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Purpose - The purpose of this paper is to report the findings from a study that explored the use of art and visual production as a means through which 20 third-graders developed and represented their social studies understandings. The author describes the ways the process of visual production and the finished products illustrate the nature of the students' social studies learning. Design/methodology/approach - The project was grounded in an inductive qualitative approach privileging student voice. This paper reports analysis and interpretation of multiple data sources, including photographs of students' projects, digital recordings of the visual productions and student interviews, as well as field notes and informal teacher conversations. Findings - Results suggest that in the process of visual production and in their final pieces, students moved in fluid ways between making sense of new knowledge, developing important social studies skills, and representing their knowledge. More specifically, students used historical evidence to present humanized versions of history through personalized narratives. These outcomes suggest that the integration of art and visual production can be a valuable and effective way for students to develop and apply social studies skills as well as represent their understanding. Originality/value - This study provides insight into how young children can use art and visual production to develop social studies skills, make sense of new knowledge, and represent their learning, contributing knowledge on an understudied topic and population in social studies education. [ABSTRACT FROM AUTHOR]

To ensure sustainable development, there is a limit to the extent of urbanization. Thus, rural development is an essential strategy that many nations must work on to ensure optimal economic, environmental, and social outcomes at a country level. However, rural development in itself is challenging because rural communities typically have limited resources and capabilities to address common livelihood challenges, let alone take on new economic roles. Hence, as part of rural revitalization strategies, innovation plays a critical role. A wide range of technologies can facilitate innovation in rural development, including the internet and new agricultural technologies. In addition, new mindsets and shifts in values, such as the changing trends of work and consumerism, can create opportunities for rural areas to adopt innovation and develop new growth engines. However, it should be noted that the nature of innovation in rural and urban settings are different. In rural regions, growth could be enabled through more specific types of innovations, including frugal innovation, inclusive innovation, and social innovation. To enable these forms of innovations in rural areas, this paper proposes a three-dimensional process model that includes pro-social technological innovation policy, rural innovation governance, and dynamic networks that close the gap between rural and urban innovation systems. Examples from China, such as the development of Tengtou Village and Taobao Villages serve to demonstrate these concepts. Overall, the discussions in the paper suggest that to enable innovation in rural development, it is necessary to foster closer interactions between rural and urban innovation ecosystems for the former to leverage the latter's technologies, networks, and resources. [ABSTRACT FROM AUTHOR]

This paper discusses the role of technology and big data in the agri-food industry. With the world population growing rapidly, there is a need to produce more food to feed everyone. Agriculture is changing rapidly, and technology is playing a crucial role in this change. The concept of Agriculture 4.0 seeks to optimize every factor to minimize inputs and maximize efficiency. Big data is being collected to improve management and farm management. Precision farming is being used to predict crop development phases and yields. The European Union is lagging behind the US and China in terms of innovation and market evaluation. Innovation drives economic growth, and it goes beyond invention. Small and medium-sized enterprises are playing an essential role in driving economic growth, particularly in the agri-food business. To improve resilience and production efficiency in the agri-food business, there is a need to boost SMEs' competitiveness. The European agri-food business is lagging in terms of digitalization, but there is a significant potential for growth. Finally, technology and big data are playing a crucial role in the agri-food industry, and there is a need to evaluate contextual elements to improve farmers' technology use. [ABSTRACT FROM AUTHOR]

Autonomous agricultural vehicles rely on accurate real-time positioning information to perform precise farming operations, including seeding, fertilizing and harvesting. Although many positioning solutions exist on the market, their cost is out of many farmers' budgets. Relative positioning can be used for accurate positioning purposes in agriculture applications. Despite the fact that several research attempts have addressed the issue of relative positioning, no agriculture-specific study appears to exist in the literature at the time of writing. In this paper, the opportunity of using real-time GPS-based relative positioning for agriculture applications instead of the typical absolute positioning solutions has been investigated. To this end, we propose to implement and evaluate different relative positioning approaches, namely absolute position differencing, pseudorange single differencing as well as pseudorange double differencing (PDD). Real-world experiments, including static and dynamic scenarios, have been conducted using low-cost single-frequency GPS receivers in an open sky environment and an agricultural field. The obtained results show the superiority of the PDD approach with about 76% of estimation errors less than 1 m in the open sky environment and more than 97% of estimation errors less than 3 m in the agricultural field, representing a considerable accuracy enhancement compared to GPS standalone positioning. [ABSTRACT FROM AUTHOR]

Smart farming is a new concept that can be described as applying different kinds of modern technology to make farming more efficient. One such technology is the Internet of Things, an extension of the Internet and other connections into mundane devices. This paper uses dedicated sensors and cloud computing technologies to model a smart farming system that helps farmers keep track of state of the crops and livestock. It also covers implementing and testing an Android tracker app that is supposed to become the first component of the mentioned system, a client application that communicates with the cloud computing services yet to be implemented. The end product provides its users with an easy way of keeping track of the state of their farms, simplifying the farmers' work and enhancing productivity. [ABSTRACT FROM AUTHOR]

In India, the agriculture is main profession for more than sixty percent of the population. The stakeholders of agriculture in India, facing plenty of problems that leads the people of the country to shift their profession and lets them migrate towards urban area. So, need of implementing technology in agriculture is must in future days because as population is increasing in exponential form as the result huge requirement of food and agricultural product. The data analytics will play a significant role in agricultural dataset for implementing prediction and recommendation system in the sector. Yield is one of the factors to be considered in the agriculture that determines the wellness and prosperity of the farmer. In this paper deals with prediction system to predict yield of areca nut product in Puttur taluk, Dakshin Kannda District, Karnataka state in India. The time series data analytics model known as Auto Regressive Integrated Moving Average (ARIMA) model is used for yield prediction system. The research is mainly focused on forecasting of areca nut production for next four or five years in Puttur taluk. It compares various ARIMA models with performance criteria and selects best model for prediction purpose. The diagnostic check is carried out to test the system performance After the prediction, then the actual values and predicted values are compared and presented in the form graphical representation. [ABSTRACT FROM AUTHOR]

Supply chain management (SCM), product traceability, and product quality certification are some of the initial prominent uses of blockchain technology. This is because blockchain technology is built on trust and cannot be changed. The popularity of blockchain technology is increasing as it is trustworthy and cannot be changed; hence making traceability easier for information such as where food came from, thus essential for managing the agricultural food supply chain (SC). On the contrary, suggested SCM systems premised on smart contract technology and blockchain tend to be specifically apply to production and production processes. Through qualitative research, this paper suggests framework for adoption of smart contracts based on Ethereum in the agri-food SC, with the aim to establish means to adopt blockchain for checking food quality and origins in the agri-food supply chain. Remix IDE is utilised to build and test the smart contract. The significance of the framework is realised through ensuring the traceability of product safety and quality. [ABSTRACT FROM AUTHOR]

Digital transformation in manufacturing necessitates the integration of advanced fields such as robotics, the Internet of Things (IoT), and data science. The latter two, in particular, introduce a unique set of challenges related to data acquisition and processing, especially for emerging manufacturing sectors that lack substantial data volumes for analytical software. This paper specifically addresses the challenges associated with limited data within the context of precision poultry farming. We begin by identifying the specific challenges encountered during the development of a smart poultry management software system. Subsequently, we propose potential solutions for each identified challenge. The outcome of this study is a comprehensive algorithm for data processing that encapsulates these proposed solutions, offering a practical approach to overcoming data limitations in precision poultry farming. [ABSTRACT FROM AUTHOR]

The objective of this paper is to assess the readiness of Italian farms to actively engage in the journey of "Agriculture 4.0" (Agri 4.0). Specifically, the focus lies on analyzing the levels of knowledge and adoption of specific Agri 4.0 enabling solutions, while also considering the underlying business needs and the primary benefits of the paradigm. A descriptive survey was conducted involving 543 respondents associated with agricultural companies of varying sizes. The collected data was analyzed to address four specific research questions. The survey findings indicate that Italian farms are at different stages in their progression towards the Agri 4.0 paradigm, primarily influenced by their revenue and land size. Furthermore, notable similarities exist in both the benefits associated with adopting the Agri 4.0 paradigm and business needs that bring farmers in adopting such technologies. In terms of future research, conducting a similar study in other countries would be beneficial for comparative and benchmark analyses. Despite scholarly discussions regarding technology adoption and the benefits of the Agri 4.0 paradigm are present to the authors' knowledge few empirical surveys have been conducted thus far to evaluate the level of digital solution adoption in agriculture within a specific country. Specifically, this preliminary study follows research conducted two years ago, paving the way for a longitudinal comparison of the two datasets. [ABSTRACT FROM AUTHOR]

The integration of Internet of Things (IoT) technologies in agriculture has emerged as a transformative force, revolutionizing traditional farming practices and driving efficiency and sustainability. This paper presents the development and implementation of a cost-effective greenhouse monitoring system utilizing LoRaWAN technology for data communication. The system's design, deployment, and performance are discussed in detail. Key components include an array of sensors for monitoring environmental parameters and LoRaWAN for long-range, low-power communication. The low-cost nature of the system challenges the notion that advanced agricultural technology is prohibitively expensive, making it accessible to farmers of varying scales. The system's affordability and realtime data accessibility make it a valuable tool for precision agriculture, contributing to improved crop yields and resource management. [ABSTRACT FROM AUTHOR]

Low carbon agricultural techniques, which aim to reduce agricultural emissions without compromising productivity, are being widely adopted as one strategy to promote more sustainable food systems. Evaluating the impact of such practices requires an effective monitoring, reporting and verification (MRV) system. To our knowledge, no MRV system has been designed or implemented for monitoring and measuring the impacts of the adoption of low carbon agricultural practices. The goal of this paper is to explore the opportunities and challenges of developing a large scale MRV system for low carbon agriculture in Brazil - a major global food producer. The analysis presented in this paper is based on primary data, collected through interviews and conversations with experts, and secondary data from a literature review as well as from public and private databases. Hence, we discuss the three phases of monitoring, reporting and verification. In each case, we analyze the informational needs of an MRV system, evaluate the strengths and limitations of available tools to collect and process these data, and present a vision of how these constituent parts could form a comprehensive MRV system for Brazil. Our analysis reveals technical and governance challenges. On the technical side, challenges include the need to develop emissions factors to calculate mitigation across a range of biomes and low carbon agricultural techniques, and the high costs of gathering and verifying information on farm level. On the governance side, there is a need to generate economic incentives for farmers to share private, farm-level data with a public MRV system. The MRV system could help producers to demonstrate adoption and mitigation, giving them improved access to low-interest credit or certification programs. We conclude that the implementation of a large scale MRV system for low carbon agriculture demands an integrative approach based on a hybrid public-private governance system that prioritizes cost-effectiveness and facilitates smooth information transfer. • Low carbon agriculture needs Monitoring Reporting and Verification (MRV) systems for measuring and reporting GHG emissions. • We propose an MRV system for Brazil, a country that has huge mitigation potential due to its agricultural activity. • Primary farm-level data about adopted techniques could be combined with remotely-sensed and secondary data about land use. • A hybrid public-private governance strategy could reduce costs and create incentives. • Brazil's case is a relevant benchmark for MRV systems in other countries. [ABSTRACT FROM AUTHOR]

Given persistent gender inequalities that influence how the benefits of technologies are distributed, the expansion of small-scale irrigation technologies requires the consideration of important gender dynamics and impacts. Women's lack of agency and access to resources relative to men, and other social constraints, often limit their ability to adopt and benefit from agricultural technologies. At the same time, expanding access to agricultural technology to women may provide a pathway for empowerment. This paper explores the potential for small-scale irrigation technologies to increase women's empowerment by evaluating the impacts of an intervention that distributed motor pumps to small groups of farmers in Northern Ghana. The paper draws on two rounds of survey data that included the Women's Empowerment in Agriculture Index, before and after the motor pump intervention was implemented. To control for possible selection bias at the baseline, the difference-in-difference method is used to estimate the impact of the program on indicators of women's empowerment. Spillover effects are estimated by comparing outcomes of farmers in treatment villages that did not receive the pumps with farmers in control villages, where no motor pumps were distributed. The results show no significant impact of the program on measures of women's empowerment. However, there are potential negative impacts, including among households that did not benefit from the intervention. The results highlight the need to pair interventions that distribute agricultural technologies with complementary investments in infrastructure that increase access to water for irrigation, as well as other activities and approaches that ensure women can reap the benefits. • Supplying men and women farmers with motor pumps for small-scale irrigation did not increase women's empowerment. • Rather, the intervention had negative spillover effects on women from households that did not receive pumps. • Women's empowerment in the study communities is generally increasing over time irrespective of the irrigation intervention. • The benefits of the motor pump intervention for women are indirect, including increasing household asset holdings. • More careful planning and implementation of irrigation interventions are needed facilitate women's empowerment. [ABSTRACT FROM AUTHOR]

The Supply Chain Management (SCM) of agricultural products (AP) is an important part of modern logistics, and cultivating talents with rich theoretical knowledge and practical operation skills of the SCM of agricultural products is particularly meaningful for China as a major agricultural country. However, at present, few studies have concerned about the training path for such talents, so to fill in this research blank, this paper studied the training path for AP-SCM talents and the assessment of their training quality, aiming to find and solve the defects in the existing training programs. At first, this paper proposed training path for AP-SCM talents and attained the conclusion that colleges and universities should pose requirements for AP-SCM talents from 9 training directions. Then, a prediction model was built for assessing the training quality of AP-SCM talents, and the specific model framework and modeling principles were given. At last, experimental results verified the effectiveness of the prediction made by the proposed model. [ABSTRACT FROM AUTHOR]

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This paper compares predictive algorithms for smart agriculture sensor data in Internet of Things (IoT) applications. The main objective of IoT in agriculture is to improve productivity and reduce production costs using advanced technology and artificial intelligence. In this study, we compared various predictive algorithms for analyzing IoT smart agriculture sensor data. Specifically, we evaluated the performance of NeuralProphet, Random Forest Regression, SARIMA, and Artificial Neural Networks (ANN) by KERAS algorithms on a dataset containing temperature, humidity, and soil moisture data. The dataset was collected using IoT sensors in a smart agriculture system. The results showed that Random Forest Regression, Seasonal ARIMA, and Artificial Neural Networks by KERAS algorithms outperformed NeuralProphet algorithm in terms of accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

Scholars have recognised digital agricultural technologies and financialization as important vectors of agrifood transformation, yet little research has examined how these trends mutually influence one another. In this paper, we present case studies of four firms that blend together digital agriculture, farmland investment, and finance capital in novel ways. Veripath is an established farmland investment company, with significant holdings in Western and Central Canada. It relies on digital technologies to remotely monitor the performance of its properties and the farming practices of its tenants. Farmers Edge is a digital agriculture platform and service provider founded in Canada in 2005, with operations spanning North America, Brazil, and Australia. The firm has received significant backing from finance capital and is partnering with U.S. farmland management services provider Farmers National Company to facilitate data flow among farmers, landowners, and investors. Finally, we present the cases of AcreTrader and FarmTogether, two recently launched farmland investment platforms promising to 'democratise' farmland investment by offering investors a seamless online experience for buying rural properties. We analyse how these firms represent an evolving nexus between finance capital and digital agriculture, with implications for agri-food restructuring. [ABSTRACT FROM AUTHOR]

Nowadays, the Internet of Things (IoT) environments are evolving and becoming popular. The number of devices connected to the Internet continues to raise. IoT is an interrelated network of numerous devices in which data is automatically gathered from the environment by the sensors and transferred over the internet without human support and intervention. The IoT eases individuals interacting with real-world applications over the internet in the IoT environment. Modern innovations in IoT have added computers, sensors, streets, buildings, and even communities to the impression of smartness. IoT appliances function in distinct environments to fulfill several purposes; result in the variety of computational devices and communication technologies employed in healthcare, education, military, agriculture, and commerce. Thus, IoT holds a lot of promise for enhancing social and corporate life. Nevertheless, IoT equipment are a soft target and prone to attacks due substantially to their resource limitations, and the nature of their networks. There are many approaches and technologies utilized to preclude IoT from varied attacks and assaults, Intrusion Detection System (IDS) and Intrusion Preventions System (IPS) are some of them, which can ensure the security, privacy, and reliability of the IoT. In this paper, we provide a deep study of many recent and pertinent IDS/IPS proposed between 2019 and 2022 for IoT networks, giving their key specifics, strengths, shortcomings, and challenges in order to spot the issues that still require to be handled. The paper also lines the mainstream research direction and opens the way for new avenues of research for forthcoming researchers. [ABSTRACT FROM AUTHOR]

This paper discusses how the theory of affordances can be used to investigate how a spectrum of opportunities, benefits, costs and risks is generated and unevenly distributed by different kinds of technology (where 'technology' is understood as techniques, processes and practices of doing and making, rather than technical artefacts and systems). Affordances are possibilities for action, which arise from relations between humans and entities that surround them. This paper discusses three kinds of affordances: material, cultural and socio-economic. The theory of affordances offers a coherent way to explain why different technologies have different implications, and why those implications vary for different stakeholders. Applied to the domain of development-oriented agricultural research and innovation, the theory of affordances could be used by researchers and practitioners to examine the differentiated implications of different kinds of farming technology and alternative programmes of technological change in agriculture, both ex ante (e.g. in their design, development and implementation) and ex post (e.g. in their evaluation). To illustrate the argument, the paper uses the example of weeding in the System of Rice Intensification. Since affordances in theory are generated relationally and situationally for each person, the full array of implications arising from the introduction of new technology could be wide and diverse. A practical challenge, therefore, is whether and how the theory of affordances can be used practically and operationally to design, implement and evaluate the appropriateness, accessibility, utility and value of agricultural technology and technological change for specific people and groups of interest. • The theory of affordances is applied to agricultural technology and innovation. • Affordances are perceived action possibilities, which arise relationally. • Affordances can be studied through material, cultural and socio-economic lenses. • The theory of affordances could be applied to development interventions ex ante and ex post. • Weeding in the System of Rice Intensification is used to illustrate the argument. [ABSTRACT FROM AUTHOR]

• This special issue examines the benefits, limitations and problems of novel smart-farming solutions. • The papers investigate the relations and processes that lie behind the introduction of smart technologies in agriculture. • This introduction focuses on two main aspects of smart farming: interconnectivity and automation. • This collection questions the micro-politics involved in the innovation and diffusion of smart-farming solutions. • The papers study the power dynamics that unfold from the proliferation of smart technologies in farming. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has fundamentally transformed our interaction with technology by connecting a diverse array of devices and objects through the internet, presenting boundless possibilities in various domains such as healthcare, agriculture, transportation, and industrial automation. However, this interconnected network of smart devices also brings forth complex security and privacy challenges, encompassing the potential for infringements on privacy, data breaches, and unauthorized access. To address these concerns and ensure successful adoption, this paper proposes a novel mechanism that involves an Audit Manager for transparency and accountability. This comprehensive approach aims to safeguard user data, promote trust, and strengthen the security of IoT environments, facilitating their seamless integration into various aspects of our lives. The security analysis of the proposed mechanism has proved it to be secure and reliable. [ABSTRACT FROM AUTHOR]

Classification of Indonesian crops is a critical task in developing farming and getting more understanding of agriculture. However, there is no clear task in classifying types of crops in Indonesia. Transfer learning has been used successfully in a variety of image classification applications. Thus, in this paper, we collected images of Indonesian crops from the internet randomly and proposed a classification by using transfer learning of deep learning with four pre-trained models: EffficientNet- B0, ResNet18, VGG19, and AlexNet. In the experiment, augmentation techniques such as random horizontal flip, random vertical flip, and random affine were utilized to prevent the network from overfitting. The result found that EfficientNet-B0 outperformed other models with an accuracy of 82.55. Then, the model struggled to distinguish between crops in the same family. According to the results, although transfer learning can work well to classify images of Indonesian agricultural crops, some improvements are still required to address existing issues. [ABSTRACT FROM AUTHOR]

Third regionalism explains the liberalization of trade centered around the Asia-Pacific region in the 21st century. Under regionalism, domestic agricultural markets that formerly enjoyed national food-security policies have loosened. This caused traditional domestic farmers' organizations to become more regionally interconnected, forming a food sovereignty movement under the auspices of La Via Campesina. Localized food-production chains are promoted to mitigate the impact of regionalism on the Asia-Pacific agricultural sector. The Taiwan Rural Front (TRF) joined La Via Campesina and the food sovereignty movement in the 2010s. During the process of adopting regionalism, Taiwanese agricultural trade and technologies were protected by public agencies and state-owned enterprises. This context differs from that of Southeast Asia, where the food sovereignty movement has thrived. Therefore, the following question is raised: Why was it possible for the food sovereignty movement to originate in Taiwan? This paper describes the developmental characteristics of Taiwan's food-security governance mechanism as a state-guided corporate food regime amid third regionalism. Further, the TRF does not advocate for localized food-production chains. Due to the formation of a state-guided corporate food regime, the food sovereignty movement has become connected with farmland protection movements that set the Taiwanese sovereignty movement apart. [ABSTRACT FROM AUTHOR]

Taking Yantai Cherry as an example, this paper studies the influencing factors of customer satisfaction in online shopping of characteristic agricultural products, and analyzes five influencing factors: pre-purchase expectation, product quality, brand image, e-commerce platform and logistics distribution, and designs a scale, puts forward assumptions and verifies them. The results show that pre-purchase expectation has no significant negative influence on customer satisfaction, product quality, brand image, e-commerce platform and logistics distribution have significant positive effects on customer satisfaction. Finally, based on the research conclusions, this paper puts forward some countermeasures and suggestions on improving customer satisfaction of characteristic agricultural products e-commerce from four aspects, which is of certain significance for increasing sales of specialty agricultural products and promoting the development of agricultural e-commerce. [ABSTRACT FROM AUTHOR]

Agricultural production has dual functions as a carbon emitter and sink, and fully exploiting the carbon sink function of agriculture is highly valuable for ensuring carbon neutrality. The layout of net carbon in agriculture shows an imbalance, i.e., underscaling in areas with a net carbon advantage or overscaling in areas with a net carbon disadvantage, which restricts the fulfillment of agricultural carbon sinks. Clarifying the global pattern of net carbon imbalances in agriculture and their drivers is highly important for improving the overall net carbon. In this regard, this paper focuses on the global net carbon in agriculture in 155 countries and regions, and a spatial mismatch index of net carbon in agriculture (MNCA) is constructed based on the relative difference between net carbon and cultivated land. Spatial autocorrelation analysis and the standard deviation ellipse are used to reflect its spatiotemporal evolution pattern. In addition, through geographically weighted regression, we explored the effects of agricultural structure, agricultural economic development, the scale of labor and cultivated land and organized the mismatches into carbon and area effects. The results show that (1) global agricultural production represents net carbon emissions, while developing countries represent net carbon sinks, and there is a mismatch of net agricultural carbon in most regions; (2) the MNCA is characterized by low-low clustering in North America, Asia and Europe, with its center of gravity falling in western Africa and migrating northeastward; and (3) the main factors influencing the MNCA are the agricultural structure and economic level. Underscaling in areas with a net carbon advantage is a major problem. To increase the global agricultural carbon sink capacity, we suggest that North America, South Asia and other regions strictly implement agricultural emission reduction policies and that Central America, South America and Africa tentatively upgrade agricultural technology and their economies to alleviate farmland pressure through transnational cooperation. In this paper, the global net carbon imbalance in agriculture is identified and the overall implementation path of increasing carbon sinks is explored to provide a reference for achieving carbon neutrality. This study reports a global mismatch in net carbon in agriculture and identifies the wasted carbon sink advantage of developing countries as the root problem. • It is a new indicator to measure the efficiency of net carbon allocation in the agricultural production process. • Agricultural production in developing countries shows a net carbon sink advantage. • Under-scaling of net carbon advantage is major problem. [ABSTRACT FROM AUTHOR]

Agriculture must overcome escalating problems in order to feed a growing population while preserving the environment and natural resources. Recently, it has become clear that sensors and the Internet of Things (IoT) are effective tools for boosting agricultural sustainability and food security. This study provides insights into the global market size for smart agriculture in future years from 2021 to 2030, In addition, this research offered four levels of the IoT architecture for smart agriculture: the perception or sensing and actuator layer, the network layer, the cloud layer, and the application layer. The state of the art in IoT and sensor technologies for agriculture is examined in this review paper, along with some of their potential uses, including 1) irrigation monitoring systems, 2) fertilizer administration, 3) crop disease detection, 4) monitoring (yield monitoring, quality monitoring, processing monitoring logistic monotoring), forecasting, and harvesting, 5) climate conditions monitoring, and 6) fire detection. Additionally, this review offers a number of sensors for agriculture that can detect parameters like soil NPK, moisture, nitrate, pH, electrical conductivity, CO2, temperature, humidity, light, weather station, water level, livestock, plant disease, smoke, flame, flexible wearable. Subsequently, this study highlights the advantages of IoT in smart agriculture, including superior efficiency, expansion, reduced resources, cleaner method, agility, and product quality improvement. However, there are still issues that need to be resolved in order for IoT technology to be used in agriculture where covered in this paper, and also provide insights into future research directions and opportunities. This study will contribute to helping future readers and researchers to better understand the state of academic achievement in this subject. [ABSTRACT FROM AUTHOR]

This study examines how an agtech startup managed to turn a mobile app designed to diagnose plant damages and recommend treatments into an asset. Rooted in assetization research and the sociology of markets, the paper theorizes agtech startups as organizations that increasingly engage in the construction of markets for pesticides and other inputs. Empirically, the study reconstructs the assetization of the app over a period of eight years, showing how the process gradually and quite radically transformed both the app itself and its socio-technical collective. More specifically, the study describes four phases constituting the analyzed segment of the assetization process in question, over the course of which the app evolved from a technology for disseminating knowledge about alternatives to chemical pesticides into a platform for brokering sales of biological and chemical pesticides on behalf of large agrochemical corporations. To make sense of this radical repositioning of the app vis-à-vis chemical pesticides, the article introduces the concept of exploratory assetization—a concept that draws attention to the fact that the socio-technical collectives through which startup-born innovations are turned into assets are not fixed from the outset but emerge only over time through constant confrontations between a given innovation and the various human and non-human actors with which the assetization process puts it in touch. The article concludes that the exploratory assetization process described in it calls into question the ability of venture capital-funded digital agriculture technologies to contribute to pesticide reduction in a long-lasting way. • Agtech startups are involved in the assetization of agri-food systems. • The assetization of agtech is not predefined but an emergent phenomenon. • Given this non-determinacy, on should speak of a process of exploratory assetization. • Agrochemical groups have strong influence on the exploratory assetization of agtech. • Exploratory assetization of agtech perpetuates agricultural problems of past decades. [ABSTRACT FROM AUTHOR]

Agriculture is the major occupation and the main origin of income in India, and most of the population depends on agriculture for their living. The smart farming system's foremost goal is to monitor farmlands by automatically rinsing the lands with appropriate water and a pest detection framework. The conventional agricultural methods lack higher crop productivity with increased human efforts. Hence, the paper proposes an IoT-based solution for smart farming. The proposed system focuses on automatic irrigation of water and plant disease detection. It uses machine learning algorithms to accurately predict adequate water required by the fields and automatic pest identification based on the requirements of the farmland. K-Nearest Neighbour and support vector machine learning algorithms in the pest detection module are used to precisely predict plant diseases. The convenient features from the leaves of the plants were obtained. Then the obtained features are used for classification purposes. Extracting the suitable features and classifying them helps detect whether the plant is pest infected or not. The proposed system monitors, analyses, assesses and controls agricultural fields for the automatic irrigation of the water and disease identification of the plants. The numerical analysis of the machine learning algorithms and the significance of the classification with accuracy are investigated. From the numerical results, it is demonstrated that an accuracy of 84 % is achieved. [ABSTRACT FROM AUTHOR]

In order to solve the problem of separation between consumer purchase and product experience in online sales, live streaming e-commerce came into being. However, the interaction of streamers is easy to cause consumers' impulse consumption, which leads to the soaring return rate. In this context, how to make reasonable return policies to avoid the loss is an important issue for brands. This paper studies return policy selection for brands. We mainly focus on MCN (multi-channel network) click farming and customer disappointment aversion in the situations that the return-freight insurances are paid by brands or consumers or brands and MCN jointly. Three leader-follower models with brands as leaders and platforms and MCN as followers are established. To solve the above bilevel models, we discuss the conditions under which the upper and lower models are both convex and, based on these theoretical results, we give the optimal strategies for all members. Then, through numerical experiments, we analyze the impacts of customer disappointment aversion level, MCN's ability, commission rate, brand's return-freight insurance purchasing ratio, and other factors on each member's optimal decision. The results show that the return policy in the situation of return-freight insurance paid by brand is suitable for a market with the high level of customer disappointment aversion; the return policy in the situation of return-freight insurance paid by consumers is applicable to the case of low customer disappointment aversion and high commission rate; the return policy in the situation of return-freight insurance paid by brand and MCN jointly is suitable for the case of low MCN capability and can effectively restrain the click farming from MCN. [ABSTRACT FROM AUTHOR]

Digitalisation has changed agricultural production and will continue to do so. Although digital technology promises to increase the efficiency, productivity and environmental friendliness of agriculture while improving the work-life balance of farmers, new digital farming technologies come with potential negatives, such as privacy and security concerns. In recognition of that fact data is a fundamental part of digital adoption in the agricultural sector, this article analyses Swiss farmers perceptions of data sharing. We apply the Responsible Research on Innovation (RRI) approach to anticipate and discuss farmers' legal and political perspectives on agricultural data and data sharing. These form the foundation of and thus the key to digitalisation in agriculture. Based on a review of the literature and two exploratory interviews on the broader regulatory context of data sharing, Swiss data regulation and management were included as background to this work. This paper, further explores in detail the relationship between farmers' attitudes towards data sharing and their relatively low adoption of digital technologies. Such an analysis is valuable as it provides us with the farmers' perspective on data use and regulations in Switzerland which, though not an EU country, has its own high data-protection standards. More specifically, we assessed Swiss farmers' perceptions of agricultural data sharing with public and private entities and placed these perceptions within the broader Swiss framework for data regulation. This was accomplished by a survey of 939 randomly selected farmers in the German- and French-speaking parts of Switzerland. From the Swiss farming perspective, we discuss how innovation can respond to societal needs. We conclude that the concerns, risks and vulnerabilities that Swiss famers are currently experiencing with regard to their farm data need to be addressed through a broader regulatory reform of Swiss agricultural data protection if digital farming is to achieve its full potential in Switzerland. • In digital agriculture, ever more data are being generated and shared by farmers with private providers and the government. • The absence of regulation of agricultural data is emphasized in this study. • Swiss farmers are aware of the value of their data but not of the terms of the data contracts and do not trust data privacy. • An imbalance of power exists between farmers and digital technology providers and between farmers and the government. • Regulatory issues must be addressed to ensure farmers can trust data management and fully realize digital farming's potential. [ABSTRACT FROM AUTHOR]

This paper looks at different technologies that are being used currently in agricultural education at the University of Queensland (UQ), Australia through the lens of 'disruption' as a positive force. The paper describes tools and systems that have been developed, tested and implemented to engage students and provide an interesting, educative interactive experience. These tools include Internet of Things (IoT) multisensory mesh networks and associated data dashboard developments for biophysical monitoring, drone technology design and build for agricultural management, and augmented reality simulations as blended learning experiences. These tools have all been used in teaching from 2018-2020. [ABSTRACT FROM AUTHOR]

Notions of naturalness are widely assumed to drive how people perceive genetic engineering (GE). As newer forms of genetic engineering—namely, gene editing, gene drives, and synthetic biology—are reshaping life forms in both agriculture and conservation, they are increasingly raising questions of what a 'natural' food, organism or ecosystem is, and whether objections toward 'unnaturalness' or preferences for 'naturalness' might reveal a deeper ethical or value-based logic. A number of fields have sought, both directly and indirectly, to define the concept, but insights have not yet been applied to new forms of genetic engineering. This paper proposes that systematically reviewing scholarly interpretations of 'naturalness' might offer weight to a concept that is often dismissed as irrational. Here, we review and synthesize insights from a range of fields, outlining possible logics public groups might employ to reason about what is '(un)natural'. We also offer a novel thought experiment in which we apply these logics to a sample of novel GE applications. One of our core findings is that '(un)naturalness' may be understood not necessarily as a quality of an object, but rather as a characteristic of ecological, social, cultural, and spiritual relationships. Such an understanding implies the need for ongoing engagement with the values embedded in ideas of naturalness and empirical explorations of how such values inform debates on novel engineered foods, organisms and ecosystems. • New forms of genetic engineering (GE) in agriculture and conservation are raising questions of 'naturalness'. • 'Naturalness' is often assumed to be an irrational reason for objecting to particular applications of GE. • Fields from natural sciences to humanities offer varied definitions of and insights into meanings behind 'naturalness'. • Relational understandings of naturalness offer crucial insights for design of future GE applications. [ABSTRACT FROM AUTHOR]

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Nowadays, we are in the era of advanced technologies where tremendous amount of data is produced by multiple sources such as sensors, devices, social media, user experiences, etc. Furthermore, this raw data has a low value, and major part is not really useful or important for business. One way to give an added value to this stored data is to extract useful knowledge from it, for the ending-system or the end-users by a process commonly called knowledge Discovery in Database (KDD). Smart Farming uses a large amount of connected technologies producing also a huge amount of data in order to maximize productions by reducing: human efforts, environment impact and wasting natural resources. In this paper, We develop a new data analytic architecture dedicated to Precision Livestock Farming (PLF) to improve in particular the livestock animals production, animals' welfare, and farming processes. We present a new data processing architecture for a knowledge-base management system (KBMS) allowing to ease decision support and monitoring operations that can help farmers and stakeholders to better exploit data and have a long-term view of the evolution of the knowledge it contains. Our main contribution in the present paper is a new architecture specifically developed for the precision livestock farming integrating a periodical data reevaluation which address the problematic of data conservation and the decrease in data value over time. [ABSTRACT FROM AUTHOR]

The subject of this paper is the review of advanced technology used in hydraulic systems. The technology in question is termed Independent Metering (IM); this is used in hydraulically driven mobile machinery, such as agricultural, construction, municipal, and forestry vehicles. The idea behind the concept is to modify the connection between the actuator, which could be a cylinder or a motor, and a flow control valve. Traditionally, spool hydraulic valves were used to control the fluid flow into and out of hydraulic actuators. This keeps the meter-in and the meter-out of the actuator mechanically connected due to the construction of these valves. This connection makes the control system blind to pressure changes in one of the hydraulic chambers in the actuator. This, in turn, reduces the overall system controllability. It also increases energy losses, especially under an overrunning load. These two main weaknesses led researchers to break this mechanical connection and get into a new technology with different characteristics. The proposed technology was called Independent Metering. New and more complex control techniques can now be applied to the hydraulic systems using this technology that were not possible before or could be applied to more conventional servo design. This paper reviews Independent Metering (IM) and the technologies used or developed in this field to date. The paper reviews the state of art hydraulic technologies and indicates the links between them and IM. It also reviews the different types of hydraulic valves used when implementing IM. This review also discusses some control algorithms, IM layouts, IM challenges, and identifies where further improvements may be achieved. • Review the hydraulic Independent metering configurations. • Investigate different technologies related to the IM. • Show the main valves embedded into IM and their effects on the performance. • Review the main IM control techniques and Layouts. • Summarize the IM challenges and research trends. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Water Resources / Recursos Hídricos is the property of Associacao Portuguesa dos Recursos Hidricos 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.)

Grain is not only the basic living materials of urban and rural residents, but an important strategic resource related to the national security. Therefore, grain security is an important aspect of national security. Farmers' willingness to grow grain is the key factor to guarantee food security. Based on the structural equation model, the main factors that influence the farmers' willingness to grow grain were studied in this paper by investigating 486 dispersed farmers in six counties (cities, districts) of three prefecture-level cities in Shandong Province. The study indicated that aside from the difficulty of measuring the influence of personal characteristic factors, the national grain subsidy policies, grain price, grain planting scale, other farmers' production behaviors, and promotion of agricultural technology affected the farmers' willingness to grow grain in varying degrees. Further regional multi-group analyses demonstrated that the farmers' willingness to grow grain showed an increasing trend from east to west in Shandong Province. Additionally, grain subsidy policies and family characteristic factors had obvious regional differences on the farmers' willingness to grow grain. Therefore, optimizing and improving the national grain subsidy policies, encouraging the management of a moderate scale, stabilizing prices of grain, increasing the propaganda of agricultural information and promoting agricultural technology were the key factors to increase the farmers' willingness to grow grain. • Establishing a comprehensive model to study the influencing factors of farmers' willingness to grow grain. • Six main factors influencing farmers' willingness to grow grain were studied. • Each factor has different effects on the farmers' willingness to grow grain and shows significant regional differences. • The farmers' willingness to grow grain shows an increasing trend from east to west in Shandong Province. [ABSTRACT FROM AUTHOR]

Using a comprehensive primary dataset collected from 3680 farmers in certain districts of China and a long-time panel dataset of 31 of China's provinces from 2000 to 2012, an empirically analyzed work is presented in this paper on the impact of farm size on agricultural technology progress from both micro and macro perspectives. A Multivariate Probit Model was built to analyze and clarify the micro basis on which farm size affects technology progress. The impact of farm size on farmers' willingness to adopt new technologies, their technical preference, and their behaviors to acquire agricultural knowledge was tested by model estimation. The influence of farmers' average scale on agricultural technology progress in most regions was estimated by using fixed-effect and random-effect models. The progress of technology was measured by the technology progressing rate (TPR), which is calculated by the trans-log stochastic frontier function. The results show that farmers with larger farms are more willing to adopt new technologies, spend more time and money in the pursuit of agricultural knowledge, and pay more attention to productive technology rather than processing technology. From the regional analysis, it seems the regions with larger farms have a much higher technology progress rate overall, and while the effect varies depending on scale, there are remarkably positive impacts in large-farm regions, slightly negative impacts in medium-sized farm regions, and notable negative impact in small-farm regions. • The impact of farm size on farmers' willingness to adopt new agricultural technologies are positive and significant. • Farmers with smaller farms are more interested in processing technologies than the larger one. • Large-scale farmers have spent more time and money to acquire agricultural knowledge. • Regions with larger average farm size have a much higher technology progress rate. • The farm size effect changes with the growth of farmers' agricultural scale: dropped first, and then rised. [ABSTRACT FROM AUTHOR]

Innovation is perceived as a crucial tool for addressing the serious global challenges faced by the agriculture sector. This paper focuses on a new local public agricultural innovation project in the context of rural China, and intends to capture the embodied agricultural innovation and dissemination network for modernizing the smallholders. Through integrating the concepts of Agricultural Innovation System and Agricultural Innovation Governance, we develop a comprehensive framework for understanding the partnerships between agri-technicians and small farmers within the network structured by innovation governance practices. In-depth interview and network analysis methods were used to scrutinize the linkages among actors engaged with the agricultural innovation programme in case area and detect the achievements in enabling smallholders to upgrade technical trajectories in production and fostering modern farmers at the local levels. Our empirical analysis suggests that the single-center and multi-level network produced in the agricultural innovation practices, which is distinctive to the previous simplistic linear model for technology transfer, demonstrates obvious effectiveness in diffusing the new knowledge both vertically and horizontally, and that the grassroots sub-network generates the interaction space between agronomic experts and farmers for building mutual trust and co-producing technologies suitable for local conditions. Through allocating financial resources and supervising the public agricultural innovation projects, the provincial government indirectly dominates the directionality of local agricultural innovation for enabling smallholders to learn emerging technologies and cultivating the new generation of professional farmers. Nevertheless, the current agricultural innovation practice in case area has not completely avoided the social selection bias due to the clear marginalization of some vulnerable smallholders, and the duration of innovation projects imposed negative influence on the persistent collaborations between agri-technicians and smallholders in places. It is argued that for meeting the national agenda of agricultural modernization and common prosperity in rural area, how to reform the management measures of public innovation projects and enable the vulnerable farmers to equally engage with the innovation activities and share the interests brought by new technologies are the urgent challenges need to be addressed in the future. • The pathway of governance on agricultural innovation diffusion for modernizing smallholders was explored. • The single-center and multi-level agricultural innovation network is effective in transferring new technologies vertically and horizontally. • Local governments indirectly steer the directionality of agricultural sci-tech innovation for empowering smallholders in Rural China. • Agricultural innovation dissemination in locality played crucial role in nurturing leading farmers and modernizing smallholder agriculture. • Agricultural innovation diffusion in rural China has not completely avoided the social exclusion and sped the marginalization of some vulnerable smallholders. [ABSTRACT FROM AUTHOR]

The increased focus on reducing greenhouse gas emissions and decreasing dependence on fossil fuels has led to heightened interest in alternative fuels. Given the critical role of agriculture in both the consumption and production of energy, understanding the factors that influence farmers' decisions to purchase an alternative fuel tractor is paramount. This study aims to identify constructs that influence German farmers' intentions to purchase alternative fuel tractors, applying the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. An online survey conducted in 2022 yielded 141 usable responses from German full-time farmers, and the UTAUT model was estimated using Partial Least Squares Structural Equation Modelling (PLS-SEM). Farmers perceive alternative fuel tractors as particularly suitable for low-energy farm and field work, but lower driving ranges relative to conventional diesel tractors are the main barrier to adoption. General performance expectancy and social influence emerged as the most potent drivers of farmers' intentions to purchase alternative fuel tractors. The paper contributes original insights into the factors influencing technology adoption in agriculture and provides practical implications for policymakers and agricultural machinery manufacturers. The results guide strategies to encourage alternative fuel tractor adoption and suggest directions for future sustainable agriculture research. • First research focussing on the intention to buy an alternative fuel tractor • Identification of barriers to the adoption of alternative fuel tractors • UTAUT model for farmers' intention to buy an alternative fuel tractor • Performance expectancy predicts the intention to buy an alternative fuel tractor. • Results are of interest for policy-makers and agricultural machinery manufacturers [ABSTRACT FROM AUTHOR]

The use of information and communication technology could increase the quantity and quality of agricultural production, including horticulture. This study focuses on the development of a mobile-based interface that makes it easier for farmers to view the data obtained from the results of land monitoring. In designing mobile devices, applications, and user interfaces, it is important to consider the user experience. This paper focuses on UX design which is based on User-Centered Design approach that focuses on user needs and prioritizes empathy for users, so as to accommodate the identification of user needs and produce high fidelity prototype. Based on the System Usability Scale and the User Experience Questionnaire testing on the prototype, it was found that the level of acceptance of horticultural farmers was positive with the level of the value of all UX elements above the average. [ABSTRACT FROM AUTHOR]

The use of digital technologies in agriculture offers various benefits, such as site-specific application, better monitoring, and physical relief. The handling of these technologies requires a specific skill set. Therefore, the question arises of when and how farm managers learn about digital technologies. Aiming to analyse the current situation, the present research investigated the role that digital technologies play in vocational training for future farm managers. Taking the example of farm management information systems (FMIS), the present study also analysed various predictors of adoption, including the effect of training. To investigate these research questions, an online survey among teachers and students of the farm management vocational programme across Switzerland was conducted in the spring of 2021. In total, 150 individuals participated, 41 of whom were teachers. Participants answered questions about the learning content in the farm management programme and their perception of digital technologies in general. Students further reported whether they already had a farm they would be managing in the future and how they perceived FMIS. The results indicate that both teachers and students are convinced that digital technologies play an important role in agriculture and will gain more importance in the future. A substantial part of 43% of the students who participated indicated that they had learned neither about digital technologies during their basic agricultural training nor the subsequent farm management programme. In terms of FMIS, 51% of the student sample indicated that they had never heard about FMIS during their agricultural training. While having learned about FMIS was not a significant predictor for adoption, gender, perceived ease of use, and intention to use more digital technologies in the future significantly predicted the adoption of FMIS. The paper concludes that, to support the adoption of digital technologies and FMIS specifically, training for future farm managers should focus on how to operate an FMIS to increase the perceived ease of use of this technology. [Display omitted] • 57% of the students learned about digital technologies during vocational school. • 49% of the students learned about FMIS during vocational school. • Intention to use digital technologies is an important predictor for the TTMA. • Perceived ease of use of FMIS is an important predictor for the TTMA. [ABSTRACT FROM AUTHOR]

Seeking out new technologies and deploying them for competitive advantage is a key priority for any company. In this context, Internet of Things (IoT) promise to change the way we live and work. IoT could help us in overtaking the top global challenges, as energy management, agriculture and food security, environment and natural resources security, etc., but to achieve this vision, "things" need to sense their environment and share this information among them as well as with us to offer intelligent decision-making. Nowadays, IoT become even more interesting due to the existence of Low Power Wide Area (LPWA) networks. LPWA is a key component of a wider IoT technology wave. In this paper, a LoRaWAN based solution is presented, for manufacturing process monitoring, in order to improve energy management in plants. The authors present a minimally invasive device, with which many product manufacturing data can be obtained for analysis and further improvements. This paper is an extended variant of [14]a. [ABSTRACT FROM AUTHOR]

Capital accumulation in the agro-food sector displays new characteristics in modern society. By means of a case study of China's sugarcane sector, this paper identifies three capital accumulation strategies that recently emerged. The first strategy is the redistribution of costs and benefits between farmers and companies through the introduction of new technologies which is known as agro-technification. The second strategy is termed food politicization and relates to the profound restructuring of both sugarcane production and the sugar market through massive state intervention. The third strategy is land swindle, namely the conversion of land from a means of production into an object of speculation. Following a discussion of the three strategies by drawing on developments in China's sugarcane sector, this paper argues that these new capital accumulation activities will render national and transnational food systems more fragile and unsustainable. Moreover, it argues that classical agrarian analyses defining accumulation as a land-labour-capital triangular relation cannot explain the current capital accumulation in agro-food sector. Instead, a new triangular technological-political-financial synergy more aptly describes recent developments in the agro-food industry in general. [ABSTRACT FROM AUTHOR]

Human societies have experienced three basic revolutions namely the agricultural, industrial and knowledge-based economic revolutions in modern socio-economic era. During those revolutions not only economic structure but also social and cultural structures have evolved. During the last two decades, the third revolution or knowledgebased economy has started; an era in which application of knowledge is the most important factor for production and it is a driving force behind industrial and economic progress more than any other factors. Given the present conditions and their profound changes, governments have prompted special measures in order to fulfill the prediction of their development. The process of development in this era depends on the right choice of leading knowledge and precise and systematic planning for pioneering it. In order to advance these measures, in addition to knowing the leading knowledge, selection criteria should also be analyzed. This paper utilized a descriptive-analytical approach to explain the subject, only from the economic point of view, and data collection was conducted using the existing documents and evidence, such as articles, books, credible websites, etc. The findings of this research indicated that the four basic criteria for an accurate and systematic selection include the capacity to create added value, the capacity to cluster, the possibility of infrastructure, and the capacity to create sustainable employment opportunities which are all discussed in details in this paper. [ABSTRACT FROM AUTHOR]

Deep learning (DL) is a robust data-analysis and image-processing technique that has shown great promise in the agricultural sector. In this study, 129 papers that are based on DL applications used in agriculture are discussed, categorizing them into five areas: crop yield prediction, plant stress detection, weed and pest detection, disease detection, and smart farming. Smart farming is sub-categorized as water management, seed analysis, and soil analysis. This study highlights the potential of deep learning in enhancing agricultural productivity and promoting economic growth. The study found that supervised learning networks, such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), AlexNet, and ResNet, are primarily used in agriculture to enhance economic growth. However, there is a need to develop new DL techniques that can improve model performance and reduce inference time for practical applications. In this review, critical research gaps, particularly in the development of new techniques, are analyzed. This study emphasizes the importance of continued research in this area to fully leverage DL's potential of DL for smart farming and to achieve sustainable agricultural development. • Deep learning is vital in agriculture. • Reviewed 129 agriculture based-DL papers. • DL propels smart farming. [ABSTRACT FROM AUTHOR]

This paper investigates the problems associated with the economical efficiency of aerial photography for the application in unmanned aerial vehicles (UAV) with low-class photography systems. The aim is to analyse the efficiency of employing unmanned aerial vehicles for specialized search and transforming the capabilities of UAVs for high efficiency applications in the agriculture. The structure and efficiency of the UAV operation when used in modern agricultural technologies for improving the functions such as search, recognition, monitoring of mobile milking systems and the manipulative-robotic actions of UAVs are shown. The range of applications could be significantly broadened by supplying the UAVs with special devices to directly carry out technological operations such as spraying of chemicals, planting plants, pasture monitoring, etc. [ABSTRACT FROM AUTHOR]

Pluralistic agricultural advisory systems comprise diverse actors, including public and private research, development, and extension (RD&E) providers, and private sector agricultural advisors. Co-innovation, as a collaborative engagement involving the full range of actors, is regarded as useful when addressing issues arising from this complexity. However, what helps or hinders successful co-innovation with public and private actors in real-world situations is still under-described in the literature. A deeper understanding of the social interactions and practices of doing co-innovation in specific settings is required to achieve successful co-innovation outcomes. This paper asks: What key features of practice support co-innovation with public and private system actors? And: How can enhanced understanding of practice assist in strengthening co-innovation processes? We present findings from research funded by the Australian government from 2015 to 2018 to strengthen private sector extension roles and connections between the RD&E functions in Australia's pluralistic advisory system. Four action research pilots were co-designed with system actors to support co-innovation. These were: Involving agricultural supply chain actors in collaborative agricultural R&D; Increasing farm advisor capacity to engage with digital agricultural technologies; Improving career pathways for new entrants in the advisory and extension sector; and Improving knowledge flows in the advisory and extension system. We found that co-innovation requires potentially profound social change; a shaking up of expectations about roles, responsibilities, and institutionalised processes. The research also suggests that the requirement for social change is underacknowledged in current co-innovation practice, with implications for the success or failure of co-innovation partnerships. Applying a practice theory perspective, our research highlights features of practice that constrained and enabled co-innovation in the four pilots. In doing so, the research provides insights to assist in successful operationalisation of co-innovation involving the private sector in pluralistic agricultural advisory systems. • Co-innovation is complex but achievable in pluralistic agricultural advisory systems. • Social dynamics and practices matter when operationalising co-innovation processes. • Nuanced understanding of practices improves co-innovation design and implementation. • Co-innovation with public and private actors must accommodate commercial realities. • The practice perspective is relevant at the broader level of AIS scholarship. [ABSTRACT FROM AUTHOR]

Reducing the negative impact of agriculture on the environment is an essential issue. This requires the application of environmental and resource-saving technologies in agriculture, ensuring environmentally friendly development of rural areas, the implementation of eco-innovation projects, promotion of eco-innovation activities. The purpose of the paper is to assess the risks for the implementation of innovations from agricultural holdings and, on the basis of the identified types of risk, to outline strategic recommendations for overcoming them. The content of the article is structured as follows: 1) Literary review of the concept of eco-innovation and the risks associated with the application of eco-innovations in agriculture; 2) Methodological framework of the research; 3) Risk assessment in the implementation of eco-innovations from agricultural holdings. The last part summarizes recommendations for overcoming the risk of implementation of ecoinnovations from agricultural holdings. [ABSTRACT FROM AUTHOR]