Agriculture In China Research Articles

Analysis and Performance Evaluation of Decoupling Relationship between Carbon Emissions and Economic Development in Chinese Agriculture

Analysis and Performance Evaluation of Decoupling Relationship between Carbon Emissions and Economic Development in Chinese Agriculture

A novel interpretation of farmland abandonment: evidence from the famine experience

The growing severity of farmland abandonment in rural areas has sparked concerns about the lack of people willing to cultivate the land. This study attempts to find the endogenous factors of farmland land abandonment among Chinese farmers and to curb land degradation to stabilize food security. Based on the China Labor-force Dynamics Survey (2016–2018), this paper explores the effect of famine experience on farmland abandonment using logit and DID models. We find that famine experience does increase the probability and extent of farmland abandonment, and undergo a series of robustness tests. We also find that the famine stigma effect increases the likelihood and extent of farmland abandonment by increasing risk aversion and reducing social trust and investment in agriculture. The growth of urbanization in China worsens the effects of famine, whereas local communal production services remove the effects of famine. The overall findings of this study provide useful insights for the government to protect land quality and food security and to carefully consider the role played by communities.

A Brief Analysis of "On the Correct Handling of Contradictions Among the People" and Its Contemporary Value

Mao Zedong's original theoretical contribution to Marxism has had a profound impact on the exploration and development of socialism with Chinese characteristics. This work plays an important role in providing theoretical guidance for national construction, covering a wide range of topics, including the differentiation and resolution of socialist contradictions, issues of political repression, and the relationship between the development of agriculture and industry in China. This paper aims to explore the historical context and core ideas of this article, as well as its historical significance and contemporary value in the development of socialism with Chinese characteristics.

Promoting Sustainability: Land Transfer and Income Inequality Among Farm Households

The United Nations Sustainable Development Goals emphasize the dangers of inequality and initiatives on how to reduce it. Income inequality is an important part of this and can cause many social problems. This study aims to investigate the impact of land transfer on income inequality of Chinese farm households and its mechanism of action. This study empirically analyzes the impact of land transfer on farm household income inequality based on the OLS model using 27,134 samples from the 2018–2020 China Family Panel Study (CFPS) data. The study finds that land transfer can effectively reduce income inequality among farm households. However, only land transfers out affect income inequality; the effect of land transfers in is not significant. At the same time, there is some heterogeneity in the impact of land transfers on farm household income inequality. The effect is greater in the east and west than in the center. The effect is greater in the north than in the south. The role is greater in food-producing areas than in non-food-producing areas. Mechanism testing shows that land transfer impacts income inequality among farm households by promoting entrepreneurship. Farm households who use the Internet and have stronger social capital gain more from the impact of land transfer on income inequality.

Xiao Han and Lei Wang: Organic agriculture and biodiversity in China

Xiao Han and Lei Wang: Organic agriculture and biodiversity in China

Long-term effects of agronomic practices on winter wheat yield and NUE in dryland regions of USA and China: a long-term meta-analysis

Dryland agriculture is fundamental to global crop production and vital to food security. Conservation tillage is extensively practiced in USA wheat cultivation. Meanwhile, the adoption of conservation tillage by Chinese farmers is limited. This meta-analysis compared the yield and nitrogen use efficiency (NUE) between conservation tillage and conventional tillage (CT) with different types of cropping systems, mulching methods, levels of nitrogen fertilizer (NF), and addition of manure. The meta-analysis presented that conservation tillage at high-NF enhanced the yield and NUE, and reduced the yield and NUE at low-NF, compared to CT. The interaction of conservation tillage with leguminous cover crops (LCC) and manure application increased the yield and NUE at low-NF, compared to CT. Non-leguminous cover crops (NLCC) increased the yield and NUE under high-NF than low-NF. The interaction of conservation tillage with management practices showed that the no-tillage (NT) with leguminous cover crops (LCC) significantly increased wheat yield by 58% and NUE by 47% under low-NF compared to CT. However, increasing the rate of NF did not increase the yield under such interaction. Cropping systems, mulching types, and manure application mainly determined the effects of conservation tillage on wheat yield and NUE. The adverse impact of CT on yield and NUE could be alleviated with the application of LCC and manure under moderate NF. We demonstrate that adding LCC and manure have a generally substitutive relationship with N fertilizer, resulting in a significant increase in wheat yield and NUE at low-NF doses as at high N fertilizer dosages. Therefore, based on the obtained results, moderate NF with LCC and manure application is recommended for growing winter wheat in dryland regions of the USA and China.

More ESG Practices, Higher Financial Performance? The U‐Shaped Pattern in China's Agricultural and Food Firms

ABSTRACTESG (environmental, social, and governance) practices, an internationally recognized concept of a firm's sustainability, can serve as a bridge to enhance effective communication between firms and various stakeholders. It is also a new tool for measuring firms' value. This study employs a balanced panel data set of 114 publicly traded agricultural and food firms in China from 2016 to 2022. It empirically investigates the relationship between ESG and financial performance based on shareholder primacy theory and stakeholder theory. Employing a two‐way fixed effects (FE) model, our findings reveal a U‐shaped nonlinear pattern in how ESG impacts financial performance. It differs from previous studies that found predominantly positive relationships: Specifically, the average ESG score for firms is 0.396, the median is 0.390, and the inflection point of the U‐shape occurs at 0.53. When firms' ESG investments are less than 0.53, the high initial ESG cost makes it difficult to transform ESG into financial improvement. However, once this threshold is surpassed, good ESG can convey an excellent reputation to the public and increase anti‐risk ability—which, in turn, significantly improves firms' financial performance and facilitates long‐term development. Also, our study demonstrates that firms' ownership and different positions in the supply chain differentially affect the relationship between ESG and financial performance. This paper also offers insights into promoting the sustainable development of Chinese agri‐food firms.

Spatial distribution and risk assessment of perchlorate in raw cow milk from China

Perchlorate is a ubiquitous environmental contaminant worldwide, recognized as an emerging thyroid toxicant. This study focused on the pollution status, spatial distribution, possible sources of perchlorate in raw cow milk collected from 155 dairy farms in China, as well as the health risk of exposure to perchlorate through dairy products. The results showed that the detection rate of perchlorate in raw milk was 100% with the mean of 15.9 μg/kg, indicating the ubiquitous contamination of perchlorate in raw milk from China. The simulation of spatial distributions indicated that the levels of perchlorate in raw milk were spatially correlated, and relatively high levels of perchlorate exist in certain parts of Beijing-Tianjin-Hebei, Shanxi, Henan, and Zhejiang, suggesting potential environmental perchlorate contamination in these regions. A positive correlation was found between the perchlorate level in milk and the perchlorate level in feed, indicating the transfer process of perchlorate from feed to milk. The hazard quotient (HQ) values of exposure to perchlorate by dairy products ranged between 0 and 2.14, with the mean of 0.0188 and P95 of 0.101, indicating relatively low health risk to perchlorate through dairy products. To our knowledge, this is the first nationwide study on the spatial distribution and risk assessment of perchlorate in raw cow milk from China.

Locating the suitable large-scale solar farms in China's deserts with environmental considerations

Desert areas offer rich solar resources and low land use costs, ideal for large-scale new energy development. However, desert ecosystems are fragile, and large-scale photovoltaic (PV) power facilities pose ecological risks. Current assessments of PV plant sites in deserts lack consideration of wind-sand hazards and ecological impacts. In this study, we have developed a new large-scale photovoltaic (PV) site selection model that integrates the analytic hierarchy process with geographic information system technology, and applies it to the desert regions of China. The results show that the potential for large-scale PV power plants in China's deserts is significant, with 69.4 % of the region assessed as medium or higher. The most suitable area is 12.7 × 104 km2 (7.6 % of the overall study area), mainly centered in the Tibetan Plateau's Qaidam Basin Desert and the deserts of northern China, characterized by favorable solar resources, climate, and terrain. Across all regions, gravel deserts are recognized as more suitable for the construction of large-scale PV power projects than sandy deserts. Considering varying PV installation density scenarios with an installed capacity potential of 36.4–84.9 TW and system costs ranging from 10.0 to 33.5 trillion USD, the study estimates an annual solar power generation potential of 47–110 PWh which is 1.7–3.9 times the global electricity demand. Carbon emissions could be reduced by 26.8–62.6 gigatons annually, offsetting 73–170 % of global emissions. Covering just 4.8–11.5 % of China's desert area (8 × 104–19.4 × 104 km2) would meet the projected 2025 electricity needs of the country. This study lays the groundwork for spatial planning and benefit assessment of large-scale PV projects in desert regions, and reduces conflicts between PV plant construction and local ecosystem.

Transmission of carbapenem-resistant enterobacterales producing NDM-5 during the broiler breeding process in China

This study conducted a four-month monitoring of carbapenem resistance in a broiler breeding farm in China. A total of 185 carbapenem-resistant bacterial isolates were obtained from 2298 cloacal swabs from broiler breeders and their offspring within a production cycle. The detection rate of carbapenem-resistant isolates was higher during the brooding period. Whole-genome sequencing (WGS) was performed on 133 isolates based on sampling stages, including 113 carbapenem-resistant Enterobacterales (CRE) isolates and 20 Stenotrophomonas pavanii isolates, which have intrinsic resistance to carbapenems. A total of 69 antibiotic resistance genes (ARGs), including blaNDM-1, mcr-1, and blaNDM-5, were identified among the sequenced CRE isolates. Notably, blaNDM-5 (92.0 %, 104/113) was the primary contributor to carbapenem resistance. CRE isolates from the same breeding stage exhibited close genomic relationships, and the blaNDM-5 genes were observed in similar genetic backgrounds, indicating the transmission of CRE strains and blaNDM-5 during the broiler breeding process. No CRE was isolated from 0 d broiler offspring, suggesting that broiler breeders were not the direct source of CRE in their offspring. Tracing the feeding process revealed that brooder and rearing houses were likely key factors in the cross-transmission of CRE between broiler breeders and their offspring. CRE pose a significant threat to public health and food safety. China is one of the world's leading poultry producing and consuming countries. This study provided insights into the epidemiological trends and key transmission nodes of carbapenem resistance and CRE within the broiler breeding process, which could help the control of antibiotic resistance and bacterial infections in the broiler industry.

Untangling lineage introductions, persistence and transmission drivers of HP-PRRSV sublineage 8.7

Despite a rapid expansion of Porcine reproductive and respiratory syndrome virus (PRRSV) sublineage 8.7 over recent years, very little is known about the patterns of virus evolution, dispersal, and the factors influencing this dispersal. Relying on a national PRRSV surveillance project established over 20 years ago, we expand the available genomic data of sublineage 8.7 from China. We perform independent interlineage and intralineage recombination analyses for the entire study period, which showed a heterogeneous recombination pattern. A series of Bayesian phylogeographic analyses uncover the role of Guangdong as an important infection hub within Asia. The spatial spread of PRRSV is highly linked with a composite of human activities and the heterogeneous provincial distribution of the swine industry, largely propelled by the smaller-scale Chinese rural farming systems in the past years. We sequence all four available modified live vaccines (MLVs) and perform genomic analyses with publicly available data, of which our results suggest a key “leaky” period spanning 2011–2017 with two concurrent amino acid mutations in ORF1a 957 and ORF2 250. Overall, our study provides an in-depth overview of the evolution, transmission dynamics, and potential leaky status of HP-PRRS MLVs, providing critical insights into new MLV development.

Response Mechanism and Evolution Trend of Carbon Effect in the Farmland Ecosystem of the Middle and Lower Reaches of the Yangtze River

The farmland system in the global terrestrial ecosystem has dual attributes as both a carbon source and a carbon sink, playing a crucial role in controlling carbon emissions and mitigating global warming. Using carbon source and sink accounting of farmland ecosystems, we applied methods such as standard deviation ellipse, Tapio decoupling theory, and Markov chain to analyze the spatiotemporal changes, response mechanisms, and evolutionary trends of regional carbon effects. The results indicated that from 2011 to 2021, the farmland ecosystem in the middle and lower reaches of the Yangtze River consistently acted as a carbon sink. However, the net carbon sink showed slight fluctuations and significant spatial differences. The migration range of the net carbon sink center in the farmland ecosystem of the middle and lower reaches of the Yangtze River was relatively small, ranging from 115.52 to 115.77° E and 30.14 to 30.27° N. The decomposition of the Tapio decoupling index between the net carbon sink of the farmland ecosystem and agricultural output value showed the order of effects on their coupling relationship as follows: agricultural mechanization level > agricultural mechanization efficiency > agricultural output value > planting scale. The probability of maintaining the original state of net carbon sink in various cities in the middle and lower reaches of the Yangtze River (over 77%) was much higher than the probability of transfer, making it difficult to achieve a leapfrog growth in net carbon sink. The net carbon sink at the city scale exhibits the Matthew effect and spatial spillover effect. The above research results clarify the spatiotemporal changes in carbon effects in agricultural production at multiple levels, including city, province, and region. They also provide a theoretical basis for formulating differentiated regional emission reduction and sink enhancement strategies in the middle and lower reaches of the Yangtze River, promoting the rapid development of low-carbon agriculture in China.

Pricing Model Construction and Empirical Research on Catastrophe Bond Pricing for Three Major Crops in China

Agricultural disaster risks are significant for the sector's development, and existing risk management tools have limitations.This paper introduces a nationwide catastrophe bond for wheat, maize, and rice , offering broad coverage for China's agriculture. The paper utilizes marginal distribution and Copula function fitting to model the disaster losses of the three major crops from 1990 to 2022. It employs Monte Carlo simulation to generate a 10,000-year event set and rank correlation to align simulated data with real data. The bond price is then calculated using the Wang model, addressing the challenge of data scarcity and providing an innovative approach to catastrophe bond design. The study finds that bond prices increase with the coverage period and risk level, with interest-risk bonds offering higher returns and risks than principal-and-interest risk bonds. Catastrophe bonds present a more stable risk diversification method compared to reinsurance, both in terms of returns and potential losses.To further the development of agricultural catastrophe bonds, the paper recommends optimizing the issuance environment and establishing a robust market infrastructure.

A Review of the Application of Hyperspectral Imaging Technology in Agricultural Crop Economics

China is a large agricultural country, and the crop economy holds an important place in the national economy. The identification of crop diseases and pests, as well as the non-destructive classification of crops, has always been a challenge in agricultural development, hindering the rapid growth of the agricultural economy. Hyperspectral imaging technology combines imaging and spectral techniques, using hyperspectral cameras to acquire raw image data of crops. After correcting and preprocessing the raw image data to obtain the required spectral features, it becomes possible to achieve the rapid non-destructive detection of crop diseases and pests, as well as the non-destructive classification and identification of agricultural products. This paper first provides an overview of the current applications of hyperspectral imaging technology in crops both domestically and internationally. It then summarizes the methods of hyperspectral data acquisition and application scenarios. Subsequently, it organizes the processing of hyperspectral data for crop disease and pest detection and classification, deriving relevant preprocessing and analysis methods for hyperspectral data. Finally, it conducts a detailed analysis of classic cases using hyperspectral imaging technology for detecting crop diseases and pests and non-destructive classification, while also analyzing and summarizing the future development trends of hyperspectral imaging technology in agricultural production. The non-destructive rapid detection and classification technology of hyperspectral imaging can effectively select qualified crops and classify crops of different qualities, ensuring the quality of agricultural products. In conclusion, hyperspectral imaging technology can effectively serve the agricultural economy, making agricultural production more intelligent and holding significant importance for the development of agriculture in China.

The Impact of Digital Capabilities on Peasants’ Wage Growth: Evidence from Chinese Farmer Entrepreneurs

The gradual integration of digital technology into traditional Chinese villages has triggered a shift in income distribution from labor to capital, posing challenges to the wage growth of employed peasants. Based on the theory of empowerment, this paper explores the mechanisms of credit availability and talent loss in the interplay between digital capabilities and wage augmentation among employed peasants. This study empirically examines or validates the mechanism of digital capabilities on wage growth for employed peasants through the entropy weight method, the OLS linear model, the mediation effect model, and propensity score matching while using survey data from 490 farmer entrepreneurs as samples. The findings are as follows. (1) The digital capabilities of farmer entrepreneurs have a significant positive impact on the wage growth of employed peasants, and this result remains robust after a series of robustness checks. In terms of hierarchical effects, digital foundational capabilities > digital application capabilities > digital innovation capabilities. (2) Credit availability and talent loss mediate the relationship between digital capabilities and wage growth for employed peasants. (3) The digital capabilities of farmer entrepreneurs who are young, highly educated, and have a low family-dependency ratio exert a more pronounced influence on the wage growth of employed peasants. Additionally, lower policy uncertainty enhances the effect of digital capabilities on wage growth for employed peasants. The study uncovers the empowerment mechanism of digital advancements embedded during the entrepreneurial journey, enriches research on digital capabilities and common prosperity, and provides a feasible path for governments to formulate reasonable entrepreneurship and digital promotion policies.

Strategies for crop straw management in China's major grain regions: Yield-driven conditions and factors influencing the effectiveness of straw return

Tailoring straw return strategies to specific regional conditions optimize soil health, crop yield, and carbon emission reduction. This study investigated yield-driven, spatial-scale, and long-term strategies for straw return of maize, rice, and wheat cultivation in China. Through a meta-analysis of 108 studies and the application of a machine learning model, the yield effects of straw return were thoroughly examined. Nitrogen fertilizer inputs were identified having the most significant impact on yield, and the yield benefits of straw return stabilized after approximately 13 years. A optimized strategy for straw return was developed for provinces in China, resulting in average yield increases of 13.9 % for maize, 12.2 % for wheat, and 14.0 % for rice. Implementing these locally adapted straw return strategies will contribute to the long-term development of sustainable agriculture in China.

Effect of ecoliteracy on farmers’ participation in pesticide packaging waste governance behavior in rural North China

Farmers’ participation in pesticide packaging waste (PPW) governance is important for improving agricultural pollution and achieving sustainable agricultural development. By incorporating the theory of planned behavior, value-belief-norm theory, cognition and behavior theory etc., we construct a theoretical model comprising “ecoliteracy–farmers’ WTP in PPW governance–participation in PPW governance behavior.” This study investigates how ecoliteracy affects farmers’ participation in PPW governance and explores the mediating effect of farmers’ willingness to participate (WTP) in PPW governance. We use structural equation modeling to analyze data collected from a questionnaire survey including 1118 samples of Chinese farmers. The results show that (1) Ecoliteracy significantly affects farmers’ WTP in PPW governance. Ecological cognition, emotion, values, and knowledge and skills positively affect WTP in PPW governance, while ecological cognition and ecological knowledge and skills significantly affect participation in PPW governance behavior. (2) Farmers’ WTP in PPW governance mediates ecoliteracy and governance participation behavior. (3) Heterogeneity analysis reveals that different planting scales, different planting categories, and receiving/not receiving government project support have different effects on farmers’ participation in governance behavior. Farmers in the large-scale group are more likely to participate in governance than those in the medium- and small-scale groups, and farmers in the mixed grain and economic category are more likely to participate in governance than those in the economic and grain categories. Furthermore, farmers who receive government support are more likely to participate in governance than those who do not. Our results can serve as a policy making reference for promoting PPW governance in various regions.

Exploration of the optimal low-carbon peanut rotation system in South China

CONTEXTPeanut is an important economic and oil crop that has the potential to contribute to low-carbon agriculture. However, there is scarcity of comprehensive evaluations regarding the impact of various peanut rotation systems and their contribution to low-carbon agriculture. OBJECTIVEThe research aims to comprehensively evaluate the contribution of peanut rotation systems to low-carbon agriculture in South China, and expected to explore the optimal low-carbon peanut rotation system in this area. METHODSThree cropping patterns were compared over a four-year experimental period: wheat–peanut (W-P) rotation, rape–peanut (R-P) rotation, and peanut monocropping (MP), under two types of initial fields (paddy and dryland). The carbon footprint (CF), product carbon footprint (PCF), carbon sequestration, food carbon cost (FCC), soil carbon characteristics, net economic benefit, and ecosystem service values of C sequestration of three rotation ecosystems were studied. RESULTS AND CONCLUSIONSOur findings reveal that R-P, WP, and MP had total CFs of 1.788, 3.882, and 1.096 t CO2-eq·hm−2, respectively. Agricultural material input, particularly N fertilizer, was the primary CF contributor. R-P had higher carbon sequestration amount and efficiency than WP. Notably, dryland-initial fields of both R-P and WP had higher carbon sequestration efficiency (71.1 % and 17.6 % higher, specifically). Our soil carbon analysis indicates that both plant residue quality and initial field type influence C sequestration. While WP had the highest PCF (0.552 t CO2-eq t−1) and FCC of protein (3.428 kg CO2-eq·kg−1), fat (3.791 kg CO2-eq·kg−1), and energy (0.135 kg CO2-eq·1000 kcal−1), R-P showed the highest net income (3333.3 US$·hm−2) and higher ecosystem service value of C sequestration (−5.6 US$·hm−2). Furthermore, our findings reveal that common crop rotations in South China have higher CFs than the tested peanut-based systems. Therefore, R-P rotation is the most suitable system for low-carbon agriculture in the research area among these three rotations due to its lower carbon cost and higher economic benefits. And the advantages, disadvantages and uncertainties of different low-carbon agricultural indicators have also been analyzed. SIGNIFICANCEOur study would contribute to exploring agroecosystems management ways and methods to mitigation climate change and provide references for the establishment of evaluation criteria for low-carbon agriculture.

Land fragmentation, adoption intensity of climate-smart agricultural practices, and economic performance of banana farmers in China

ABSTRACT Land fragmentation (LF) may influence farmers’ choices of agricultural practices to adapt to climate change in developing countries. Based on the primary data collected from 422 banana growers in China, this work first assesses the impact of LF on farmers’ adoption intensity of climate-smart agricultural practices (CSAPs) using the instrumental variables (IV) method, and explore the heterogeneous effects of adoption intensity of CSAPs and LF on farmers’ economic performance using the quantile regression (QR) method. The estimated results provide the first insight that LF is positively associated with farmers’ adoption intensity of CSAPs in agricultural production. China has a large population and less cultivated lands for each farmer household. Thus, farmers are inclined to use more CSAPs on these fragmented lands to sustain farm productivity and net profits under climatic shocks. Furthermore, we find that the adoption intensity of CSAPs significantly enhanced the economic performance of banana farms. Specifically, the higher intensity of CSAPs improved farmers’ banana income across the selected quantiles, while it increased net farm returns only for farmers with a high-level income. However, LF exerted a negative impact on farmers’ economic performance, and it is statistically significant for low-income farmers.

Hybrid wind speed optimisation forecasting system based on linear and nonlinear deep neural network structure and data preprocessing fusion

Wind speed time series forecasting has been widely used in wind power generation. However, the nonlinear and non-stationary characteristics of wind speed make accurate wind speed forecasting a difficult task. In recent years, the rapid development of artificial intelligence and machine learning technology provides a new solution to the problem of wind speed forecasting. Combining the advance of artificial intelligence and data analysis strategy, this paper proposes a wind speed forecasting system based on multi-model fusion and integrated learning. Considering the differences in data observation and training principles of various algorithms and exploiting the advantages of each model, a wind speed forecasting system with multiple machine learning algorithms embedded in integrated learning is constructed, which includes three modules: data preprocessing, optimization and forecasting. The data preprocessing module can conduct quantitative analysis through input data decomposition and feature extraction, and the combination of multi-objective intelligent optimization algorithm and combined forecasting method can effectively forecast the wind speed time series. The validity of the algorithm is verified using the data of Shandong wind farm in China. The forecasting results show that compared with the traditional single model forecasting, the proposed integrated wind speed forecasting system based on the fusion of multiple models has higher forecasting accuracy.