration. We improved the mechanism model using a flow accumulation algorithm to construct a measure of the NPS pollutant output response at the administrative region scale. The mediating effect test confirmed that socioeconomic factors such as labour transfer, farmland property rights, large‐scale operations, agricultural technological progress and risk aversion were also fundamental drivers that affected the NPS pollutant output by changing the arable land use form factors. The mediating drivers included endowment, landscape morphology, management system, planting mode and production capacity. The average total phosphorus concentrations per unit area in townships with various arable land use patterns were grain and economical crop extensive operations (0.83 mg/L); grain and economical crop scale operations (0.54 mg/L); grain, oil, and cotton scale operations (0.45 mg/L); and suburban compound operations (0.44 mg/L). We found that the degree of influence and path of each fundamental and mediating driver on NPS pollutant output concentrations showed clear differences between townships with different patterns, which were the primary reasons for the significant differences in NPS pollutant output responses.

The Effects of Agricultural Technology Progress on Agricultural Carbon Emission and Carbon Sink in China

The development mode of expanding agricultural scale will inevitably lead to an increase in agricultural carbon emissions but the impacts of agricultural technology progress on agricultural carbon emission and carbon sink are still not quite clear. This paper firstly discuss the definition of agricultural technology level. Then the estimating methods of agricultural technology, agricultural carbon emission and carbon sink are introduced. Based on the China’s provincial panel data with 31 province from 2000 to 2019, the indicators are calculated and statistically analysed. After that, the representativeness of the three secondary classifications of the agricultural technology is empirically checked. Panel data regression models especially the fixed effect model is employed to estimate the effects of agricultural technology level as well as its components on agricultural carbon emission and carbon sink. Results show that the agricultural carbon sink is approximately 10 times higher than agricultural carbon emission. Agricultural technology level in general has significant effect on the carbon emission rather than the carbon sink. Our suggestion is that (1) it is not necessary to worry about the agricultural carbon emission since the net effect of agriculture is carbon neutrality; (2) the development of agricultural production technology and agricultural management technology needs strong support, and the two need to develop coordinated.

Sustainable growth, input factors, and technological progress in agriculture: Evidence from 1990 to 2020 in China

This paper decomposes agricultural input factors into labor, land, fertilizer, and farm machinery in 31 provinces of China from 1990 to 2020. This paper analyzes the input factor’s contribution rates to China’s agricultural growth using the stochastic frontier model. The empirical results indicate that the contribution rate of input factors in China’s agricultural growth has weakened, with decreasing contribution rate of labor, an increasing contribution rate of fertilizer and machinery, and decreasing contribution rate of the land year by year. The contribution rate of technological progress is increasing, and there is room for improvement. In addition, technological progress and input factors alternately lead to the time of policy change in China. The research also shows that the prerequisite for promoting rural supply-side reform and achieving sustained agricultural growth is ensuring a stable supply of input factors, focusing on promoting agricultural technological progress.

Green Finance Assists Agricultural Sustainable Development: Evidence from China

Whether green finance can promote agriculture to achieve carbon emission reduction is an important issue in agricultural sustainable development. Based on panel data on 30 provinces in China from 2011 to 2020, this paper established a mediation effect framework and employed stepwise regression and bootstrapping to study whether and how green finance can promote carbon emission reduction in China’s agricultural sector. The empirical research results indicate that the development of green finance can significantly reduce China’s agricultural carbon emission intensity. Using instrumental variables for robustness regression tests, the empirical results were also found to be robust. Further research found that green finance can not only directly promote agricultural carbon emission reduction but also indirectly facilitate it by optimizing the agricultural industrial structure and guiding agricultural technological progress. Finally, this article puts forward a number of policy recommendations to actively develop green finance, optimize the structure of the agricultural industry, and promote the progress of agricultural technology with the overarching aim of promoting the sustainable development of China’s agriculture through green finance.

Diferenciação espaço-temporal e correlação espacial da produtividade fatorial total agrícola na China: uma estimativa baseada em dados de cidades em nível de prefeitura

ABSTRACT: The improvement of agricultural TFP is critical to promoting the high-quality development of agriculture. This paper described and identified the spatiotemporal differentiation characteristics and spatial correlation of China’s agricultural TFP in 283 prefecture-level cities from 2001 to 2018 using the Metafroniter-Malmquist and Moran index. The results showed that: (1) From 2001 to 2018, China’s agricultural TFP was 6.64%, and its growth was mainly driven by agricultural technological progress. The contribution of agricultural technological efficiency was small. The growth law showed an “inverted U-shaped” growth trend of first rising and then falling. (2) China’s agricultural TFP has significant characteristics of regional unbalanced growth. (3) The growth rate of agricultural TFP in most prefecture-level cities is medium and slow, and most prefecture-level cities relied on agricultural technological progress to promote growth. (4) The agricultural TFP of various cities showed a significant spatial correlation phenomenon of “high-high” or “low-low.” This study has significant theoretical and practical value for maintaining the stable growth of China’s agricultural TFP and promoting the high-quality development of China’s agriculture.

Impact of agricultural insurance on green agricultural production in China: Based on the mediation effect of agricultural technology progress

Impact of agricultural insurance on green agricultural production in China: Based on the mediation effect of agricultural technology progress