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Comprehensive accounting of carbon emissions and carbon sinks in the agricultural sector is crucial for China to achieve its carbon neutrality goal as early as possible. This paper develops a comprehensive and scientific accounting system to recalculate China's agriculture sector's carbon emissions and sinks from 1995 to 2020, taking into account both resource inputs and productive activities. Subsequently, the STIRPAT model is employed to predict alterations in carbon emissions and sinks across different scenarios. The results show that energy consumption, chemical inputs, and farmland soil management have surpassed livestock and poultry breeding as the main contributors to agricultural carbon emissions. Furthermore, this paper classifies 31 provinces in China into five distinct types based on the variations in agricultural carbon emissions and carbon sinks. These types include carbon sink-dominated regions, paddy planting-dominated regions, livestock farming-dominated regions, resource inputs-dominated regions, and composite factor-dominated regions. In addition, the extent of agricultural technology and the magnitude of agricultural development are the key factors impacting China's agricultural carbon emissions and carbon sinks, respectively. Prior to 2045, agricultural carbon emissions must be directly reduced as much as possible, and their source must be controlled; following that year, the role of carbon sequestration will become more prominent, and the active development of agricultural carbon sinks will be more beneficial in achieving agricultural carbon neutrality. [ABSTRACT FROM AUTHOR]

Based on the monthly panel data of China's imports of agricultural machinery products from 2016–2022, this paper uses a multi-period double-difference model to assess the impact of China's imposition of counter-tariffs on China's imports of agricultural machinery in the context of U.S.–China trade friction. It is found that China's implementation of counter-tariffs significantly reduces China's imports of agricultural machinery products from the U.S. and significantly increases imports from 16 other countries, but the trade diversion effect is lower than the trade suppression effect. Mechanism analysis finds that China–U.S. trade friction affects the technological innovation capacity of agricultural machinery enterprises and the degree of uncertainty in the Chinese economy, which in turn affects China's agricultural machinery imports. Heterogeneity analysis finds that China–U.S. trade friction has a more significant inhibitory effect on seeding and planting and fertilizing machinery, drainage, irrigation, and water lifting machinery, and other machinery imported from the U.S., and a more significant diversionary effect on agricultural primary processing machinery and harvesting machinery imported from 16 other countries. The imposition of countervailing tariffs mainly affected imports of complete machinery products rather than machinery spare parts. [ABSTRACT FROM AUTHOR]

Genomic editing technologies are developing rapidly, promising significant developments for biomedicine, agriculture and other fields. In the present investigation, we analyzed and compared the process of innovation for six genomic technologies: viral vectors, RNAi, TALENs, meganucleases, ZFNs and CRISPR/Cas including the profile of the main research institutions and their funders, to understand how innovation evolved and what institutions influenced research trajectories. A Web of Science search of papers on viral vectors RNAi, CRISPR/Cas, TALENs, ZFNs and meganucleases was used to build a citation network of 16,746 papers. An analysis of network clustering combined with text mining was performed. For viral vectors, a long-term process of incremental innovation was identified, which was largely publicly funded in the United States and the European Union. The trajectory of RNAi research included clusters related to the study of RNAi as a biological phenomenon and its use in functional genomics, biomedicine and pest control. A British philanthropic organization and a US pharmaceutical company played a key role in the development of basic RNAi research and clinical application respectively, in addition to government and academic institutions. In the case of CRISPR/Cas research, basic science discoveries led to the technical improvements, and these two in turn provided the information required for the development of biomedical, agricultural, livestock and industrial applications. The trajectory of CRISPR/Cas research exhibits a geopolitical division of the investigation efforts between the US, as the main producer and funder of basic research and technical improvements, and Chinese research institutions increasingly leading applied research. Our results reflect a change in the model for financing science, with reduced public financing for basic science and applied research on publicly funded technological developments in the US, and the emergence of China as a scientific superpower, with implications for the development of applications of genomic technologies. [ABSTRACT FROM AUTHOR]

The Republic of Moldova has made significant strides in adopting organic farming practices, supported by government subsidies and strategic focus on market demand. This paper aims to analyze the economic performance of organic farms in Moldova and their impact on the sustainable development of the agricultural sector, using primary data collected from 63 organic farms benefiting from subsidies between 2020 and 2022. The agricultural sector in Moldova has experienced a gradual increase in cultivated land, with a noteworthy 9.5% dedicated to organic farming. Economically, farmers have seen substantial growth in income per hectare, credited to favorable climatic conditions and advanced technologies. Although organic farming contributes significantly, constituting approximately one-third of total income, conventional agriculture remains the primary contributor with two-thirds. The impact of subsidies from the National Fund for Agricultural and Rural Development is evident in farm development, as calculated profits per one lei of subsidy have surged from 1.51 to 10.43 lei in 2022. This underscores the effectiveness of government support in fostering growth and development within Moldova's agricultural sector, emphasizing a positive trajectory for sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

This paper explores to evaluate how Pakistan's agriculture is affected by climate change and to find techniques to mitigate and adapt to the changes. Pakistan's agriculture industry is drastically affected by climate change. The continuous inclination of temperature, shifting weather patterns, and more frequent climate change events are remarkably reducing crop yields, compromising food security and posing serious threats to rural livelihood. In order to evaluate the effects of climate change on agricultural output, water resources, and controlling pests, this study sought farmers in liable areas, reviewed a variety of literature in detail, and examined climate data. The paper also founds critical declines in crop yields, changes in developing seasons, and expanded irritation and sickness pressure. Farmers were observed using more groundwater, which resulted in a shortage of water and less fertile land. Pakistan needs to prioritize climateresilient agricultural techniques, raise farmer awareness and capacity building, improve water management, and encourage crop variety to ensure agricultural sustainability. [ABSTRACT FROM AUTHOR]

In the European agri-food sector, operators with substantial bargaining power often engage in unfair trading practices (UTPs). Our paper aims to empirically examine the occurrence of UTPs and their influence on the performance of cooperatives. To fulfill the goal of our paper, we collected responses from 109 cooperatives in Greece after the transposition of a specialized EU Directive (i.e., Directive (EU) 2019/633). We found that, on average, the sampled cooperatives encountered three prohibited ("black") UTPs, while all reported at least one prohibited UTP. Moreover, the two most commonly reported practices (i.e., "unduly late payments" and "buyers' demand that suppliers pay for the deterioration or loss of products that occurred after ownership transfer") exerted a significant negative influence on cooperative performance, even in the presence of a proficient Board of Directors. Consequently, policymakers may need to pay more attention to UTPs and ensure that the national enforcement authorities are well-equipped to act rapidly and effectively against offenders. [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]

The interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current utilization of ML and DL in agricultural research, with a pronounced emphasis on agroclimatic impacts and adaptation strategies. Our investigation reveals a dominant reliance on conventional ML models and uncovers a critical gap in the documentation of methodologies. This constrains the replicability, scalability, and adaptability of these technologies in agroclimatic research. In response to these challenges, we advocate for a strategic pivot toward Automated Machine Learning (AutoML) frameworks. AutoML not only simplifies and standardizes the model development process but also democratizes ML expertise, thereby catalyzing the advancement in agroclimatic research. The incorporation of AutoML stands to significantly enhance research scalability, adaptability, and overall performance, ushering in a new era of innovation in agricultural practices tailored to mitigate and adapt to climate change. This paper underscores the untapped potential of AutoML in revolutionizing agroclimatic research, propelling forward the development of sustainable and efficient agricultural solutions that are responsive to the evolving climate dynamics. [ABSTRACT FROM AUTHOR]

The development of alternative soil tillage technologies, which ensure the conservation and maintenance of its productive capacity as well as the reduction of energy consumption per unit of processed area, is today a necessity in developing a sustainable agriculture. The study presented in this paper was carried out in the area of Oravița, Caraş-Severin County, Romania, and refers to the minimum tillage technology in wheat culture. The study points to the unfavourable effect of intensive soil works -- classic (conventional) system -- on soil erosion. This has led to the development of some research oriented towards new technologies of soil working in the conservation system. The purpose of this paper is to promote the introduction of alternative technologies in agricultural works, by dealing with the main technical, economic and environmental aspects that compete for the achievement of efficient agriculture. From an economic point of view, this method is less expensive because fuel consumption and machine working time are reduced. The use of modern mechanization technologies has a great economic efficiency due to the following aspects. [ABSTRACT FROM AUTHOR]

Modern and precision agriculture is constantly evolving, and the use of technology has become a critical factor in improving crop yields and protecting plants from harmful insects and pests. The use of neural networks is emerging as a new trend in modern agriculture that enables machines to learn and recognize patterns in data. In recent years, researchers and industry experts have been exploring the use of neural networks for detecting harmful insects and pests in crops, allowing farmers to act and mitigate damage. This paper provides an overview of new trends in modern agriculture for harmful insect and pest detection using neural networks. Using a systematic review, the benefits and challenges of this technology are highlighted, as well as various techniques being taken by researchers to improve its effectiveness. Specifically, the review focuses on the use of an ensemble of neural networks, pest databases, modern software, and innovative modified architectures for pest detection. The review is based on the analysis of multiple research papers published between 2015 and 2022, with the analysis of the new trends conducted between 2020 and 2022. The study concludes by emphasizing the significance of ongoing research and development of neural network-based pest detection systems to maintain sustainable and efficient agricultural production. [ABSTRACT FROM AUTHOR]

In the analysis of agricultural product price time series, the detection of abnormal fluctuations is the primary task. Accurately judging the abnormal fluctuations of agricultural product prices can help farmers avoid potential economic losses in a timely manner and improve the circulation efficiency of agricultural products. This paper introduces a convolutional neural network (CNN) classification model based on time series images (TSI), and identifies abnormal fluctuations in agricultural product prices using improved standard deviation–slope judgment. First, a standard deviation–slope (SDS) time series abnormal fluctuation criterion is proposed. Second, the Markov Transfer Field (MTF) method is used to convert the sparse one-dimensional time series of agricultural product prices into a two-dimensional dense image. Third, the CNN model is used to automatically extract features from time series images containing abnormal fluctuations, and they are divided into two categories: "normal" and "abnormal"; Finally, the performance of the proposed model was evaluated using China's corn and wheat price dataset. Comparing with other abnormal fluctuation judgment methods, the accuracy of the proposed algorithm is about 20% higher on average. This confirms the applicability of the standard deviation–slope time series Image-Resnet-34 (SDS-TSI-Resnet34) model in practical scenarios. At the end of the paper, some feasible suggestions for the efficient development of agricultural economy are proposed based on the abnormal fluctuation judgment method. [ABSTRACT FROM AUTHOR]

This paper aims at analyzing the research productivity and scientific knowledge discovery of the COVID-19 pandemic in agriculture using a bibliometric analysis approach. A total of 1514 research papers indexed in the Scopus database, covering a period of 2020 to 2022, are processed using VOSviewer and R-Studio software. The analysis of research productivity indicates that the number of research publications on COVID-19 and agriculture has exponentially increased globally, and about 80% of the research papers have been published in the top 10 countries led by the USA, India, and China. The countries are increasingly collaborating in undertaking research on COVID-19 and agriculture. Furthermore, major journals and articles with citations have been extracted to analyze the leading publication avenues and focused areas of research. The science mapping is done using co-occurrence and thematic map. With the help of co-occurrence analysis, six clusters are identified depicting major research themes, i.e., COVID-19 and agricultural supply chain disruption, COVID-19 and human health issues and coping strategies, COVID-19 and non-human and animal health, COVID-19 pandemic and environment and pollution, COVID-19 and healthcare and treatment, and COVID-19 and food nutrition from dairy and meat products. The thematic map analysis identifies potential research areas such as mental health, anxiety, and depression in the agricultural system, which may help in setting future research agenda and help devising policy supports for managing the agriculture sector better during crisis. The paper also highlights the theoretical and practical implications. [ABSTRACT FROM AUTHOR]

Agriculture plays a pivotal role in our society by providing food, fiber, and raw materials for various industries. The world's population is steadily growing, and there is increasing pressure on agriculture to meet the rising global food demand. In this context, the use of machine learning approaches to predict crop yields has gained significant importance. This paper aim is to study the significance of crop yield prediction through machine learning, its methods, applications, and its potential to revolutionize the agricultural sector. [ABSTRACT FROM AUTHOR]

Purpose: This case study is based on the Women in Agri-Tech programme, a teacher professional development programme that aimed to build teachers' capabilities to use Agri-Tech in their agriculture/STEM classes to increase student awareness of agriculture technology and its associated career paths. Teachers and agriculture industry partners co-created Agri-Tech modules, which were implemented and evaluated from teachers' and students' perspectives. This paper demonstrates how work-related learning that emphasises technology can increase the visibility of career pathways and how multi-stakeholder benefits can evolve from teacher–industry partnerships. Design/methodology/approach: An action research design using quantitative and qualitative methods was used to construct this case study. Data collection methods included surveys, interviews, peer evaluation and teacher reflections. Findings: Teacher professional development that incorporates teacher-industry partnerships can increase teachers' self-efficacy and build confidence to support authentic work-related learning in their classes. Integrating technology into agriculture/STEM classes can increase the visibility of agriculture career paths for students, which is critical given the serious skills shortage in this sector. Research limitations/implications: This study is limited in that the Women in Agri-Tech professional development programme was one standalone programme tailored specifically for women agriculture/STEM teachers through a competitive process. However, the beneficial implications of such programmes that support teacher–industry engagement have far-reaching benefits. Teacher professional development programmes that provide opportunities to partner with industry can support improvements in integrating career-aligned learning into the curriculum and can specifically address industry skills and knowledge gaps by addressing school-based learning requirements for the future workforce. Originality/value: This paper contributes to the literature on education–industry partnerships and considers how teachers can contribute to an early intervention sector workforce development strategy for future industry sustainability. [ABSTRACT FROM AUTHOR]

The income effect of rice–crayfish co-culture technology (RCT) is directly related to rate of adoption of farmers and the process of China's green development of agriculture. The aim of this study is to explore the income effect and income growth mechanism of rice–crayfish co-culture technology from the perspective of continuous adoption. With the treatment effect model (TEM), this paper empirically analyzes the income effect and income-generating mechanisms of RCT using field survey data from 736 farmers in the Jianghan Plain. As a result of this study, it was discovered that RCT will increase farmers' net agricultural income by RMB 83,430 if they continue to adopt it. Further examinations indicate that the optimal adoption period for RCT is four and a half years. Additionally, it has also been shown that non-farm employment positively moderates the relationship between continuous adoption of RCT and net agricultural income. Farmers who participate in non-farm employment and continue to adopt the RCT will experience an increase in net agricultural income by RMB 104,510. Therefore, our results suggest that it is necessary to encourage farmers to continuously adopt RCT and actively participate in non-farm employment to enhance the income effect of RCT. [ABSTRACT FROM AUTHOR]

Introduction: Digital agricultural technology service has the characteristics of high efficiency, convenience and flexibility, and plays an important role in the process of Chinese agricultural digitalization, which is of great significance for realizing the modernization and intelligent development of agricultural production. Methods: Based on micro-survey data of small-scale farmers in Sichuan Province, this study utilizes the OLS method and the mediation effect model to investigate the impact of digital agricultural technology services on farmers' willingness to adopt digital production technologies and its underlying mechanisms. Results: The results indicate that digital agricultural technology services effectively enhance farmers' willingness to adopt digital production technologies, especially among those engaged in cooperative. Further analysis of mechanisms suggests that digital agricultural technology services influence farmers' choices of household production and management methods by expanding their information channels, enhancing their cognition of digital production technologies, and facilitating access to technology. Moreover, heterogeneous analysis reveals significant differences in the willingness of farmers with varying levels of digital literacy to adopt digital production technologies. Digital agricultural technology services have a more pronounced impact on the willingness of highly digitally literate farmers. Discussion: The findings of this paper deepen our comprehension of the operational mechanisms of digital agricultural technology services in the context of agricultural development, and advocate for policy recommendations such as enhancing the supply of digital agricultural technology services, strengthening the role of new agricultural entities, improving farmers' digital literacy training, and enhancing policy support systems. [ABSTRACT FROM AUTHOR]

To explore whether digital finance can reduce agricultural carbon emissions, promote regional convergence, and foster inclusivity in rural revitalization and shared prosperity, this paper uses the provincial-level index of digital financial inclusion to analyze the impact of digital financial inclusion on the intensity of agricultural carbon emissions and the Degum Gini coefficient (D-Gini coefficient) of regional carbon emission intensity in 30 sample provinces from 2010 to 2020. It examines the mechanism of the impact of digital financial inclusion on both variables to understand the underlying factors better. The main conclusions are as follows: (1) Digital financial inclusion significantly reduces the intensity of agricultural carbon emissions and narrows the gap in carbon emission intensity between regions. (2) The unconditional quantile regression coefficients show that the negative coefficients of the digital financial inclusion index and the three-dimensional indices decrease with increasing quantiles. However, the significant effects vary significantly at different quantiles. (3) Technological progress and the government's ability to allocate financial resources play a significant mediating role, and the income gap between urban and rural areas can be further narrowed, as well as the carbon emission intensity gap between provinces. The empirical results are robust and proven by replacing the econometric analysis method, changing the core variables, and other methods. [ABSTRACT FROM AUTHOR]

The integration of the Internet of Things (IoT) has brought about transformative changes across diverse industries, and its application in agriculture, particularly in soil management, has become a focal point of research and innovation. This paper explores the paradigm shift enabled by IoT in detecting organic carbon in soil, with the overarching goal of advancing agricultural productivity and sustainability. Emphasizing the pivotal role of organic carbon in soil health, the research addresses the existing challenges associated with its detection and underscores the potential advantages offered by IoT-based solutions for precise and real-time monitoring. The study meticulously examines various IoT technologies, including sensors, data analytics, and wireless communication protocols, within the specific context of organic carbon detection. A thorough review of contemporary techniques, methodologies, and devices utilized in IoT-based organic carbon detection in soil is presented. The paper not only sheds light on the current state-of-the-art but also explores the advantages, limitations, and prospects inherent in the implementation of IoT-enabled systems in agriculture. The envisioned outcomes encompass enhanced soil management practices, heightened crop yields, and the simultaneous preservation of the environment. In essence, this research contributes to the expanding body of knowledge surrounding IoT applications in agriculture, specifically emphasizing the transformative potential of IoT-enabled organic carbon detection for revolutionizing farming practices and promoting sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Copyright of Society: Chinese Journal of Sociology / Shehui is the property of Society: Chinese Journal of Sociology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we considered and characterised the features of information systems management of agricultural production processes, which are based on agricultural technologies to support and increase food security in the domestic and external markets. We revealed management models in this category, which are used in the agrarian sector of Canada and Vietnam. Differences between these two models are connected with several factors, including socioeconomic development, quality of arable land, availability of resources and their cost, level of labour resources' readiness to the implementation of new ICT, and farms' adopting the necessity of transition to precise farming. The revealed advantages and problems of implementing Agritech at the level of the two countries demonstrate that the focus on sustainable and precise farming has become a new trend in this sphere. The goal of this paper was to establish the features of the formation of approaches to information systems management in Agritech to ensure the food security of countries that produce agricultural products. The scientific novelty of this paper lies in the determination of approaches to the implementation and management of information systems in the considered category, which facilitate the creation of conditions for the growth of efficiency of agricultural productions under the influence of threats of climate change. [ABSTRACT FROM AUTHOR]

Agriculture plays a crucial role in fostering sustainable growth through the integration of various technological advancements such as image processing, artificial intelligence, deep learning, and the Internet of Things (IoT). The global population is increasing on a daily basis. The increasing demand within the agriculture industry has necessitated the collective enhancement of plant cultivation and field productivity. This paper emphasizes the significance of effectively managing the crop during its initial growth phase as well as during the harvesting era. Image processing and artificial neural networks are employed as distinct methodologies for detecting illnesses on leaves. When capturing images using drones, the resulting images undergo a process of segmentation and transformation, resulting in the identification of three distinct vectors that represent diseases. These vectors include colour, texture, and morphology. This paper reviews on various disease classification strategies that can be utilized for the detection of plant diseases. [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]

Technological advancements can potentially revolutionize agriculture in Nigeria, addressing critical challenges such as low productivity, inefficiencies, and sustainability concerns. This paper explores the significance of these technological innovations, focusing on their impact and implementation within the Nigerian context. Through a series of case studies--including precision farming by Olam Nigeria, crowdfunding platforms like Thrive Agric, cooperative models employed by Babban Gona, and eextension services by the Federal Ministry of Agriculture--this study illustrates how technology can enhance agricultural productivity, economic viability, and sustainability. Key findings highlight increased yields, cost efficiencies, improved market access, and the promotion of sustainable practices. However, challenges such as high initial costs, limited internet connectivity, and the need for technical expertise persist. The paper concludes with recommendations to improve infrastructure, increase access to affordable financing, strengthen research and development, enhance education and training, promote sustainable practices, facilitate market access, implement supportive policies, and foster innovation ecosystems. These steps are essential for harnessing the full potential of technological advancements to transform Nigerian agriculture and drive socio-economic growth. [ABSTRACT FROM AUTHOR]

The current geopolitical and socioeconomic landscape creates a difficult and uncertain operating environment for farming and agri-food businesses. Technological innovation has not been suggested to be a "silver bullet" but is one of the ways organizations can seek to reduce environmental impact, deliver net zero, address the rural skills and labor deficit and produce more output from fewer resources and as a result, make space for nature. But what barriers limit this promissory narrative from delivering in practice? The purpose of the paper is to firstly explore the reported social, technical and systemic barriers to agri-technology adoption in an increasingly uncertain world and then secondly identify potential research gaps that highlight areas for future research and inform key research questions. Socio-technical and infrastructural barriers have been identified within the context of the complex hollowing out and infilling of rural communities across the world. These barriers include seventeen factors that emerge, firstly those external to the farm (economic conditions, external conditions including bureaucracy, market conditions, weather uncertainty and the narratives about farmers), those internal to the farm business (farming conditions, employee relations, general finance, technology and time pressures) and then personal factors (living conditions, personal finances, physical health, role conflict, social isolation and social pressure). Adaptive resilience strategies at personal, organizational and community levels are essential to address these barriers and to navigate agri-technology adoption in an uncertain and dynamic world. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The symbiotic relationship between nitrogen-fixing cyanobacteria and plants offers a promising avenue for sustainable agricultural practices and environmental remediation. This review paper explores the molecular interactions between nitrogen-fixing cyanobacteria and nanoparticles, shedding light on their potential synergies in agricultural nanotechnology. Delving into the evolutionary history and specialized adaptations of cyanobacteria, this paper highlights their pivotal role in fixing atmospheric nitrogen, which is crucial for ecosystem productivity. The review discusses the unique characteristics of metal nanoparticles and their emerging applications in agriculture, including improved nutrient delivery, stress tolerance, and disease resistance. It delves into the complex mechanisms of nanoparticle entry into plant cells, intracellular transport, and localization, uncovering the impact on root-shoot translocation and systemic distribution. Furthermore, the paper elucidates cellular responses to nanoparticle exposure, emphasizing oxidative stress, signaling pathways, and enhanced nutrient uptake. The potential of metal nanoparticles as carriers of essential nutrients and their implications for nutrient-use efficiency and crop yield are also explored. Insights into the modulation of plant stress responses, disease resistance, and phytoremediation strategies demonstrate the multifaceted benefits of nanoparticles in agriculture. Current trends, prospects, and challenges in agricultural nanotechnology are discussed, underscoring the need for responsible and safe nanoparticle utilization. By harnessing the power of nitrogen-fixing cyanobacteria and leveraging the unique attributes of nanoparticles, this review paves the way for innovative, sustainable, and efficient agricultural practices. [ABSTRACT FROM AUTHOR]

This study aims to provide a scientific basis for the development of county-level agricultural industries through a comprehensive evaluation of the environmental and economic benefits of agricultural products. Focusing on Hancheng City in Shaanxi Province, this paper calculates and analyzes the carbon emission intensity per unit output value and the economic benefits of major agricultural products, assessing their comprehensive advantage indices. The research methods include data collection, data processing, and model construction, utilizing a bi-factor matrix analysis to explore the balance between environmental sustainability and economic profitability of different agricultural products. The results indicate that pepper and vegetables have the highest comprehensive advantages, demonstrating significant economic and environmental benefits, while soybeans show lower comprehensive advantages, requiring improvements in cultivation techniques and management practices. Based on the research findings, this paper proposes policy and management recommendations for different agricultural products, including focusing on the development of high-comprehensive-advantage products, improving cultivation techniques for low-comprehensive-advantage products, promoting green agricultural technologies, establishing a carbon footprint monitoring system for agricultural products, and strengthening agricultural infrastructure construction. The study's conclusions provide theoretical support and practical guidance for the agricultural development strategies of Hancheng City and similar regions, contributing to the achievement of sustainable agricultural development and carbon reduction goals. [ABSTRACT FROM AUTHOR]

Image Enhancement (IE) is vital and one of the significant parts of Image processing. It is necessary to enhance the contrast and reduce the noise to improve the quality of the image.IE is one of the processes for altering the visibility of an image. It is widely applied in different fields such as medical science, industry, military, agriculture, etc. Image Enhancement is modifying digital images to make the image appear pleasing to the viewer. Several research works have been done on Image Enhancement. This paper also discusses the Self-Calibrated Illumination method (SCIM) and the HE method. SCIM along with HE Image Enhancement techniques and algorithms can improve the visual quality of the digital image. There are several techniques to enhance the quality of an image to extract meaningful information from the image. The wellknown techniques for image enhancement are the RetiNex-based method, Weber-Fechner method, Linear Regression algorithm-based method, Histogram Equalization, Fourier transform, etc. This paper reviews and compares the research work carried out in image enhancement based on the Histogram Equalization Method by different authors. This paper also reviews the merits and drawbacks along with the enhanced images and histogram plots obtained in these methods developed over the past decades. Finally, it concludes what further work needs to be done for a better quality of image. [ABSTRACT FROM AUTHOR]

This paper presents an innovative approach to improving agricultural practices using modern technologies such as machine learning, IoT, and image processing. The proposed system includes two main modules: fertilizer prediction and crop recommendation and crop disease detection. The first module utilizes machine learning algorithms to analyze data from various sources such as soil sensors, weather stations, and historical crop yield data to predict optimal fertilizer requirements and recommend suitable crops for the specific soil type and climate. The second module employs image processing and Convolutional Neural Network (CNN) algorithms to detect crop diseases by analyzing images captured by IoT devices such as drones and cameras. The proposed system aims to increase crop yield, reduce the cost of crop maintenance, and promote sustainable farming practices. The results of this research demonstrate the potential of smart agriculture technologies in improving food security and agricultural sustainability. [ABSTRACT FROM AUTHOR]

In order to explore the impact of education and training of farmers' professional cooperatives on agricultural green production, this paper uses the Oprobit model to analyze the impact of the time, methods, and content of cooperative education and training on green production willingness based on 534 micro-survey data of cooperative members in Sichuan Province. And then the instrumental variable method (IV-Oprobit) is used for endogeneity treatment and robustness test. The results show that: (1) Cooperative education and training time can significantly promote the green production willingness of members. Specifically, for every additional hour of education and training, the probability of "very willing" to participate in green production increases by 1.7%; (2) the four types of education and training methods of cooperative project demonstration, on-site training, bulletin board publicity, and online information publicity are all positively affecting the willingness of members to green production, and on-site training is the most effective method; (3) the three education and training contents of cognition, emotion and skills all positively affect the green production intention of members, and cognition is the most effective content; (4) the methods and contents of cooperative education and training have an interactive effect on the influence of members' green production willingness. Based on this, this paper proposes policy suggestions to optimize the functions, training methods, and content design of green production education and training in cooperatives. [ABSTRACT FROM AUTHOR]

This paper firstly compares the structure of agricultural supply chain ecosystem from both internal members and external environment and analyzes the information transfer mechanism of information flow, capital flow, logistics and other energy and information in the supply chain. The importance of supply chain ecological coordination mechanism and its functional components are also discussed in depth. On this basis, the biosecurity strategy system of agricultural products supply chain management is constructed and the biosecurity strategy of supply chain management is proposed. Finally, the biosafety risk of agricultural products supply chain management in the e-commerce environment is assessed, and a multi-dimensional risk assessment index is proposed. Meanwhile, risk management theory is applied to provide a detailed analysis of the likelihood, loss, contagiousness, controllability and comprehensiveness of risks. The study showed that the risk indices were relatively high with the average values of 85% for transportation and storage technology risk, 76% for additive abuse risk, and 70% for agricultural input improper risk, respectively. The research in this paper provides new ideas and methods for biosafety management in the supply chain of agricultural products. [ABSTRACT FROM AUTHOR]

In the last decades, geostatistics has been widely used for precision agriculture (PA) producing quite exciting results. Research on this topic is important for sustainable agriculture growth in Brazil. The objective of the review is an attempt to outline the current state of using geostatistical tools for PA applications in Brazil in the last 20 years (2002–2022), but not to provide an exhaustive review of models. We analyzed the scientific literature on this field in Brazil to identify their merits and weaknesses in the present, and to conjecture on future developments. We analyzed 151 proceeding papers and 144 peer-reviewed journal articles regarding applications of geostatistics in PA in Brazil from 2002 to 2022 using bibliometric techniques to reveal current research trends and hotspots. We detected using geostatistics for PA has been limited, mostly for univariate interpolation purposes. The co-citation analysis reveals four broad research clusters in the literature: (i) spatial variability, semivariogram, soil management, (ii) soil fertility, ordinary kriging, spatial dependence, (iii) coffee plant, coffee, Coffea arabica, and (iv) glycine max, zea mays, management zones. The presented review is a springboard to future modeling developments useful for geostatistics applications to PA in Brazil. We suggest expanding the use of geostatistics for smart agricultural technology by adding new potential approaches in new research. Combined with other approaches, such as machine learning, uncertainty modeling, efforts for more geostatistical training, and data fusion from multi-sensor and multi-source are a new frontier to be explored more often by the Brazilian PA community. [ABSTRACT FROM AUTHOR]

Despite its status as one of the most ancient sectors worldwide, agriculture continues to be a fundamental cornerstone of the global economy. Nevertheless, it faces obstacles such as a lack of trust, difficulties in tracking, and inefficiencies in managing the supply chain. This article examines the potential of blockchain technology (BCT) to alter the agricultural industry by providing a decentralized, transparent, and unchangeable solution to meet the difficulties it faces. The initial discussion provides an overview of the challenges encountered by the agricultural industry, followed by a thorough analysis of BCT, highlighting its potential advantages. Following that, the article explores other agricultural uses for blockchain technology, such as managing supply chains, verifying products, and processing payments. In addition, this paper examines the constraints and challenges related to the use of blockchain technology in agriculture, including issues such as scalability, legal frameworks, and interoperability. This paper highlights the potential of BCT to transform the agricultural industry by offering a transparent and secure platform for managing the supply chain. Nevertheless, it emphasizes the need for involving stakeholders, having clear legislation, and possessing technical skills in order to achieve effective implementation. This work utilizes a systematic literature review using the PRISMA technique and applies meta-analysis as the research methodology, enabling a thorough investigation of the present information available. The results emphasize the significant and positive effect of BCT on agriculture, emphasizing the need for cooperative endeavors among governments, industry pioneers, and technology specialists to encourage its extensive implementation and contribute to the advancement of a sustainable and resilient food system. [ABSTRACT FROM AUTHOR]

The paper aims to identify the main aspects of digitalization in the EU and Romania at present, in general, and emphasizing on agriculture, because in this sector has a deep impact on infrastructure and work resources. The EU average for DESI index quantifying digital economy performance was compared with the index in the member states to show the differences in the performance of the digital economy. The aspects related to the impact of digitalization in agriculture from many points of view, but mainly on human resources have also been highlighted. Index scores differ from one country to another and reflect the performance result of the efforts that each member state has made to implement digital economy. The higher the index value, the higher the digital economy performance in that country. During the period 2017-2022, Finland, Denmark, the Netherlands and Sweden have maintained their top position in the EU, while Romania and Bulgaria are situated on the last places. Romania should be focused on the improvement of digital infrastructure, promotion of digital competences, innovation and entrepreneurship in order to increase its performance in digital economy. Major efforts should be done to improve connectivity, educational programmes in digital competences and to develop a favourable business environment for contributing to its digital transformation and integration into the EU digital unique market. [ABSTRACT FROM AUTHOR]

The digital economy is integral in driving economic growth, particularly of high-quality standards. Against the backdrop of the "Double Carbon" project, exploring the impact of the digital economy on green agricultural development bears tremendous practical significance. Thus, this study aims to investigate how the digital economy affects agricultural green total factor productivity (GTFP). The entropy-TOPSIS method and SBM-GML index are used to measure core variables quantitatively. In addition, two-way fixed effects panel data models, Tobit, and intermediary effect models are implemented. Three research findings emerge. First, China's agricultural GTFP level generally experiences an upward trend, and the development of the digital economy has a significant positive effect on increasing agricultural GTFP. Second, the digital economy mainly promotes agricultural technology innovation that boosts agricultural GTFP. Third, Western China experiences a more significant positive effect of the digital economy on agricultural GTFP than Central and Eastern China. Finally, based on the findings, this paper proposes relevant policy recommendations to promote green and sustainable agriculture development. [ABSTRACT FROM AUTHOR]

Agricultural technologies (agri-techs) have focused on developing the AI perspective of human-AI interaction rather than human perceptions and responses. A lack of understanding of their employees' behavioral responses when interacting with advanced technologies can lead to unexpected problems in the future. Drawing on the theoretical perspective of advanced user engagement, this paper examines the impact of five different technostressors on user engagement and, consequently, user experience. For data collection, 464 participants from the U.S. and Asian (Singaporean) agri-tech sectors were interviewed via an electronic survey. The U.S. study showed that techno-overload, techno-complexity, and techno-uncertainty were positively related to user engagement (t = 2.609; t = 6.998, and t = 6.013, respectively), whereas techno-invasion and techno-uncertainty were negatively correlated with user engagement (t = –2.167 and t = –3.119, respectively). The Singapore study showed that techno-overload, techno-complexity, and techno-invasion were negatively related to user engagement (t = –2.185, t = –2.765; t = –5.062, respectively), while techno-insecurity and techno-uncertainty surprisingly showed nonlinear correlations with user engagement. In both studies, user engagement is positively related to user experience (t = 2.009 for the U.S. study and t = 2.887 for the Singapore study). First, this paper provides agri-techs with a modern framework to better predict the behavioral responses of their employees when managing AI. Second, this paper expands the equation of change in the discipline of change management by introducing the dimension of readiness. [ABSTRACT FROM AUTHOR]

The institutional environment in Bulgarian agricultural sector is a complex system of relationships, dynamically changing under the influence of national and sectoral legislation. Over the last 16 years, was characterized as a difficult period for agriculture and land relations in Bulgaria -- because of insufficient legislation the Ownership and Use of Agricultural Land Act about 34 changes have been made to the Act, which are directed in the interest of agricultural users. The changes made concern the concluded contracts for the use and lease of the agricultural land. The dynamics and future changes in land relations are inextricably linked to changes in European and national policy. Receiving European subsidies and financial support to the income of Bulgarian farmers deforms the economic environment in our country. The European subsidies are a key motive and priority for farmers. The purpose of this paper is to describe the state in Bulgarian agricultural sector which is characterized by intensity and dynamics, more complexity and instability. The value of the gross agricultural output had declined during the last years. This research work is based on the following methodological approaches: complex, structural and comparative. The theoretical framework of this article provides a summary overview of the main institutional changes in the agricultural policy and the structure of land relations in Bulgaria. For the purposes of the research different information sources have been used - scientific journals, as well as the author's own research. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present the procedure of managing public procurement contracts for sustainable agricultural products from the public entities perspective (with reference to setting criteria for selecting the suppliers, contract management, etc), but also from the perspective of the selling companies (from drafting the tender to products being delivered). The research is based on data processed by Eurostat (2012-2021), but also on information taken from the Romanian Electronic Public Procurement System (2018-2022). The analyses in the paper concern indicators such as: the procurement of agricultural products from Romania, and at European level the organic production of animal products, the number of processors of sustainable agricultural products, etc. In conclusion, since the public institutions buy large quantities of agricultural products, but the market for sustainable agricultural products is restricted, a global strategy for rethinking the public procurement in this area is clearly required. The work is relevant both for the contracting authorities with respect to the management of public procurement for agricultural products, but also for the companies with respect to the business management of public contracts. [ABSTRACT FROM AUTHOR]

This paper examines whether financial technology (FinTech) development affect household energy consumption. The proposed point that FinTech can reduce household energy consumption is theoretically discussed and empirically tested using data from the 2017 Digital Financial Inclusion Index, the 2018 China Family Panel Studies (CFPS), the 2018 China Environmental Statistical Yearbook and the 2018 China Science and Technology Statistical Yearbook. The results show that FinTech contributes to reducing household energy consumption. Several retests, including the instrumental variable, replacement sample and propensity score matching methods, prove its robustness. Mechanism tests show that investment in environmental governance and technological innovation promotion are the two main transmission channels. We also find that the reducing effect is more significant in the following groups: the low-middle income level classes, the eastern regional residents, those with bachelor's degrees and above, the those aged over 60 and rural residents. The outcomes of this paper call for government departments to positively guide FinTech development to reduce household energy consumption. From another perspective, the conclusions drawn from our analysis make a great reference value for countries and provide new ideas for Chinese carbon peaking and carbon neutralisation goals. [ABSTRACT FROM AUTHOR]

As a powerful statistical method, meta-analysis has been applied increasingly in agricultural science with remarkable progress. However, meta-analysis research reports in the agricultural discipline still need to be systematically combed. Scientometrics is often used to quantitatively analyze research on certain themes. In this study, the literature from a 30-year period (1992–2021) was retrieved based on the Web of Science database, and a quantitative analysis was performed using the VOSviewer and CiteSpace visual analysis software packages. The objective of this study was to investigate the current application of meta-analysis in agricultural sciences, the latest research hotspots, and trends, and to identify influential authors, research institutions, countries, articles, and journal sources. Over the past 30 years, the volume of the meta-analysis literature in agriculture has increased rapidly. We identified the top three authors (Sauvant D, Kebreab E, and Huhtanen P), the top three contributing organizations (Chinese Academy of Sciences, National Institute for Agricultural Research, and Northwest A&F University), and top three productive countries (the USA, China, and France). Keyword cluster analysis shows that the meta-analysis research in agricultural sciences falls into four categories: climate change, crop yield, soil, and animal husbandry. Jeffrey (2011) is the most influential and cited research paper, with the highest utilization rate for the Journal of Dairy Science. This paper objectively evaluates the development of meta-analysis in the agricultural sciences using bibliometrics analysis, grasps the development frontier of agricultural research, and provides insights into the future of related research in the agricultural sciences. [ABSTRACT FROM AUTHOR]