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Background: The adoption of new agricultural technologies is one of the key factors for achieving sustainable agricultural development. With the rapid development of China's economy and the widening gap between urban and rural areas, it has become the norm for farmers to seek employment outside their home villages. This phenomenon not only changes the lifestyle of farmers but may also affect their attitudes toward and adoption behavior of new agricultural technologies. However, existing research in this field is not yet sufficient. This paper aims to assess the overall impact, heterogeneous effects, and mechanisms of action of migrant work experience on farmers' willingness to adopt new agricultural technologies. Methods: Based on the 8,391 sample data from 243 counties in the 2018 China Labor Force Dynamic Survey (CLDS2018), this paper uses the Linear Probability Model (LPM), Two Stage Least Square (2SLS), Conditional Mixed Process (CMP) methods, and omitted variable test to estimate the impact of migrant work experience on farmers' willingness to adopt new agricultural technologies. Simultaneously, it explored the heterogeneity in the relationship between migrant work experience and the willingness to adopt new agricultural technologies from the perspectives of gender, age, and educational level. Lastly, the Karlson-Holm-Breen (KHB) model was utilized to analyze the mechanisms through which migrant work experience affects farmers' willingness to adopt new agricultural technologies. Results: Migrant work experience significantly enhances farmers' willingness to adopt new agricultural technologies, with the probability of willingness among farmers with migrant work experience being 26.65% higher than that of farmers without such experience. At the same time, compared to female farmers, those born before 1980, and those with primary education or less, this enhancing effect is more pronounced among male farmers, those born after 1980, and those with more than a primary education. Furthermore, it was found that migrant work experience not only directly enhances farmers' willingness to adopt new agricultural technologies but also indirectly promotes it by increasing capital accumulation, enhancing risk awareness, expanding social networks, and strengthening agricultural cognition, with risk awareness and agricultural cognition playing a larger indirect role. Conclusion: Based on the empirical results, this paper suggests actively guiding farmers with migrant work experience to adopt new agricultural technologies, and encouraging return migrant labor with the intention of resettling in rural areas to engage in agriculture again, to further promote the adoption of new agricultural technologies. [ABSTRACT FROM AUTHOR]

China's agricultural economy has been hindered by insufficient accumulation of agricultural capital and credit constraints. It is worth investigating whether China's county financial marketization reform policy can alleviate these constraints and promote high-quality development of the agricultural economy (HQDAE). This paper presents an empirical analysis of the impact of county financial marketization reform on the HQDAE, based on county panel data. The focus is on the mechanism of county urbanization in the above relationship. The results show that county financial marketization has a significant non-linear impact on the HQDAE. Specifically, it has a 'U-shaped' impact on the overall growth of the agricultural economy and an inverted 'N-shaped' impact on the quality improvement of the agricultural economy. Secondly, the relationship between county financial marketization and the HQDAE is influenced by a threshold effect based on the level of county urbanization. As the level of county urbanization increases, the promoting effect of county financial marketization on HQDAE also increases significantly. Additionally, county financial marketization helps to promote county urbanization and accelerate urban-rural integration, which in turn leads to HQDAE. The research in this paper suggests that county-level local governments should promote a differentiated county financial system. In the early stages of financial market-oriented reform, the government should enhance the capacity of financial services in rural areas through tax breaks, policy incentives, and other measures to prevent financial leakage from agriculture. In the later stages of financial marketization reform, the government should strengthen financial supervision to prevent financial resources from being diverted from industry to capital. Moreover, to achieve the HQDAE, it is necessary to promote county financial market-oriented reform and accelerate the construction of county urbanization. This will help break the dual economic structure of urban and rural areas and promote the flow of financial capital, technology, and human capital from county cities to rural areas. [ABSTRACT FROM AUTHOR]

The stability of agricultural futures market is of great significance to social economy and agri-cultural development. In view of the complexity of the fluctuation of agricultural futures prices, it is challenging to make up for the shortcomings of the existing data preprocessing technology so as to improve the prediction accuracy of the model. This paper puts forward a new VMDSGMD-LSTM model based on improved quadratic decomposition technology and artificial intelligence model. First of all, in the data preprocessing part, VMD is used to decompose the original futures price data, and SGMD is used to further process the remaining components. Secondly, the LSTM model is used to predict a series of modal components, and the final result is obtained by synthesizing the predicted values of different components. Furthermore, based on the futures trading data of wheat, corn and sugar in China agricultural futures market, this paper makes an empirical study in the 1-step, 2-step and 4-step ahead forecasting scenarios, respectively. The results show that compared with other benchmark models, the VMD-SGMD-LSTM hybrid model proposed in this paper has better forecasting ability and robustness for different agricultural futures, which effectively makes up for the shortcomings of existing research. [ABSTRACT FROM AUTHOR]

Digitization is becoming the key to achieving rural revitalization, and there is a complex inter-active relationship with farmer enrichment, and agriculture development, making it highly valued by governments around the world. Quantitatively evaluating the symbiotic relationship between rural digitization, farmer enrichment, and agricultural development, and reveal the driving mechanism behind them, which can provide evidence for the rural government, agricultural enterprises, and relevant stakeholders. This paper conducts an empirical study of 84 digital village national pilots in China based on coupling coordination model and geographically weighted regression, with focus on the spatial characteristics, symbiotic relationship and driving mechanisms of the pilots. The symbiotic relationship between rural digitization, farmer enrichment, and agriculture development has significant heterogeneity, with most of the pilots in coordination state. The driving mechanism of rural digitization, farmer enrichment, agriculture development, and symbiotic relationship were complicated, with significant heterogeneity and synergy in the driving forces of different factors, and special attention should be paid to spatial effects (the nature and intensity of regression coefficients in local regions) in the policy design and implementation. It is worth noting that population aging mainly plays a negative role, while industrialization, government support, resident capacity plays a positive role. The other factors play both positive and negative roles. Income gap between urban and rural residents, population aged 65 and above, financial self-sufficiency are the most critical factors. We suggest developing differentiated management policy, accurate management policy, and integrated management policy, which can provide a basis for digital village and smart village planning, construction and management in China. In view of the significant differences in rural digitalization and its driving mechanisms in different pilots as shown in the study, it is necessary to design differentiated spatial policies according to local conditions, to design accurate management policies based on the driving effects of key single factors, and to design integrated development policies by taking into account the interactive effects of multiple factors. [ABSTRACT FROM AUTHOR]

The coupling coordination of agricultural technology innovation with food security is of great significance for high-quality agricultural development. By identifying the coupling coordination relationship between the two systems and the influencing factors, this paper aims to promote the virtuous cycle of coordinated development between regional agriculture and technology, as well as accelerate the realisation of high-quality development of Chinese agriculture. Therefore, this paper explores the spatial and temporal coupling characteristics of the two using the entropy value method, coupling coordination degree model, and exploratory spatial data analysis, and it screens for important influencing factors using the grey correlation model. The main results show that ① the coupling coordination relationship between agricultural technology innovation and food security in China is at a dissonant stage, but the value of the coupling coordination degree increases from 0.2076 to 0.3437 during the period of study, and the level of coordination gradually improves. ② The degree of coupling coordination in the provincial space exhibits a distribution pattern of "high in the east and low in the west". The areas of high value are primarily situated in the provinces of Shandong, Jiangsu, and other provinces along the southeastern coast of China, while the areas of low value are mainly located in the provinces of Qinghai, Ningxia, and other provinces in inland northwest China. ③ The Moran's index of provincial coupling coordination is greater than 0, showing a certain positive correlation, and there is a significant pattern of spatial aggregation. ④ The correlation coefficients between the influencing factors and the degree of coupling coordination are all greater than 0.35, indicating a moderate or high correlation, but the significance of technological support capacity and food distribution security increased over time. [ABSTRACT FROM AUTHOR]

The new development pattern has identified two key avenues for the sustained advancement of high-quality agricultural and rural development: digitalisation and low-carbon development. The measurement of the digital economy and the agricultural carbon emission performance, and their spatial and temporal heterogeneity, is a crucial step in promoting the spatial coordination and sustainable development of digitalisation and low-carbon agriculture. This paper employs the entropy value method, SBM model, and coupling coordination degree model to investigate the coupling coordination measurement and spatial-temporal heterogeneity of the performance of the digital economy and agricultural carbon emissions. The data used are provincial panel data from 2013 to 2021. The simulation results demonstrate that, between 2013 and 2021, the digital economy of all provinces exhibited varying degrees of growth, yet the development of the digital economy between provinces exhibited a more pronounced tendency to diverge. Concurrently, the agricultural carbon emission efficiency in China exhibited a fluctuating upward trend. The development of the digital economy and the efficiency of agricultural carbon emission were found to be highly coupled. Their coupling and coordination relationship showed a downward trend followed by an upward trend. In general, it is suggested that we should increase investment in digital economy infrastructure and technology, promote digital agricultural applications, strengthen policy guidance and financial support, establish a coupling coordination mechanism and strengthen farmers' digital literacy and environmental awareness. [ABSTRACT FROM AUTHOR]

China is transitioning into the digital economy era. The advancement of the digital economy could offer a fresh mechanism to attain carbon peak and carbon neutrality objectives. Applications of the digital economy, such as smart energy management, intelligent transport systems, and digital agricultural technologies, have significantly reduced carbon emissions by optimizing resource use, reducing energy waste, and improving production efficiency. This research does so by devising a theoretical model that looks into the multi-faceted power of the digital economy under a two-sector paradigm. Utilising a panel model, a mediation effect model and a spatial Durbin model to assess the digital economy's power on carbon emissions. This research has determined that the digital economy can significantly diminish carbon emissions, with green tech innovations and industrial transformation being key contributors. The spatial spillover effect was used for the digital economy to aid in lowering carbon emissions in adjacent districts and upgrading better environmental stewardship. The influence of the digital economy has better performance in lowering carbon emissions in mid-western China than in the eastern area. This paper deepens understanding of the drivers of low-carbon growth and the significance, mechanism and regional disparities of the digital economy's effect on reducing carbon emissions. It offers valuable policy insights and guidance for globally achieving digital economy growth, reducing carbon emissions and reaching carbon peak and neutrality goals. [ABSTRACT FROM AUTHOR]

Based on the panel data of provincial units in China from 2000 to 2020, this paper uses the entropy method to calculate agricultural environmental regulation level in China from the perspectives of afforestation projects, water conservancy projects and environmental protection projects. Then, this paper calculates agricultural non-point source pollutant emissions in China by using the unit survey and evaluation method, and calculates agricultural green productivity growth in China by using the SBM directional distance function and Luenberger productivity index. On this basis, the influence of environmental regulation on agricultural green productivity growth in China and its mechanism are empirically analysed. The results show that:(1) During the sample period, agricultural environmental regulation level and agricultural green productivity growth increased significantly, while the emission density of agricultural non-point source pollution decreased significantly; (2) On the whole, environmental regulation significantly promoted agricultural green productivity growth in China, which was mainly reflected in the promotion of agricultural green technology progress change; (3) Environmental regulation can significantly promote agricultural green productivity growth in China through the channel of agricultural innovation investment. The innovation of this paper lies in the measurement of agricultural environmental regulation, and the analysis of the moderating effect of agricultural innovation investment on the impact of environmental regulation on agricultural green productivity growth in China. The research conclusions of this paper verify the 'Porter Hypothesis' theory in the field of agriculture, and have guiding significance for China to promote agricultural green productivity growth by relying on environmental regulation. [ABSTRACT FROM AUTHOR]

Farmland transfer is a critical component in facilitating agricultural scale management and improving agricultural production efficiency. This study examines the spatial distribution of farmland transfer in China and identifies the factors influencing it, offering valuable guidance for advancing China's farmland transfer practices. Through the application of mathematical statistics and GIS spatial analysis, the study investigates changes in spatial patterns related to the scale, rate, mode, and recipients of farmland transfer across China's 30 provinces from 2015 to 2020. Geographical detectors are also employed to identify the key factors influencing the extent and pace of farmland transfer. The study reveals that between 2015 and 2020, China's farmland transfer area increased from 29,789 to 37,638 million hectares. Provinces with abundant farmland resources generally experienced larger farmland transfers, while economically developed regions and major grain-producing areas saw higher rates of farmland transfers. The predominant mode of farmland transfer in China was leasing (subcontracting), accounting for over 80% of the total transferred area. Large-scale grain growers and family farms were significant participants in farmland transfers, acquiring approximately 60.1% of the transferred lands, followed by professional cooperatives (21.5%), enterprises (10.4%), and other entities (7.9%). Key factors influencing the farmland transfer area include the "regional farmland area", the "proportion of family farms supported by loans", and the "proportion of non-agricultural population", with explanatory powers of 0.663, 0.319, and 0.225, respectively. Notably, there is a substantial interaction between the "regional farmland area" and factors such as the "proportion of family farms supported by loans" and the "grain yield per unit area", with explanatory powers reaching 0.957 and 0.901, respectively. These findings offer valuable insights for promoting farmland transfer in agriculturally rich regions. Factors affecting the farmland transfer rate include "grain yield per unit area", "GDP per capita", and the "proportion of non-agricultural population", each with an explanatory power above 0.500. Moreover, their interactive explanatory powers with other indicators exceed 0.600, indicating that provinces with high agricultural productivity or economic development levels are more likely to undergo farmland transfer. The paper concludes by proposing strategies and recommendations to promote farmland transfer in both "large agricultural areas" and "metropolitan suburbs." [ABSTRACT FROM AUTHOR]

As a new business model, E-commerce brings new changes to the global economy and society. So, can E-commerce development policies promote high-quality agricultural development? This article regards the pilot construction of national e-commerce demonstration cities as a quasi-natural experiment for the development of e-commerce. Based on the E-commerce pilot and economic and social development data of national prefecture-level cities from 2004 to 2018, the agricultural total factor productivity calculated by the Fare-Primont index method is used as the characterization of the quality of urban agricultural development, and an empirical model is constructed under the progressive Differences-in-Differences framework. This paper empirically tests the overall impact of E-commerce development on the high-quality development of agriculture and its sources, analyzes the heterogeneity and dynamics of the impact, and investigates the possible impact mechanism. The result shows that from the overall impact and its sources, the development of E-commerce in cities has a positive impact on the high-quality development of agriculture, and the impact is mainly due to its role in promoting technological innovation and economies of scale. From the perspective of heterogeneity, the larger the population size of a city, the more significant the level of e-conomic development or Internet development. From the perspective of the dynamic impact, the positive impact of e-commerce development becomes more significant over time. With the passage of time, the impact of E-commerce on high-quality agricultural development policies shows a trend of first increasing and then decreasing. Overall, this study provides empirical evidence for the rationality and effectiveness of policies and measures related to E-commerce to promote the high-quality development of agriculture. [ABSTRACT FROM AUTHOR]

The transformation and development of agricultural science and technology park counting intelligence is an important way to accelerate the realization of agricultural modernization. The construction of agricultural science and technology parks in China is still in the primary stage of development. With the continuous breakthrough and integration of digital technology and agricultural technology, agricultural science and technology parks are transforming and developing from the traditional single agricultural science and technology demonstration to the direction of integrated innovation and digital intelligence. At present, China's agricultural science and technology parks are facing the backwardness of agricultural information technology infrastructure, the lack of high-quality agricultural production and management personnel, digital agriculture equipment backwardness, digital services and management mechanisms not perfect and other outstanding problems. The digitalized agriculture machinery and equipment is backward, and the digitalized service management mechanism is imperfect. Therefore, it is necessary to optimize the configuration of digital elements, improve the intelligent facilities and equipment, and innovate the way of digital services. This paper defined the connotation of China's agricultural science and technology park digital intellectual transformation and development, analyzed the current situation and the main problems and explored the main direction of agricultural science and technology park digital intellectual transformation and development. Based on these, it provided theoretical guidance for the transformation and development of agricultural science and technology parks, and provided suggestions and countermeasures for cracking the transformation and upgrading of agriculture and industrial integration. [ABSTRACT FROM AUTHOR]

Currently, the self-sufficiency rate of domestic vegetable oil is still low. As an important oil crop in China, rapeseed contributes to nearly 50% of the oil production of domestic oil crops, and it plays a vital role in ensuring national edible oil supply security. Since the "No. 1 central document" for 2012 first proposed the comprehensive deployment of agricultural science and technology strategy, the rapeseed industry has made great progress with scientific and technological support. The "No. 1 central document" for 2023 clearly proposes to further promote the soybean and oilseed production capacity improvement project, take coordinated steps to support the rapeseed industry, promote rice-oil rotation, and vigorously develop winter idle fields. This paper systematically figured the development status of rapeseed industry from 2012 to 2022, summarized the scientific and technological progress within this sector, and analysed the current challenges and prospects. Finally, policy suggestions were put forward to support the sustainable development of rapeseed industry in China. [ABSTRACT FROM AUTHOR]

The purpose of this work is to investigate the varied effects of China's free trade zone (FTZ) strategy on agricultural trade and its underlying mechanisms. This work utilizes the propensity score matching–staggered difference-in-differences (PSM–Staggered DID) approach and synthetic control method (SCM) as its analysis methods. This study analyzes trade volume data between China and various countries alongside diverse economic indicators spanning from 1995 to 2020. The data sources include CEPII_BACI, the China Free Trade Zone Services website, the Penn World Tables, and the CEPII database. The novelty of this work lies in exploring the multidimensional heterogeneity of agricultural product trade effects in FTZs and their underlying mechanisms and extending the application of causal inference methods to the assessment of FTZs' trade effects. Empirical analysis indicates that the establishment of FTZs with partner countries has contributed to the growth of China's agricultural trade. The effects of agricultural trade resulting from China's FTZ strategy exhibit multidimensional heterogeneity in the aspects of agreement terms, years, product categories, and network positions. Specifically, when it comes to the agreement terms, FTZs negotiated by China with broader scope, deeper terms, and stronger constraints have a more significant impact on agricultural trade due to the establishment of FTZs; in terms of years, the agricultural trade effects have gradually expanded over time; in terms of product categories, China has expanded its imports of primary agricultural products and semiprocessed agricultural products from partner countries, thus augmenting its exports of horticultural agricultural products and processed agricultural products. In terms of network positions, China, as a hub country, has greater agricultural trade effects than partner countries after the establishment of the FTZs. Finally, the paper proposes policy recommendations for optimizing the implementation strategy of FTZs. [ABSTRACT FROM AUTHOR]

Innovations in precision agriculture continue to increase in both number and significance. Contemporaneously, given their expanding scope and application, the growing pool of technologies is increasingly complex. Although some recent attempts have been made, a knowledge gap remains in respect to the evolution of precision agricultural innovation. Synthesized, such knowledge should inform the untapped opportunities for innovation. This paper narrows this gap by conducting a network analysis of patent applications in areas concerning precision agriculture. Spanning the years from 1960 to 2021, the analysis shows an annual average growth in patent applications of 15.1%. During the last decade, this growth is almost entirely attributable to China and the USA. Priority innovation themes have been dynamic. Its phases can be characterized as 'motorized mechanization' (1960–1999), 'mechanical automation' (2000–2009), 'digital mechanization' (2010–2019), and 'digital automation' (2020–2021). The significance of information communication technology has grown in association with other innovation clusters, but a lag time has persisted in introducing innovations based on such technologies. Opportunities are ripe for speeding transference through economic and other incentives. [ABSTRACT FROM AUTHOR]

Purpose: Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology. Design/methodology/approach: This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models. Findings: The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices. Practical implications: Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos. Originality/value: This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE. [ABSTRACT FROM AUTHOR]

Prefabricated dishes are an effective carrier for the foodization of agricultural products, which is an industry that is gradually moving towards a trillion-level market scale, playing an important role in ensuring food security. The prefabricated dishes industry develops modern agriculture with the concept of industrialization, promotes the further agglomeration and development of upstream and downstream supporting enterprises in the agricultural industry chain, which is the link connecting the primary, secondary and tertiary industries and the endogenous driving force to promote their innovation and development, and is an important bridge connecting the integrated development of multiple industrial chains such as production and sales between rural and urban areas. This paper introduced the development status of the prefabricated dishes industry, analyzed the problems facing by the prefabricated dishes, predicted the future development trend, and made a suggestion for the future development of the prefabricated dishes industry, so as to provide reference for the healthy and sustainable development of the prefabricated dishes industry. [ABSTRACT FROM AUTHOR]

As part of sustainable agricultural innovations and the alternative food movement, agroecology provides important tools to achieve the sustainable development goals (SDGs). Yet very few existing studies have explicitly addressed their linkages. Synergies among the SDGs are often examined at the national level, overlooking nuanced opportunities revealed by small agroecology initiatives at the local scale. Based on literature review, field visits and semi-structured interviews with farms and relevant organizations in China, this research investigates how locally embedded agroecology practices lead to advancement of multiple SDG targets and facilitate the synergies among the SDGs. It also highlights their motivations, achievements, and challenges. We argue that the technocentric metrics of SDGs underappreciate the application of traditional knowledge and small-scale low-tech innovations. By bringing visibility to low-tech and small agroecology initiatives, this paper advocates for stronger inclusion of grassroots agroecology initiatives in SDG discussions among researchers and policy makers. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep development of digital finance can contribute to the optimization and transformation of the rural industrial structure. The research further explores the particular effects of this financial transformation in the central and western regions of China. Design/methodology/approach: This research studies the influence of digital finance on rural industrial integration across 30 Chinese provinces from 2011 to 2020. Utilizing the entropy weight method, a comprehensive evaluation index system is established to gauge the level of rural industrial integration. A two-way fixed effects model, intermediary effect model, and threshold effect model are employed to decipher the relationship between digital finance and rural industrial integration. Findings: Findings reveal a positive relationship between digital finance and rural industrial integration. A single threshold feature was identified: beyond a traditional finance development level, the marginal effect of digital finance on rural industrial integration increases. These effects are more noticeable in central and western regions. Originality/value: Empirical outcomes contribute to policy discourse on rural digital finance, assisting policymakers in crafting effective strategies. Understanding the threshold of traditional finance development provides a new perspective on the potential of digital finance to drive rural industrial integration. [ABSTRACT FROM AUTHOR]

The adoption of green control technologies in agriculture is an important approach to ensure the quality and safety of agricultural products, address agricultural pollution from its source, and promote increased productivity and income in agriculture, thereby driving high-quality agricultural development. This paper is based on production and operation data from 2,155 tea farmers in 16 major tea-producing provinces in China. Using an endogenous transformation model from the perspective of the value chain, it empirically analyzes the impact of adopting green control technologies on tea farmers' income and draws three conclusions. First, the adoption of green control technologies significantly promotes income growth for tea farmers. Second, the awareness of tea farmers regarding pesticide residue limits and the exchange of pest control techniques among tea farmers significantly enhance the adoption of green control technologies. Third, the income effects of adopting green control technologies differ across different stages of the value chain, with the income growth in the cultivation stage being lower than that in the processing and marketing stages. Finally, based on the analysis and relevant research by scholars, four targeted suggestions are proposed: (1) Increase efforts to promote the adoption of green control technologies and enhance farmers' willingness to adopt them. (2) Promote education and training on green control technologies for tea farmers. (3) Ensure fair distribution of benefits along the agricultural value chain. (4) Strengthen the promotion of green control technologies at the market and consumer end. [ABSTRACT FROM AUTHOR]

Education plays a crucial role in promoting green development by shaping environmentally friendly production behaviors and fostering low-carbon lifestyles. This research examines the impact of China's free compulsory education (FCE) policy on agricultural green total factor productivity (AGTFP) using provincial panel data from 2002 to 2015. Additionally, it explores the impact mechanisms and regional heterogeneity. The results indicate that first, the FCE policy has a significantly positive effect on AGTFP, as confirmed through a series of robustness tests. Second, the FCE policy primarily influences AGTFP by increasing farmers' awareness of green production and promoting the development of green technologies in agriculture. Third, the impact of the FCE policy varies across regions. It promotes green technologies in agriculture in developed provinces and fosters ecological awareness among farmers in less developed provinces. These findings offer valuable empirical evidence and policy implications for implementing education popularization projects and reducing agricultural carbon emissions in developing countries. [ABSTRACT FROM AUTHOR]

Climate change poses an urgent threat, necessitating the implementation of measures to actively reduce carbon emissions. The development of effective carbon emission reduction policies requires accurate estimation of the costs involved. In situations where actual prices of commodities are not available in the market, shadow pricing provides a useful method to calculate relative prices between commodities with and without price information. However, most studies focus on the industry, with few contributions on agricultural sector. This paper estimates the shadow price of carbon emissions in the agricultural sector from a provincial perspective, incorporating the impact of livestock into the calculation of carbon emissions and shadow pricing. Our findings indicate that ignoring livestock may overestimate CSP values. On the whole, the level of carbon shadow price is rising, indicating good green development in China's agricultural sector. The two types of convergence results show that there is sigma convergence and beta convergence in the western and central regions, demonstrating a significant improvement in environmental performance. [ABSTRACT FROM AUTHOR]

Rapid urbanization negatively affects the eco-land. The topic of accurate zoning and control of ecological space has become a challenge for many countries. This paper uses the idea of ESP to delineate the control system of China's coastal area. First, three types of ecological sources were identified from the aspects of landscape functions' importance, landscape sensitivity, and landscape connectivity. Then, ecological corridors and nodes were identified using the model of minimum cumulative resistance (MCR) based on the resistance surface. Finally, an ecological control zoning system was constructed by using a "bottom-up" transmission mechanism. The results show that: (1) Most of the landscape function-oriented sources and connectivity-oriented sources are located in the south, where habitat quality is superior. Urban construction and agricultural production are the main threat factors to sensitivity-oriented sources. (2) 81.24% of ecological corridors are reticulated, indicating good structural connectivity, and 11 fragile corridors should be specially protected. (3) Among the three second-level of strictly protected areas, the percentage of restoration area and landscape structure maintenance area are 40.19% and 28.47%, indicating the high threat to eco-land and low landscape connectivity; measures are needed to enhance eco-connectivity and increase the resilience of eco-lands. The research constructs a point-line-plane integrated ecological control zoning system, which can provide a scientific basis for the spatial prioritization of coastal ecological protection in China's coastal areas. [ABSTRACT FROM AUTHOR]

China has to perform high-intensity and high-chemical input agricultural production to improve its food security, which has caused uncertainty in the development of ecological agriculture. This study utilizes bibliometrics and spatial statistical methods to examine the representative literature on ecological agriculture published in the CNKI database from 2012 to 2023. The findings reveal that keywords such as rural revitalization, modern agriculture, and ecological tourism are frequently mentioned while emerging interests include carbon neutrality, eco-circular agriculture, and industrial integration. The main clusters of keywords can be classified into specific practical research, general studies, and countermeasures orderly. The themes of ecological tourism, developing mode, and rural revitalization have attracted long-lasting concerns in research over the past decade. Spatial statistical analysis indicates that, aside from the Eastern coastal areas, most provinces in China exhibit insufficient collaboration and limited spill-over effects in research of ecological agriculture, highlighting the necessity for enhanced integration. This study also provides recommendations to address the prevailing challenges to food security through the promotion of ecological agriculture in China. [ABSTRACT FROM AUTHOR]

• Explain the economic value of the quadratic cost of MECM in terms of marginal cost and elasticity. • Adopt an opinion modification mechanism based on social network. • The MECMs with uncertain adjustment costs are developed under three uncertain scenarios. • The proposed models are applied to the agricultural insurance premiums subsidy policymaking in China. In the realm of group decision making (GDM), the maximum expert consensus model (MECM) emerges as a potent tool for consensus optimization. The complexity of decision-making environment leads to the uncertainty of adjustment costs and the intricate social relationships between decision makers (DMs). Therefore, this paper aims to develop the MECM that integrates both social relationships and uncertain adjustment costs to support social network group decision making (SNGDM) problems. Specifically, we propose a MECM with quadratic cost that can more accurately reflect DMs' sensitivity for opinion adjustment. Additionally, we adopt an opinion modification mechanism based on the information obtained from the social network. The paper also develops the robust MECM (RMECM) to handle the uncertainty of the unit adjustment cost under three uncertain scenarios. Finally, the efficiency of the proposed models is demonstrated by applying them to the agricultural insurance premiums subsidy policymaking in China, further substantiated by sensitivity analysis and comparative analysis showcasing their robust performance. [ABSTRACT FROM AUTHOR]

• Adopting ecological agricultural technologies is an effective way to achieve sustainable agriculture. • The ecological effect of digital economy empowerment should be emphasized. • We analyze how farmers' participation in the digital economy affects their adoption of ecological agricultural technologies. • The treatment effect model is used to address the endogeneity issue. • Farmers' participation in the digital economy can promote ecological agricultural technologies adoption. Adopting ecological agricultural technologies (EATs) is an effective way to guarantee food security and protect the environment. With the advancement of the digital village strategy, the continuous integration of the digital economy with the rural economy has gradually become an emerging driving force for sustainable agriculture. However, few studies have examined the impact of farmers' participation in the digital economy in different links of the agricultural industry chain on EATs adoption from a micro perspective. Using data from 2,825 grain farmers from the 2020 China Rural Revitalization Survey, this paper applies the treatment effect model and the mediating effect model to empirically analyze the impact and mechanism of participation in the digital economy on farmers' EATs adoption from an ecological effect perspective. This paper characterizes farmers' participation in the digital economy in terms of digital production, digital sales, and digital finance. The results show that participation in the digital economy significantly promotes farmers' EATs adoption. The sub-dimensional test found that participation in digital production, digital sales, and digital finance significantly promotes farmers' EATs adoption. The above findings remain robust after a series of robustness tests, such as changing the estimation method and replacing the dependent variable. Mechanism analysis shows that participation in the digital economy, especially digital sales and digital finance, could promote farmers' EATs adoption by increasing the demand for agricultural machinery services, improving information availability, and enhancing food safety cognition; participation in the digital production could promote farmers' EATs adoption by increasing the demand for agricultural machinery services. Results of heterogeneity analysis show that the promotion effect of participation in the digital economy on EATs adoption is more substantial among farmers with higher digital literacy and larger cultivated land scales. The findings of this paper provide insights for China and other countries to effectively use digital technology to promote sustainable agriculture under the pressure of achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

Efficient allocation of agricultural scientific and technological talents (ASTTs) is crucial for agricultural innovation and economic development. This study aims to systematically evaluate ASTTs' allocation efficiency in provincial agricultural research institutions in China, aiding decision-making for local governments and research bodies. Utilizing data from 2009 to 2019 across 31 provinces, an output-oriented data envelopment analysis model measures ASTTs' allocation efficiency and analyzes its trends, regional differences, and spatial characteristics. Results show: (1) Provincial ASTTs' mean comprehensive technical efficiency (CTE) in China was 0.786, with room for improvement. (2) Enhanced CTE was driven by scale efficiency improvements, while pure technical efficiency declined, indicating a need for better management systems and technology applications. (3) Disparities in ASTTs' allocation efficiency among provinces decreased, with higher efficiencies in the East and Central-Southern China regions. At the provincial level, areas like Jiangsu, Shandong, Henan, and Sichuan demonstrated relatively high ASTTs allocation efficiencies. (4) Spatial agglomeration of ASTTs' allocation efficiency was localized in a few major agricultural provinces without a significant overall effect. These findings advocate for further optimization of ASTTs' regional layout and management mechanisms in China. [ABSTRACT FROM AUTHOR]

Introduction: This study delves into the intricate dynamics between fiscal policies supporting agriculture and the non-linear influence of agricultural science and technology innovation on enhancing agricultural resilience. We conducted research across 31 provinces (including autonomous regions and municipalities) in China from 2007 to 2021. Method: By constructing the evaluation index system of agricultural resilience, the entropy value method is used to measure the value of agricultural resilience, and then standard deviation ellipse and center of gravity migration analysis, benchmark regression model, heterogeneity analysis, threshold regression model are used to analyze the relationship between agricultural science and technology innovation, fiscal policies supporting agriculture and agricultural resilience. Result: (1) The analysis of the spatio-temporal evolution trend shows that the overall development of China's agricultural resilience is relatively stable, the resilience range is expanding, and the geographical area with the southeast as the center of gravity presents a stronger pulling effect; (2) The benchmark regression model shows that agricultural science and technology innovation has a significant positive effect on agricultural resilience; (3) Agricultural science and technology innovation plays a nonlinear role in increasing agricultural resilience when fiscal policies supporting agriculture are used as a threshold variable. (4) Heterogeneity analysis highlights stronger promotion of agricultural resilience through science and technology innovation in non-main producing areas and economically underdeveloped regions. Discussion: To address this, policymakers should leverage the resilience of the Southeast, boost innovation capacity, tailor innovation to local needs, and reinforce fiscal policies supporting agriculture. These insights provide valuable direction for policymakers in crafting effective measures to enhance agricultural resilience. [ABSTRACT FROM AUTHOR]

Agricultural green production technology (AGPT) is essential for the sustainable development of agriculture, yet adoption rates among farmers are often low due to limited access to education and information. Based on the extended technology acceptance model, this study takes Liaoning, a major agricultural province in China, as a representative region to explore how digital multimedia influences the adoption of AGPT by farmers. The findings show that the perceived ease of use of these technologies significantly enhances farmers' intentions to adopt, while perceived risks detract from these intentions. Although digital multimedia effectively promotes AGPT by improving its perceived ease of use and usefulness, its role in mitigating perceived risks is minimal. Based on these results, we recommend that the government improve the quality of information on digital platforms by involving experts in the field and offer specific digital marketing training to potential users to increase the adoption of sustainable agricultural technologies. [ABSTRACT FROM AUTHOR]

The accurate prediction of crop yields is crucial for enhancing agricultural efficiency and ensuring food security. This study assesses the performance of the CNN-LSTM-Attention model in predicting the yields of maize, rice, and soybeans in Northeast China and compares its effectiveness with traditional models such as RF, XGBoost, and CNN. Utilizing multi-source data from 2014 to 2020, which include vegetation indices, environmental variables, and photosynthetically active parameters, our research examines the model's capacity to capture essential spatial and temporal variations. The CNN-LSTM-Attention model integrates Convolutional Neural Networks, Long Short-Term Memory, and an attention mechanism to effectively process complex datasets and manage non-linear relationships within agricultural data. Notably, the study explores the potential of using kNDVI for predicting yields of multiple crops, highlighting its effectiveness. Our findings demonstrate that advanced deep-learning models significantly enhance yield prediction accuracy over traditional methods. We advocate for the incorporation of sophisticated deep-learning technologies in agricultural practices, which can substantially improve yield prediction accuracy and food production strategies. [ABSTRACT FROM AUTHOR]

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. • The internal mechanism of rebound effect is expounded from the view of producers and consumers. • The average energy efficiency of China's agricultural energy consumption was 68.9 % during 1999–2020. • The determinants of the agricultural energy rebound effect were further discussed by considering the spatial spillover effect. [ABSTRACT FROM AUTHOR]

Agricultural scientific and technological innovation and rural industry integration are the key contents of promoting agricultural and rural modernization in China. This study empirically analyzed the matching relationship between the two and its influencing factors, and found that the matching degree between agricultural scientific and technological innovation and rural industry integration in China showed a steady upward trend in the sample period. Both China as a whole and all regions completed the upgrading from moderate to high matching in the sample period, The performance of each region is also excellent. In 2020, the matching degree of 28 regions will enter a high matching range. The implementation of the rural revitalization policy will help to improve the matching degree between China's agricultural scientific and technological innovation and rural industrial integration. The scale of rural financial development and the matching degree of lagging one period also have a significant positive impact on the improvement of the matching degree. This study further proposes relevant policy recommendations from improving the supply level of agricultural scientific and technology innovation, enhancing the adaptability between supply and demand of agricultural scientific and technology innovation, improving the policy support system, and optimizing the financial security system. [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) is a reliable measure of the carbon sink potential of terrestrial ecosystems and is an essential element of terrestrial carbon cycle research. This study employs the diffuse fraction-based two-leaf light-use efficiency (DTEC) model to imitate China's monthly GPP from 2001 to 2020. We studied the trend of GPP, investigated its relationship with climatic factors, and separated the contributions of climate change and human activities. The findings showed that the DTEC model was widely applicable in China. During the study period, China's average GPP increased significantly, by 9.77 g C m−2 yr−1 (p < 0.001). The detrimental effect of aerosol optical depth (AOD) on GPP was more widespread than that of total precipitation, temperature, and solar radiation. Areas that benefited from AOD, such as Northwest China, experienced significant increases in GPP. Climate change and human activities had a primary and positive influence on GPP during the study period, accounting for 28% and 72% of the increase, respectively. Human activities, particularly ecological restoration projects and the adoption of advanced agricultural technologies, played a significant role in China's GPP growth. China's afforestation plan was particularly notable, with the GPP increasing in afforestation areas at a rate greater than 10 g C m−2 yr−1. This research provides a theoretical foundation for the long-term management of China's terrestrial ecosystems and helps develop adaptive ecological restoration tactics. [ABSTRACT FROM AUTHOR]

Eco-agricultural technology is crucial in alleviating agricultural resource scarcity and environmental pressures. However, financial constraints affect its successful promotion. Digital finance significantly impacts farmers. However, existing research neglects the impact of digital finance on farmers' adoption of eco-agricultural technology. This study focuses on rice-crayfish co-cultivation technology. It utilizes survey data from 1063 households in China. An endogenous switching probit model is employed to solve self-selection bias. The results are as follows: First, the average treatment effect is 51.5%. This indicates that if farmers who use digital finance were to stop using it, the probability of adopting rice-crayfish co-cultivation technology would decrease by 51.5%. Therefore, digital finance is beneficial for farmers in adopting this technology. Second, heterogeneity analysis shows that the promoting effect of digital finance is a greater promoting effect on older farmers, and on those with lower education levels and higher proportions of agricultural income. This suggests a greater reliance on digital financial services among vulnerable groups. Third, digital finance promotes farmers' adoption of rice-crayfish co-cultivation technology by alleviating financial constraints, expanding information channels, and increasing social capital accumulation. Overall, the findings offer valuable insights for formulating supportive eco-agricultural policies. [ABSTRACT FROM AUTHOR]

Based on a large national sample of the China Family Panel Studies (CFPS) database, the study will to provide some thoughts and suggestions for the transformation and upgrading of China's agriculture, the enhancement of total factor productivity by exploring the agricultural production efficiency from the micro-farmers' perspective. By constructing the models of Charnes, Cooper & Rhodes (CCR), Banker, Charnes & Cooper (BCC), Slacks-Based Model (SBM) and technology optimization Malmquist-Luenberger index, it finally obtained the comprehensive technical efficiency value, pure technical efficiency value, farm household efficiency value and green total factor productivity level value at the micro-farm household level based on the comparative analysis. It was found that: the comparison of the measures based on different models found that although there are differences in the calculated efficiency values, the pure technical efficiency values calculated by BCC are the main factors affecting the micro agricultural production efficiency values at the farmer level, the SBM model should optimize the CCR, BCC models, and more suitable for Chinese government policy formulation and optimization; the technology optimization Malmquist-Luenberger index method is the micro agricultural production efficiency measurement method of choice, with the characteristics of diverse model selection, rich application scenarios and convenient processing of negative outputs; environmental factors in the current evaluation of agricultural green total factor productivity, mainly play a negative inhibitory role, reducing the negative externalities of environmental variables output, become one of the key issues facing the current micro farm layer green total factor production enhancement; the combination of subjective and objective measures of environmental non-desired output is an important way to measure environmental factors of agricultural green total factor productivity, it can be used in practical applications based on a combination of research objectives and data availability. [ABSTRACT FROM AUTHOR]

Eradicating poverty and improving human well-being are pivotal objectives for achieving global sustainable development. Sustainable agriculture, as a key domain, plays a crucial role in addressing poverty. However, to date, there remains insufficient research on the specific impact of agricultural green development on poverty. To bridge this gap, we utilize panel data from 273 prefecture-level cities in China from 2006 to 2022 to explore how agricultural green development affects poverty based on constructing a regional multidimensional poverty index and an index of green agriculture. Our study reveals that agricultural green development effectively reduces poverty, particularly in regions of deep poverty and the eastern part of China. Further mediating analysis indicates the alleviation of poverty by agricultural green development through the infrastructure, the industrial structure, and the green technology innovation effect. Our findings offer valuable insights for informing policies on agricultural green development and poverty reduction, as well as for improving government resource allocation and strengthening resilience in impoverished areas. By deepening our understanding of the link between green agriculture and poverty, this research significantly contributes to global agricultural sustainability and expedites poverty eradication worldwide. [ABSTRACT FROM AUTHOR]

The adoption of soil and water conservation (SWC) technology is a key strategy for reducing global land degradation and improving agricultural productivity. This study uses survey data from households in the Loess Plateau in 2017 to evaluate the impact of social interaction on the decision-making process of SWC adoption by farmers. It measures the mediating effect of information acquisition and the moderating effect of internet use and deploys the probit model, general decomposition (KHB) model, and moderated effect model for analysis. The study found that the level of SWC adoption by farmers in the Loess Plateau of China remains relatively low, with only 57.3% of farmers adopting SWC, whereas social interaction increases the possibility of farmers adopting SWC by 10.0%. Accordingly, the paper argues that social interaction can encourage farmers to adopt SWC by improving their ability to acquire information, while internet use can positively moderate the impact of social interaction on farmers' adoption of SWC. Furthermore, the study found the positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies. Therefore, the research results provide a new perspective for promoting SWC in China, emphasizing the importance of enhancing social interaction improving farmers' ability to acquire information, and accelerating internet use. • Social interaction plays a crucial role in promoting SWC adoption. • Improving farmers' ability to acquire information can promote SWC adoption. • Internet use can moderate the impact of social interaction on SWC adoption. [ABSTRACT FROM AUTHOR]

To achieve the goals of carbon peaking and carbon neutrality, China is actively promoting carbon reduction in many areas. Agriculture is one of the main sources of greenhouse gas emissions, and promoting the development of low-carbon agriculture is a critical way to achieve carbon reduction targets. Taking Chongming District in Shanghai as an example, this study summarizes the experience of low-carbon agricultural development in Chongming and analyzes the problems and challenges faced during its development. Finally, based on the system dynamics method, the causal relationship of carbon emission in Chongming's agricultural development is constructed, and feasible loop optimization suggestions are put forward. [ABSTRACT FROM AUTHOR]

This research aims to investigate the average and heterogeneous impacts of digital agricultural technology extension service use on eco-efficiency among 1302 maize-producing farmers from a major maize-producing area in Northeast China in 2022. The slack-based measure model with undesirable outputs is applied to calculate the eco-efficiency of maize production. To obtain an unbiased estimation of the average effect, the self-selection problem generated by observable and unobservable factors is solved by the endogenous switching regression model. Quantile regression is utilized to analyze the heterogeneous effect. Notably, the mediated effects model is utilized to examine the potential mechanism between them. Our findings indicate that digital agricultural technology extension service use can increase maize production's eco-efficiency. Digital agricultural technology extension service users would have reduced the eco-efficiency of the service by 0.148 (21.11%) if they had not used it. Digital agricultural technology extension service nonusers would have improved the eco-efficiency of the service by 0.214 (35.20%) if they had used it. The robustness check reconfirms the results. Moreover, digital agricultural technology extension service use is more helpful for maize farmers who have lower eco-efficiency than those who have higher eco-efficiency. Digital agricultural technology extension service use can improve the eco-efficiency of maize production through the application of organic fertilizers, green pesticides, and biodegradable agricultural films. There are policy implications of these findings: there is an argument for using the publicity of the digital agricultural technology extension service to encourage farmers to use sustainable inputs; additionally, it might be worthwhile to implement a categorized promotion strategy based on the different real-world situations. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR). Design/methodology/approach: This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice. Findings: The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%. Originality/value: To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector. [ABSTRACT FROM AUTHOR]

Agricultural technology adoption is an important way to improve agricultural technology and production efficiency and promote agricultural modernization. However, the low willingness to adopt agricultural technologies has been a challenge in China. Cognitive load may affect smallholder farmers' decision to adopt new technologies. Using an experimental economics approach, we examine the effect of cognitive load on smallholder farmers' willingness to adopt technology from a cognitive perspective based on a field experiment with 440 smallholder farmers in Shaanxi Province, China, in 2021 and 2022. The experimental results show that cognitive load has a significant negative effect on farmers' willingness to adopt technology, and the higher the level of cognitive load, the lower the farmers' willingness to adopt the technology. From the mechanism of action, cognitive load influences smallholder farmers' technology adoption intention by consuming their attention. In addition, cognitive ability, technology training, and government subsidies had heterogeneous effects on cognitive load affecting farmers' willingness to adopt new technologies, i.e., the cognitive load had less inhibitory effects on technology adoption willingness of smallholder farmers who has the high cognitive ability, participated in technology training and received government subsidies. Therefore, in the context of rural revitalization, the Chinese government should pay attention to the influence of farmers' cognitive mechanism on their willingness to adopt agricultural technologies, improve their cognitive ability, provide more technical training guidance, and provide targeted subsidies, to guide farmers to actively adopt new technologies and get rid of the "poverty trap". [ABSTRACT FROM AUTHOR]

In a world grappling with the overuse of pesticides, China emerges as a key consumer and producer, facing substantial challenges in environmental and agricultural sustainability. This study investigates how agricultural services can foster eco-friendly pesticide use among farmers. It leverages data from the 'China Land Economic Survey' (2020-2021) by Nanjing Agricultural University, covering 52 villages and 2600 households. Using a multi-dimensional fixed effects model and propensity score matching, the research addresses biases inherent in the data. Results show that agricultural business services significantly boost green pesticide adoption, outperforming agricultural technology and input sectors. These services increase the use of safer pesticides and the recycling of their containers by 11.6% and 6%, respectively. Farmer satisfaction and regular internet use also play a role in reinforcing this trend. Based on these insights, it recommends enhancing support for low-toxicity pesticides and recycling programmes, creating tailored policies for diverse agricultural needs, and implementing resource management and incentive mechanisms to promote sustainable practices. These strategies aim to bolster sustainable agriculture, balancing environmental health with economic viability. [ABSTRACT FROM AUTHOR]