The impact of ethical commitments on the intention to adopt digital agricultural technologies

Sustainable food security is a critical global concern and an urgent priority in developing countries such as Iran. Digital agricultural technologies (DAT) represent significant solutions in this regard, yet their adoptions and development in Iran face limitations. Theoretical studies have underscored the importance of ethical commitments in the adoption process. This study aims to investigate whether ethical commitments regarding food security can influence the intention to adopt digital technologies by farmers. The study employed the Norm Activation Model and integrated two additional components, namely perceived risk and social capital. We applied this framework to examine research works on farmers of Kermanshah Province in the west of Iran, using survey data (sample n = 384). Data analyses were done through structural equation modeling (SEM). Based on the results, the developed Norm Activation Model can be used to predict the adoption intention of DAT by farmers; with the model explaining 65% of total variance. Feeling guilt exhibited the highest direct effect, followed by feeling proud. Furthermore, ethical norms had a direct and indirect impact on intention through the mediating variables of feeling proud and Feeling guilt. The findings of this study contribute to facilitating innovation adoption strategies. It is recommended that, in order to facilitate and stabilize farmers' adoption of innovation, their sense of guilt should first be aroused. After stimulating the farmers' sense of pride toward the adoption; emphasis should be placed on ethical commitments. Ultimately, the introduction of technology and the facilitation of infrastructure should be pursued.

Review: Ruminant heat-stress terminology

With increasing climate variability, there is a rise in the exposure to, and incidence of, ruminant heat stress (HS), increasing the requirement for focused research. As such, precise terminology is crucial to maintain effective communication and knowledge advancement. Despite this, several key terms are currently defined inconsistently, leading to confusion and misinterpretation. This paper examines the historical and contemporary use of the terms 'resistance', 'tolerance', 'resilience', and 'susceptibility' across various disciplines, revealing significant ambiguities that hinder both research and practice. Through this comprehensive review, we propose new definitions for each term as they are used relating to HS, with a focus on ruminant production. Proposed definitions align with current scientific understanding, providing a robust framework for future research and application. As further research is conducted, we hope these definitions can be improved through the inclusion of quantitative measures which align with these classifications. This present review provides definition clarity for common heat abatement terminology, enabling consistency and from this, progress in the field to ameliorate HS for ruminants.

The Future of Obesity Management through Precision Nutrition: Putting the Individual at the Center

PURPOSE OF REVIEW: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. RECENT FINDINGS: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

A Living Lab approach to understanding dairy farmers' technology and data needs to improve herd health: Focus groups from 6 European countries

For successful development and adoption of technology on dairy farms, farmers need to be included in the innovation process. However, the design of agricultural technologies usually takes a top-down approach with little involvement of end-users at the early stages. Living Labs offer a methodology that involve end-users throughout the development process and emphasize the importance of understanding users' needs. Currently, exploration of dairy farmers' technology needs has been limited to specific types of technology (e.g., smartphone apps) and adult cattle. The aim of this study was to use a Living Lab approach to identify dairy farmers' data and technology needs to improve herd health and inform innovation development. We conducted 18 focus groups with a total of 80 dairy farmers from Belgium, Ireland, the Netherlands, Norway, Sweden, and the United Kingdom. Data were analyzed using Template Analysis, and 6 themes were generated representing the fundamental needs of autonomy, comfort, competence, community and relatedness, purpose, and security. Farmers favored technologies that provided them with convenience, facilitated their knowledge and understanding of problems on farm, and allowed them to be self-reliant. Issues with data sharing and accessibility and usability of software were barriers to technology use. Furthermore, farmers were facing problems around recruitment and management of labor and needed ways to reduce stress. Controlling aspects of the barn environment, such as air quality, hygiene, and stocking density, were particular concerns in relation to youngstock management. Overall, the findings suggest that developers of farm technologies may want to include farmers in the design process to ensure a positive user experience and improve accessibility. The needs identified in this study can be used as a framework when designing farm technologies to strengthen need satisfaction and reduce any potential harm toward needs.

Sustainable agriculture in the digital era: Past, present, and future trends by bibliometric analysis

The digital era is reshaping agricultural practices, opening new avenues for sustainable growth, and proving indispensable in global challenges like food security and environmental conservation. However, a comprehensive understanding of this evolving landscape remains paramount. This research evaluates 344 papers from the Web of Science database to delve into sustainable agriculture's historical and current patterns in the digital era through bibliometric analysis and project future domains. Specifically, citation analysis identified influential papers, journals, institutions, and countries, while co-authorship analysis verified the interactions between authors, affiliations, and countries. Co-citation analysis found four hotspot clusters: prosperity and challenges in agricultural sustainability, digital information and agricultural development, innovations for sustainable agriculture, and geospatial analysis in environmental studies. The co-occurrence of keywords analysis revealed four main clusters for future studies: smart agriculture and biodiversity conservation, digitalization and sustainable agriculture, technologies and agricultural challenge management, and digital intelligence and farmer adoption. The study pioneers the use of bibliometric analysis to explore sustainable agriculture in the digital era. It presents invaluable insights into the evolving landscape of this field, summarizing its hotspots and suggesting future trajectories.

Development of an animal health testing tool to reduce antimicrobial use on farms: perceptions, implications, and needs of Irish dairy farmers and farm veterinarians

BACKGROUND

The threat of antimicrobial resistance is triggering the need for behavioural change towards antimicrobial use on Irish farms. Newly introduced veterinary medicine regulations are mandating the restricted and more prudent use of antimicrobials in the animal health sector. The need to reduce antimicrobials has placed a greater emphasis on the importance of animal health testing, however, issues with current testing practices are affecting diagnosis and subsequent drug usage. There is potential for digital technologies to address these issues and reduce antimicrobial use on farms, however, for these tools to be successful, they would need to be developed in collaboration with future end users.

RESULTS

Using qualitative approaches (focus groups), this study engages with dairy farmers and farm veterinary practitioners to detail current challenges with animal health diagnosis and to explore the initial development of a rapid, on-farm animal health testing tool to address these challenges. Issues with timing and testing, the role of knowledge and experience, and veterinarian availability all affect the ability of farmers and veterinarians to diagnose animal health issues on farm. These issues are having negative implications including the increased and unnecessary use of antimicrobials. An on-farm testing tool would help mitigate these effects by allowing veterinarians to achieve rapid diagnosis, facilitating the timely and targeted treatment of animal illnesses, helping to reduce overall antimicrobial use on farms. However, engagement with end users has highlighted that if a tool like this is not developed correctly, it could have unintended negative consequences such as misdiagnosis, increased antimicrobial use, challenges to farmer-veterinarian relationships, and data misuse. This study outlines initial end user needs and requirements for a testing tool but suggests that in order to successfully design and develop this tool, co-design approaches such as Design Thinking should be applied; to mitigate future negative impacts, and to ensure a testing tool like this is designed specifically to address Irish dairy farmers and farm veterinarians' values and needs, ensuring responsible and successful uptake and use.

CONCLUSIONS

Digital tools can be effective in reducing antimicrobial use on farms, however, to be successful, these tools should be designed in a user centred way.

Agrochemical-free genetically modified and genome-edited crops: Towards achieving the United Nations sustainable development goals and a 'greener' green revolution

Sustainable farming on ever-shrinking agricultural land and declining water resources for the growing human population is one of the greatest environmental and food security challenges of the 21st century. Conventional, age-old organic farming practices alone, and foods based on costly cellular agriculture, do not have the potential to be upscaled to meet the food supply challenges for feeding large populations. Additionally, agricultural practices relying on chemical inputs have a well-documented detrimental impact on human health and the environment. As the available farming methods have reached their productivity limits, new approaches to agriculture, combining friendly, age-old farming practices with modern technologies that exclude chemical interventions, are necessary to address the food production challenges. Growing genetically modified (GM) crops without chemical inputs can allow agricultural intensification with reduced adverse health and environmental impacts. Additionally, integrating high-value pleiotropic genes in their genetic improvement coupled with the use of modern agricultural technologies, like robotics and artificial intelligence (AI), will further improve productivity. Such 'organic-GM' crops will offer consumers healthy, agrochemical-free GM produce. We believe these agricultural practices will lead to the beginning of a potentially new chemical-free GM agricultural revolution in the era of Agriculture 4.0 and help meet the targets of the United Nations Sustainable Development Goals (SDGs). Furthermore, given the advancement in the genome editing (GE) toolbox, we ought to develop a new category of 'trait-reversible GM crops' to avert the fears of those who believe in ecological damage by GM crops. Thus, in this article, we advocate farming with no or minimal chemical use by combining chemical-free organic farming with the existing biofortified and multiple stress tolerant GM crops, while focusing on the development of novel 'biofertilizer-responsive GE crops' and 'trait-reversible GE crops' for the future.

Adoption of ICT4D and its determinants: A systematic review and meta-analysis

Various Digital Agricultural Technologies (DAT) have been developed and implemented around the world. This study aims to estimate the overall adoption rate and identify the determinant factors for a better adoption perspective after decades of innovation and dissemination. A systematic review was conducted on published studies that reported adoption rates and determinant factors using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. We used meta-regression and the partial correlation coefficient to estimate the effect size and establish the correlation between socioeconomic characteristics and the adoption of various technologies reported. Fifty-two studies with 32400 participants met the selection criteria and were included in the study. The results revealed an overall pooled adoption rate of 39 %, with the highest adoption rates in developing countries in Africa and South America. Socioeconomic factors such as age, education, gender, and income were found to be the main determinants and should be considered when designing technology for sustainable adoption. The study also found that young farmers were more susceptible to adoption. Moreover, farmers with higher income levels and educational attainment are more likely to use technology linked to agricultural production, market access, and digital advising, implying that high-income farmers with more education are more tech-savvy. However, this does not exclude low-income and low-educated farmers from adopting the technologies, as many models and strategies with socioeconomic considerations were developed. It is one of the reasons behind the underlying enthusiasm for digital agricultural adoption in low and middle-income countries.

Exploring inclusion in UK agricultural robotics development: who, how, and why?

The global agricultural sector faces a significant number of challenges for a sustainable future, and one of the tools proposed to address these challenges is the use of automation in agriculture. In particular, robotic systems for agricultural tasks are being designed, tested, and increasingly commercialised in many countries. Much touted as an environmentally beneficial technology with the ability to improve data management and reduce the use of chemical inputs while improving yields and addressing labour shortages, agricultural robotics also presents a number of potential ethical challenges - including rural unemployment, the amplification of economic and digital inequalities, and entrenching unsustainable farming practices. As such, development is not uncontroversial, and there have been calls for a responsible approach to their innovation that integrates more substantive inclusion into development processes. This study investigates current approaches to participation and inclusion amongst United Kingdom (UK) agricultural robotics developers. Through semi-structured interviews with key members of the UK agricultural robotics sector, we analyse the stakeholder engagement currently integrated into development processes. We explore who is included, how inclusion is done, and what the inclusion is done for. We reflect on how these findings align with the current literature on stakeholder inclusion in agricultural technology development, and suggest what they could mean for the development of more substantive responsible innovation in agricultural robotics.

Plant Nutrition-New Methods Based on the Lessons of History: A Review

As with new technologies, plant nutrition has taken a big step forward in the last two decades. The main objective of this review is to briefly summarise the main pathways in modern plant nutrition and attract potential researchers and publishers to this area. First, this review highlights the importance of long-term field experiments, which provide us with valuable information about the effects of different applied strategies. The second part is dedicated to the new analytical technologies (tomography, spectrometry, and chromatography), intensively studied environments (rhizosphere, soil microbial communities, and enzymatic activity), nutrient relationship indexes, and the general importance of proper data evaluation. The third section is dedicated to the strategies of plant nutrition, i.e., (i) plant breeding, (ii) precision farming, (iii) fertiliser placement, (iv) biostimulants, (v) waste materials as a source of nutrients, and (vi) nanotechnologies. Finally, the increasing environmental risks related to plant nutrition, including biotic and abiotic stress, mainly the threat of soil salinity, are mentioned. In the 21st century, fertiliser application trends should be shifted to local application, precise farming, and nanotechnology; amended with ecofriendly organic fertilisers to ensure sustainable agricultural practices; and supported by new, highly effective crop varieties. To optimise agriculture, only the combination of the mentioned modern strategies supported by a proper analysis based on long-term observations seems to be a suitable pathway.

Exploring the data divide through a social practice lens: A qualitative study of UK cattle farmers

Appropriate management decisions are key for sustainable and profitable beef and dairy farming. Data-driven technologies aim to provide information which can improve farmers' decision-making practices. However, data-driven technologies have resulted in the emergence of a "data divide", in which there is a gap between the generation and use of data. Our study aims to further understand the data divide by drawing on social practice theory to recognise the emergence, linkages, and reproduction of youngstock data practices on cattle farms in the UK. Eight focus groups with fifteen beef and nineteen dairy farmers were completed. The topics of discussion included data use, technology use, disease management in youngstock, and future goals for their farm. The transcribed data were analysed using reflexive thematic analysis with a social practice lens. Social practice theory uses practices as the unit of analysis, rather than focusing on individual behaviours. Practices are formed of three elements: meaning (e.g., beliefs), materials (e.g., objects), and competencies (e.g., skills) and are connected in time and space. We conceptualised the data divide as a disconnection of data collection practices and data use and interpretation practices. Consequently, we were able to generate five themes that represent these breaks in connection.Our findings suggest that a data divide exists because of meanings that de-stabilise practices, tensions in farmers' competencies to perform practices, spatial and temporal disconnects, and lack of forms of feedback on data practices. The data preparation practice, where farmers had to merge different data sources or type up handwritten data, had negative meanings attached to it and was therefore sometimes not performed. Farmers tended to associate data and technology practices with larger dairy farms, which could restrict beef and small-scale dairy farms from performing these practices. Some farmers suggested that they lacked the skills to use technologies and struggled to transform their data into meaningful outputs. Data preparation and data use and interpretation practices were often tied to an office space because of the required infrastructure, but farmers preferred to spend time outdoors and with their animals. There appeared to be no normalisation of what data should be collected or what data should be analysed, which made it difficult for farmers to benchmark their progress. Some farmers did not have access to discussion groups or veterinarians who were interested in data and therefore could not get feedback on their data practices.These results suggest that the data divide exists because of three types of disconnect: a disconnect between elements within a practice because of tensions in competencies or negative meanings to perform a practice; a disconnect between practices because of temporal or spatial differences; and a break in the reproduction of practices because of lack of feedback on their practices. Data use on farms can be improved through transformation of practices by ensuring farmers have input in the design of technologies so that they align with their values and competencies.

Detecting heterogeneity parameters and hybrid models for precision farming

Precision farming (PF) plays a crucial role in the field of agriculture to solve the challenges of food shortages in society. Heterogeneity, multicollinearity, and outliers are problems in PF because they can cause bias and lead to incorrect inferences. However, traditional methods typically assume it to be a homogenous model, and in machine learning, data scientists ignore heterogeneity. In this study, the aim is to identify the heterogeneity parameters and develop hybrid models before and after heterogeneity. Data on seaweed is collected using sensor smart farming technology attached to v-Groove Hybrid Solar Drier (v-GHSD). There are 29 drying parameters, and each parameter has 1914 observations. We considered the highest order up to the second order interaction, and the parameters increased to 435 parameters from 29 parameters. In high-dimensional data, the number of observations is less than the number of parameters. The authors proposed a method using the variance inflation factor to identify the heterogeneity parameters. Seven predictive models such as ridge, random forest, support vector machine, bagging, boosting, LASSO and elastic net are used to select the 15, 25, 35 and 45 significant drying parameters for the moisture content removal of the seaweed, and hybrid models are developed using robust statistical methods. For before heterogeneity, the hybrid model random forest M Hampel with 19 outliers is the best, because it performs better when compared to other models. For after heterogeneity, the hybrid model boosting M Hampel with 19 outliers is the best, because it performs better when compared to other models. These results are vital to seaweed precision farming. The study of heterogeneity will not only help us to comprehend the dynamics of the large number of the drying parameters, but also gives a way to leverage the data for efficient predictive modelling.

IoT and Deep Learning-Based Farmer Safety System

Farming is a fundamental factor driving economic development in most regions of the world. As in agricultural activity, labor has always been hazardous and can result in injury or even death. This perception encourages farmers to use proper tools, receive training, and work in a safe environment. With the wearable device as an Internet of Things (IoT) subsystem, the device can read sensor data as well as compute and send information. We investigated the validation and simulation dataset to determine whether accidents occurred with farmers by applying the Hierarchical Temporal Memory (HTM) classifier with each dataset input from the quaternion feature that represents 3D rotation. The performance metrics analysis showed a significant 88.00% accuracy, precision of 0.99, recall of 0.04, F_Score of 0.09, average Mean Square Error (MSE) of 5.10, Mean Absolute Error (MAE) of 0.19, and a Root Mean Squared Error (RMSE) of 1.51 for the validation dataset, 54.00% accuracy, precision of 0.97, recall of 0.50, F_Score of 0.66, MSE = 0.06, MAE = 3.24, and = 1.51 for the Farming-Pack motion capture (mocap) dataset. The computational framework with wearable device technology connected to ubiquitous systems, as well as statistical results, demonstrate that our proposed method is feasible and effective in solving the problem's constraints in a time series dataset that is acceptable and usable in a real rural farming environment for optimal solutions.

Comparison of Physical and System Factors Impacting Hydration Sensing in Leaves Using Terahertz Time-Domain and Quantum Cascade Laser Feedback Interferometry Imaging

To reduce the water footprint in agriculture, the recent push toward precision irrigation management has initiated a sharp rise in photonics-based hydration sensing in plants in a non-contact, non-invasive manner. Here, this aspect of sensing was employed in the terahertz (THz) range for mapping liquid water in the plucked leaves of Bambusa vulgaris and Celtis sinensis. Two complementary techniques, broadband THz time-domain spectroscopic imaging and THz quantum cascade laser-based imaging, were utilized. The resulting hydration maps capture the spatial variations within the leaves as well as the hydration dynamics in various time scales. Although both techniques employed raster scanning to acquire the THz image, the results provide very distinct and different information. Terahertz time-domain spectroscopy provides rich spectral and phase information detailing the dehydration effects on the leaf structure, while THz quantum cascade laser-based laser feedback interferometry gives insight into the fast dynamic variation in dehydration patterns.

Exploring innovation adoption behavior for sustainable development of Mediterranean tree crops

Introduction

The combination of knowledge, personal skills and company resources influences, all things being equal, such as the availability of new technologies, market conditions and other factors external to the company, farmers in their innovation choices. This study is an attempt to understand which psychological constructs influence the decision-making process of farmers specialized in typical Mediterranean crops with regard to innovation. Previous studies on the adoption of agricultural innovations have often considered socio economic characteristics and ignored the underlying motivational factors that influence the behavioral intention of farmers.

Methods

This study adopted three socio-psychological constructs, Attitude (ATT), Subjective Norm (SN), and Perceived Behavioral Control (PBC), derived from the Theory of Planned Behavior (TPB), and proposed three new constructs, Perceived Innovations Characteristics (PIC), Benefits (B), and Transferability (T), thus using an Extended Model of the Theory of Planned Behavior.

Results

The outcome of the multiple regression revealed that farmers' intention (I) to adopt sustainable irrigation innovations is positively influenced by attitude (ATT), subjective norm (SN), and perceived innovation characteristics (PIC). This last construct had mediating effects on the indirect relationships between PBC, benefits (B), transferability (T), and intention (I).

Discussion

The results provide numerous insights, useful both for outlining the demand for innovation and for calibrating future policies aimed at the primary sector, especially on the sustainable management of irrigation resources. In particular, the analyses carried out highlight the importance of factors external to the company as key levers in shaping the demand for innovations.

Achieving the nutrient reduction objective of the Farm to Fork Strategy. An assessment of CAP subsidies for precision fertilization and sustainable agricultural practices in Germany

The Farm to Fork Strategy of the EU aims at sustainable food systems. One objective of the Strategy is to reduce nutrient losses by at least 50% resulting in at least 20% less fertilizer use by 2030. To this end, Member States are expected to extend digital precision fertilization and sustainable agricultural practices through the Common Agricultural Policy. In this context, this article applies a qualitative governance analysis which aims to assess the extent to which the measures proposed by the Farm to Fork Strategy, i.e., digital precision fertilization and sustainable agricultural practices, contribute to the nutrient objective of the Farm to Fork Strategy. The article analyses how these measures are implemented through the Common Agricultural Policy in Germany and Saxony. Results show that the nutrient objective of the Farm to Fork Strategy itself offers shortcomings. Germany offers some, yet overall limited, support for sustainable agricultural practices and digital precision fertilization. Hence, the Common Agricultural Policy will to a limited extend only contribute to the objective of the Strategy. The results furthermore highlight some general shortcomings of digitalization as sustainability strategy in the agricultural sector including typical governance issues (rebound and enforcement problems), and point to the advantages of quantity-based policy instruments.

The social impact of cultivated and plant-based meats as radical innovations in the food chain: Views from Brazil, the United States and Europe

Cultivated and plant-based meats have been recognized as radical innovations that may revolutionize food production worldwide. Despite potentially being more sustainable than conventional meat, little is known about the consequences these innovations can bring to society. To help to clarify this topic, we studied the social impacts that cultivated and plant-based meats may bring to Brazil, the United States and Europe. Based on the perspective of 136 experts, our results are divided into market expectations, consumer access, consumer acceptance, impacts on farms, and business opportunities along the new chains. Experts generally predicted an optimistic picture of the social effects with several opportunities as alternative meats become available. However, the consequences for animal farmers seemed worrying in the experts' views. Overall, the opinion of Brazilian and American experts seemed more optimistic than that of Europeans. Our findings may be helpful for practitioners and people involved in rural policy interested in better guiding this transition process in the food production chain.

Can digital farming technologies enhance the willingness to buy products from current farming systems?

While current global agriculture allows for efficient food production, it brings environmental disadvantages, which resulted in a lack of public acceptance. Digital technologies (e.g., technologies that enable precision agriculture) have been suggested as a potential solution to reconcile environmental sustainability and yield increases. By embedding digital technologies into holistic farming system visualized through mission statements, this study tests the effect of different intensities of digitization, as well as environmental arguments on the willingness to buy food produced by farms in Germany. We use a 4 x 4 repeated measure experimental design surveying a representative sample of 2,020 German citizens recruited online. Our research framework captures the farming system (comparing low intensity of digitalization for a small or organic farm and low, medium, and high intensity of digitalization for large or conventional farms) and environmental arguments (comparing no arguments, and altruistic, egoistic, and biospheric arguments). The results show a negative effect of digital technologies on willingness to buy. However, this relationship turns positive when introducing environmental arguments. Furthermore, there is a moderation effect for respondents’ attitudes towards technologies that varies depending on whether altruistic, egoistic, or biospheric concerns were stated. The results indicate that digital technologies can increase willingness to buy products from both large and conventional farms, but not to the level of small farms and organic farms.

Intellectual property meets transdisciplinary co-design: prioritizing responsiveness in the production of new AgTech through located response-ability

This paper explores the complex relationship between intellectual property (IP) and the transdisciplinary collaborative design (co-design) of new digital technologies for agriculture (AgTech). More specifically, it explores how prioritizing the capturing of IP as a central researcher responsibility can cause disruptions to research relationships and project outcomes. We argue that boundary-making processes associated with IP create a particular context through which responsibility can, and must, be located and cultivated by researchers working within transdisciplinary collaborations. We draw from interview data and situated IP practices from a transdisciplinary co-design project in Aotearoa New Zealand to illustrate how IP is a fluid boundary-requiring-and-producing object that impels researchers into its management, and produces tensions that need to be noticed and skillfully navigated within research relations. We propose located response-ability as a conceptual tool and practice to reposition IP within the relations that make up a transdisciplinary co-design project, as opposed to prioritizing IP by default without recognizing its possible impacts on collaborative relations and other project aims and accountabilities. This can support researchers practicing responsible innovation in making everyday decisions on how to protect potential IP without disrupting the collaborative relations that make the creation of potential IP possible, and the existence of protected IP relevant and beneficial to project collaborators and wider societal actors. This may help to ensure that societal benefits can be generated, and positive science-society relationships prioritized and preserved, in the design of new AgTech.

The old, the new, or the old made new? Everyday counter-narratives of the so-called fourth agricultural revolution

Prevalent narratives of agricultural innovation predict that we are once again on the cusp of a global agricultural revolution. According to these narratives, this so-called fourth agricultural revolution, or agriculture 4.0, is set to transform current agricultural practices around the world at a quick pace, making use of new sophisticated precision technologies. Often used as a rhetorical device, this narrative has a material effect on the trajectories of an inherently political and normative agricultural transition; with funding, other policy instruments, and research attention focusing on the design and development of new precision technologies. A growing critical social science literature interrogates the promises of revolution. Engagement with new technology is likely to be uneven, with benefits potentially favouring the already powerful and the costs falling hardest on the least powerful. If grand narratives of change remain unchallenged, we risk pursuing innovation trajectories that are exclusionary, failing to achieve responsible innovation. This study utilises a range of methodologies to explore everyday encounters between farmers and technology, with the aim of inspiring further work to compile the microhistories that can help to challenge robust grand narratives of change. We explore how farmers are engaging with technology in practice and show how these interactions problematise a simple, linear notion of innovation adoption and use. In doing so, we reflect upon the contribution that the study of everyday encounters can make in setting more inclusionary, responsible pathways towards sustainable agriculture.

Knowledge networks to support youth engagement in sustainable food systems

Young people are on the front lines of transforming agriculture and food systems, coping with the social and economic impacts of COVID-19 as well as environmental and climate change effects which are likely to accelerate and intensify during their lifetimes. At the same time, young people across global contexts are increasingly emerging as visible agents of change in food systems, especially through networks that create, transform, and distribute food systems knowledge. This policy and practice review examines the role of youth as actors through food systems knowledge networks. Increasing youth participation in creating sustainable food systems for the future requires policies and practices that support food systems-related knowledge in two ways: (1) democratizing formal education systems; and (2) strengthening horizontal networks of grassroots research and innovation, including through traditional, ecological, local and community knowledge (TELCK). Food systems policies should be developed through dialogue with diverse knowledge systems, experiences, place-based needs, and aspirations of young people to maximize their participation in food systems policy development and evaluation.

Assessment of video see-through smart glasses for augmented reality to support technicians during milking machine maintenance

Smart glasses for augmented reality are digital technology under investigation in the agricultural sector. The potential of augmented reality was underlined, in some scientific contributions, as a support tool for farmers' activities and for the decision-making process. One of the most practical applications studied for augmented reality was in maintenance operations, where the use of smart glasses showed high capability. This work focuses on the evaluation of the performance and applicability of smart glasses with a video see-through display system and testing the device's available functions in agricultural frameworks. In addition, an augmented assistance scenario describing the main steps involved in the functioning of the maintenance operation was developed for milking machine inspection. The audio–video quality, battery life, detection capabilities of markers, and voice control interaction system were evaluated. The results showed the capabilities of smart glasses to reach augmented information from a long distance in a short time interval and to transmit audio and video with a high level of detail, allowing discrimination of small objects during remote assistance with reduced delay. The built maintenance scenario represents an example of augmented reality digital assistance application in the inspection and maintenance of the milking machine. The device performance and the proposed maintenance scenario underline the potential that augmented reality could have in the agricultural sector to assist and guide both farmers and technicians to timely problem solving. This solution fits into the agriculture 4.0 perspective, which is increasingly focused on digital transformation to improve farms’ efficiency and sustainability.

Toward digitalization futures in smallholder farming systems in Sub-Sahara Africa: A social practice proposal

This paper contributes to the digitalization of rural agriculture literature by proposing a social practice approach. Digitalization (practices) is conceived as an unfolding constellation of everyday farming activities manifested by practically conscious people meaningfully leveraging competences to integrate materials elements of life. Thirty-one expert key informants' interviews were conducted on experiences and pathways for the future of digital agriculture in Africa. Thematic analysis of the interviews revealed that materials (access to digital tools, enabling digital infrastructure, supporting social infrastructure), competencies (digital literacy among farmers and extension officers, IT and data education among populaces), and meanings (connecting digitization with local customs and norms and aligning digital tools with the values/perceptions of what farming is) are critical elements to establishing and embedding digital tools and services in everyday agriculture in Africa. Thus, I propose adopting a social practice approach (which focus on establishing and integrating materials, competencies, and meanings) to understanding, researching, and guiding processes of rural smallholder digitalization. The proposed approach, the first application of the social practice lens to smallholder digitalization, would allow for interventions that focus on establishing holistic and all-encompassing building blocks that bring digitalization practices to life. Specifically, the social practice proposal provides an outlook to move beyond the technologies –tools and services– of digitalization, to equally value the competencies required and meanings engendered in smallholder digital futures.

Monitoring System of the Mar Menor Coastal Lagoon (Spain) and Its Watershed Basin Using the Integration of Massive Heterogeneous Data

The tool created aims at the environmental monitoring of the Mar Menor coastal lagoon (Spain) and the monitoring of the land use of its watershed. It integrates heterogeneous data sources ranging from ecological data obtained from a multiparametric oceanographic sonde to agro-meteorological data from IMIDA's network of stations or hydrological data from the SAIH network as multispectral satellite images from Sentinel and Landsat space missions. The system is based on free and open source software and has been designed to guarantee maximum levels of flexibility and scalability and minimum coupling so that the incorporation of new components does not affect the existing ones. The platform is designed to handle a data volume of more than 12 million records, experiencing exponential growth in the last six months. The tool allows the transformation of a large volume of data into information, offering them through microservices with optimal response times. As practical applications, the platform created allows us to know the ecological state of the Mar Menor with a very high level of detail, both at biophysical and nutrient levels, being able to detect periods of oxygen deficit and delimit the affected area. In addition, it facilitates the detailed monitoring of the cultivated areas of the watershed, detecting the agricultural use and crop cycles at the plot level. It also makes it possible to calculate the amount of water precipitated on the watershed and to monitor the runoff produced and the amount of water entering the Mar Menor in extreme events. The information is offered in different ways depending on the user profile, offering a very high level of detail for research or data analysis profiles, concrete and direct information to support decision-making for users with managerial profiles and validated and concise information for citizens. It is an integrated and distributed system that will provide data and services for the Mar Menor Observatory.

Responsible robotics design-A systems approach to developing design guides for robotics in pasture-grazed dairy farming

Application of robotics and automation in pasture-grazed agriculture is in an emergent phase. Technology developers face significant challenges due to aspects such as the complex and dynamic nature of biological systems, relative cost of technology versus farm labor costs, and specific market characteristics in agriculture. Overlaying this are socio-ethical issues around technology development, and aspects of responsible research and innovation. There are numerous examples of technology being developed but not adopted in pasture-grazed farming, despite the potential benefits to farmers and/or society, highlighting a disconnect in the innovation system. In this perspective paper, we propose a "responsibility by design" approach to robotics and automation innovation, using development of batch robotic milking in pasture-grazed dairy farming as a case study. The framework we develop is used to highlight the wider considerations that technology developers and policy makers need to consider when envisaging future innovation trajectories for robotics in smart farming. These considerations include the impact on work design, worker well-being and safety, changes to farming systems, and the influences of market and regulatory constraints.

Future agricultural systems and the role of digitalization for achieving sustainability goals. A review

By leveraging a wide range of novel, data-driven technologies for agricultural production and agri-food value chains, digital agriculture presents potential enhancements to sustainability across food systems. Accordingly, digital agriculture has received considerable attention in policy in recent years, with emphasis mostly placed on the potential of digital agriculture to improve efficiency, productivity and food security, and less attention given to how digitalization may impact other principles of sustainable development, such as biodiversity conservation, soil protection, and human health, for example. Here, we review high-level policy and law in the German and European context to highlight a number of important institutional, societal, and legal preconditions for leveraging digital agriculture to achieve diverse sustainability targets. Additionally, we combine foresight analysis with our review to reflect on how future frame conditions influencing agricultural digitalization and sustainability could conceivably arise. The major points are the following: (1) some polices consider the benefits of digital agriculture, although only to a limited extent and mostly in terms of resource use efficiency; (2) law as it applies to digital agriculture is emerging but is highly fragmented; and (3) the adoption of digital agriculture and if it is used to enhance sustainability will be dependent on future data ownership regimes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13593-022-00792-6.

Rice Seedling Detection in UAV Images Using Transfer Learning and Machine Learning

To meet demand for agriculture products, researchers have recently focused on precision agriculture to increase crop production with less input. Crop detection based on computer vision with unmanned aerial vehicle (UAV)-acquired images plays a vital role in precision agriculture. In recent years, machine learning has been successfully applied in image processing for classification, detection and segmentation. Accordingly, the aim of this study is to detect rice seedlings in paddy fields using transfer learning from two machine learning models, EfficientDet-D0 and Faster R-CNN, and to compare the results to the legacy approach—histograms of oriented gradients (HOG)-based support vector machine (SVM) classification. This study relies on a significant UAV image dataset to build a model to detect tiny rice seedlings. The HOG-SVM classifier was trained and achieved an F1-score of 99% in both training and testing. The performance of HOG-SVM, EfficientDet and Faster R-CNN models, respectively, were measured in mean average precision (mAP), with 70.0%, 95.5% and almost 100% in training and 70.2%, 83.2% and 88.8% in testing, and mean Intersection-over-Union (mIoU), with 46.5%, 67.6% and 99.6% in training and 46.6%, 57.5% and 63.7% in testing. The three models were also measured with three additional datasets acquired on different dates to evaluate model applicability with various imaging conditions. The results demonstrate that both CNN-based models outperform HOG-SVM, with a 10% higher mAP and mIoU. Further, computation speed is at least 1000 times faster than that of HOG-SVM with sliding window. Overall, the adoption of transfer learning allows for rapid establishment of object detection applications with promising performance.

A Fruit Colour Development Index (CDI) to Support Harvest Time Decisions in Peach and Nectarine Orchards

Fruit skin colour is one of the most important visual fruit quality parameters driving consumer preferences. Proximal sensors such as machine vision cameras can be used to detect skin colour in fruit visible in collected images, but their accuracy in variable orchard light conditions remains a practical challenge. This work aimed to derive a new fruit skin colour attribute—namely a Colour Development Index (CDI), ranging from 0 to 1, that intuitively increases as fruit becomes redder—to assess colour development in peach and nectarine fruit skin. CDI measurements were generated from high-resolution images collected on both east and west sides of the canopies of three peach and one nectarine cultivars using the commercial mobile platform Cartographer (Green Atlas). Fruit colour (RGB values) was extracted from the central pixels of detected fruit and converted into a CDI. The repeatability of CDI measurements under different light environments was tested by scanning orchards at different times of the day. The effects of cultivar and canopy side on CDI were also determined. CDI data was related to the index of absorbance difference (IAD)—an index of chlorophyll degradation that was correlated with ethylene emission—and its response to time from harvest was modelled. The CDI was only significantly altered when measurements were taken in the middle of the morning or in the middle of the afternoon, when the presence of the sun in the image caused significant alteration of the image brightness. The CDI was tightly related to IAD, and CDI values plateaued (0.833 ± 0.009) at IAD ≤ 1.20 (climacteric onset) in ‘Majestic Pearl’ nectarine, suggesting that CDI thresholds show potential to be used for harvest time decisions and to support logistics. In order to obtain comparable CDI datasets to study colour development or forecast harvest time, it is recommended to scan peach and nectarine orchards at night, in the early morning, solar noon, or late afternoon. This study found that the CDI can serve as a standardised and objective skin colour index for peaches and nectarines.

A bibliometric and thematic approach to agriculture 4.0

Researchers are developing digital solutions for agriculture. Humanity has perfected agriculture throughout history because this activity is fundamental to our existence. The agricultural sector is currently incorporating new technologies from other areas. This phenomenon is agriculture 4.0. However, a challenge to research is the integration of technologies from different knowledge fields, and this has caused theoretical and practical difficulties. Thus, our purpose with this study has been to understand the core agriculture 4.0 research themes. We have used a bibliometric analysis, and guided the data collection by the PRISMA protocol. VosViewer and Bibliometrix software generated the results. We found two main research fronts, one focussed on agriculture 4.0 development, and another on the impacts of agriculture 4.0, which may be positive or negative. We found 21 main keywords or topics researched in agriculture 4.0 related to these research fronts. These themes are within five different axes. We managed to establish a good understanding of the topics around agriculture 4.0. Future studies could focus on the responsible development of digital solutions for agriculture. This is because the social, environmental, and economic impacts of these new solutions may be positive or negative. We conclude that digital agriculture is the node technologies integration for the automation of agricultural activities.

Deep Learning-Based Complete Coverage Path Planning With Re-Joint and Obstacle Fusion Paradigm

With the introduction of autonomy into the precision agriculture process, environmental exploration, disaster response, and other fields, one of the global demands is to navigate autonomous vehicles to completely cover entire unknown environments. In the previous complete coverage path planning (CCPP) research, however, autonomous vehicles need to consider mapping, obstacle avoidance, and route planning simultaneously during operating in the workspace, which results in an extremely complicated and computationally expensive navigation system. In this study, a new framework is developed in light of a hierarchical manner with the obtained environmental information and gradually solving navigation problems layer by layer, consisting of environmental mapping, path generation, CCPP, and dynamic obstacle avoidance. The first layer based on satellite images utilizes a deep learning method to generate the CCPP trajectory through the position of the autonomous vehicle. In the second layer, an obstacle fusion paradigm in the map is developed based on the unmanned aerial vehicle (UAV) onboard sensors. A nature-inspired algorithm is adopted for obstacle avoidance and CCPP re-joint. Equipped with the onboard LIDAR equipment, autonomous vehicles, in the third layer, dynamically avoid moving obstacles. Simulated experiments validate the effectiveness and robustness of the proposed framework.

Biocompatible Wearable Electrodes on Leaves toward the On-Site Monitoring of Water Loss from Plants

Impedimetric wearable sensors are a promising strategy for determining the loss of water content (LWC) from leaves because they can afford on-site and nondestructive quantification of cellular water from a single measurement. Because the water content is a key marker of leaf health, monitoring of the LWC can lend key insights into daily practice in precision agriculture, toxicity studies, and the development of agricultural inputs. Ongoing challenges with this monitoring are the on-leaf adhesion, compatibility, scalability, and reproducibility of the electrodes, especially when subjected to long-term measurements. This paper introduces a set of sensing material, technological, and data processing solutions that overwhelm such obstacles. Mass-production-suitable electrodes consisting of stand-alone Ni films obtained by well-established microfabrication methods or ecofriendly pyrolyzed paper enabled reproducible determination of the LWC from soy leaves with optimized sensibilities of 27.0 (Ni) and 17.5 kΩ %-1 (paper). The freestanding design of the Ni electrodes was further key to delivering high on-leaf adhesion and long-term compatibility. Their impedances remained unchanged under the action of wind at velocities of up to 2.00 m s-1, whereas X-ray nanoprobe fluorescence assays allowed us to confirm the Ni sensor compatibility by the monitoring of the soy leaf health in an electrode-exposed area. Both electrodes operated through direct transfer of the conductive materials on hairy soy leaves using an ordinary adhesive tape. We used a hand-held and low-power potentiostat with wireless connection to a smartphone to determine the LWC over 24 h. Impressively, a machine-learning model was able to convert the sensing responses into a simple mathematical equation that gauged the impairments on the water content at two temperatures (30 and 20 °C) with reduced root-mean-square errors (0.1% up to 0.3%). These data suggest broad applicability of the platform by enabling direct determination of the LWC from leaves even at variable temperatures. Overall, our findings may help to pave the way for translating "sense-act" technologies into practice toward the on-site and remote investigation of plant drought stress. These platforms can provide key information for aiding efficient data-driven management and guiding decision-making steps.

Lameness in Dairy Cow Herds: Disease Aetiology, Prevention and Management

As livestock production systems have changed to intensive commercial structures to meet the increasing demand for animal-based products, there has been an increase in food production diseases, subsequently resulting in animal welfare issues. After mastitis and infertility, lameness is one of the three major issues affecting dairy cattle globally, resulting in reduced productivity, economic losses, and animal welfare problems. Lameness is associated with reduced milk yield, lack of weight gain, poor fertility, and frequently, animal culling. Environmental (temperature, humidity) and animal risk factors contribute to disease severity, making this multifaceted disease difficult to eradicate and control. As such, prevalence rates of lameness in dairy herds ranges from 17% to 35% globally. Clinical lameness is often treated with antibiotic therapy, which is undesirable in food-producing animals, as outlined in the One Health and the European Farm to Fork food sustainability goals. Lameness is not a single disease in dairy cows but is the manifestation a range of issues, making lameness control one of the greatest challenges in dairy farming. Lameness prevention, therefore, must be a key focus of farm management and sustainable food production. There is an urgent need to establish farm-level aetiology of disease, promote the recognition of lameness, and implement effective control measures to lower incidence and transmission of disease within herds.

Developing 'Smart' Dairy Farming Responsive to Farmers and Consumer-Citizens: A Review

Innovation has resulted in more dairy products being produced with less inputs than ever before. It has also affected how animals are raised, the structure of the sector and the nature of products produced. Not all impacts have been positive. As disruptive technologies-such as precision farming and robotics-herald significant change, it is timely to reflect on the perspectives of different actors on innovations within the sector. Drawing on a review of academic literature, this paper considers farmers' and consumer-citizens' perspectives; as expected, their diverse knowledge, interests and values surface a range of perspectives. To provide focus to the study, it examines technologies across three stages of the dairy production cycle: breeding, feeding and milking. It finds that consumer-citizen and farmer perspectives have been examined by researchers in several countries, using a variety of methods, across a range of technologies. It finds both areas of agreement and tension within and between consumer-citizen and producer cohorts. While differences in knowledge account for some variation, differences in values are also significant. The extent to which efforts can and should be put into addressing differences is raised as a point for reflection.

Communicating the Utility of the Microbiome and Bioinformatics to Small Flock Poultry Producers

The use of “omics” has become widespread across poultry production, from breeding to management to bird health to food safety and everywhere in between.  While the conventional poultry industry has become more exposed to the power and utility of “omic” technologies, smaller poultry flock producers typically do not have this same level of experience. Because smaller, nonconventional poultry production is a growing portion of the overall poultry market, it is important that they also have educational access to these research tools and the resultant data. While small flock producers are dedicated and knowledgeable farmers, their knowledge of these newer technologies may be limited at best, and it is the task of academic researchers to communicate the importance of these “omic” tools and how the omic data can improve a variety of different aspects of their operations. This review discusses ways to effectively communicate complex microbiota and microbial genome sequence data to small flock producers and transforming this data into meaningful and applicable information that they can utilize to inform beneficial management decisions.

Logistics and Agri-Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy

This paper examines the current challenges faced by logistics with a focus on the agri-food sector. After outlining the context, a review of the literature on the relationship between logistics and strategic management in gaining and increasing competitiveness in the agri-food sector is conducted. In particular, the flow of the paper is as follows: after examining the aforementioned managerial problem and its broader repercussions, the paper proceeds to address two main research questions. First, how and by which tools can digitization contribute to improving supply chain management and sustainability in logistics? Second, what are the main managerial and strategic implications and consequences of this for the agri-food sector in terms of efficiency, effectiveness, cost reduction, and supply chain optimization? Finally, the paper presents Italy as a case study, chosen both for its peculiar internal differences in logistical infrastructures and entrepreneurial management between Northern and Southern regions (which could be at least partially overcome with the use of new technologies and frameworks) and for the importance of the agri-food sector for the domestic economy (accounting about 25% of the country’s GDP), on which digitization should have positive effects in terms of value creation and sustainability.

The social and ethical impacts of artificial intelligence in agriculture: mapping the agricultural AI literature

This paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through a thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this paper aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. It aim is to analyse these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed.

Industry 4.0 and the small business something behind the technology: A literature review

Small and medium-sized enterprises (SMEs) are especially vulnerable to technology issues, often because they lack the financial resources or the skills to properly exploit new technologies.This paper presents the results of a study that explores the link between Industry 4.0 and SMEs through a systematic literature review. The results show that this link is dominated by themes that can be grouped into the following categories: "Industrial revolutions", "Technology", "Management", "Operations Management/ Industrial Engineering", "Social issues/ Sustainability", and "Methodology". The study shows the relevance of the topics Management, Social Issues, and Sustainability, which is not then reflected in publications of articles on Industry 4.0 in journals in these areas. Eventually, the establishment of partnerships between research teams in these areas of knowledge and the teams studying Industry 4.0 could mitigate this insufficiency. The themes Social Issues and Sustainability are underrepresented and therefore an effort is needed to develop research on the impacts of these themes on Industry 4.0 and vice versa.

A Bibliometric Network Analysis of Recent Publications on Digital Agriculture to Depict Strategic Themes and Evolution Structure

The agriculture sector is one of the backbones of many countries’ economies. Its processes have been changing to enable technology adoption to increase productivity, quality, and sustainable development. In this research, we present a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, we used 4694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis of the literature using SciMAT software with the support of the PICOC protocol. Our findings presented 22 strategic themes related to Digital Agriculture, such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAV) and Climate-smart Agriculture (CSA), among others. The thematic network structure of the nine most important clusters (motor themes) was presented and an in-depth discussion was performed. The thematic evolution map provides a broad perspective of how the field has evolved over time from 1994 to 2020. In addition, our results discuss the main challenges and opportunities for research and practice in the field of study. Our findings provide a comprehensive overview of the main themes related to Digital Agriculture. These results show the main subjects analyzed on this topic and provide a basis for insights for future research.

Patterns of Inequalities in Digital Agriculture: A Systematic Literature Review

Digitalization of agriculture is often hailed as the next agricultural revolution. However, little is yet known about its social impacts and power effects. This review addresses this research gap by analyzing patterns of inequality linked to the development and adoption of digital technologies in agriculture and reviewing the strategies developed to reduce these inequalities and challenge the power relations in which they are embedded. Analysis of 84 publications found through a systematic literature review identified five patterns of inequality: (1) in digital technology development; (2) in the distribution of benefits from the use of digital technologies; (3) in sovereignty over data, hardware and digital infrastructure; (4) in skills and knowledge (‘digital literacy’); and (5) in problem definition and problem-solving capacities. This review also highlights the existence of emancipatory initiatives that are applying digital technologies to challenge existing inequalities and to advance alternative visions of agriculture. These initiatives underscore the political nature of digital agriculture; however, their reach is still quite limited. This is partly due to the fact that existing inequalities are structural and represent expressions of corporate power. From such a perspective, digitalization in agriculture is not a ‘revolution’ per se; rather, digital technologies mirror and reproduce existing power relations.

Sustainable food supply chains: overcoming key challenges through digital technologies

Purpose

The purpose of this paper is to offer a consolidative approach in exploring the potential contribution of digital technologies in sustainable supply chain management (SSCM) for the sustainable performance of food supply chain business, through the circular economy concepts.

Design/methodology/approach

As a single case study, this qualitative, interpretivist research was based on one of the largest food producers in the United Kingdom. The research utilises semi-structured interviews and applies thematic analysis to offer rich insights into SSCM challenges and their relationship with the business performance, through ten in-depth interviews.

Findings

Findings derived from thematic analysis of the interview transcripts suggest four main critical success factors underpinning SSCM practices and businesses performance – i.e. business continuity, waste reduction, performance measurement approach, and organisational learning, which could use the help of digital technologies to improve. This led to seven propositions to be addressed in the future research.

Originality/value

This research offers real, practical insights into SSCM challenges, within the context of food supply chain and explores the potential of digital technologies in overcoming them. Accordingly, the primary contribution of this work is grounded in the identification of critical success factors in SSCM for food supply chains (FSC). Hence, this work contributes further to the literature on SSCM, as well as circular economy, by providing a study of a business in the context of the highly pertinent and valuable food industry.

Smart Indoor Farms: Leveraging Technological Advancements to Power a Sustainable Agricultural Revolution

Conventional farming necessitates a large number of resources and infrastructure such as land, irrigation, manpower to manage farms, etc. Modern initiatives are required to automate conventional farms. Smart indoor farms offer the potential to remedy the shortfalls of conventional farms by providing a controlled, intelligent, and smart environment. This paper presents a three-dimensional perspective consisting of soilless farming, energy harvesting, and smart technologies, which could be considered as the three important characteristics of smart indoor farms. A six-layer smart indoor farms architecture has also been proposed, which explains how data are collected using various sensors and devices and then transmitted onto the cloud infrastructure for further analysis and control through various layers. Artificial lighting, smart nutrition management, and artificial climate control, to name a few, are some of the important requirements for smart indoor farms while considering control and service management factors. The major bottleneck in installing such systems is both the economical and the technical constraints. However, with the evolution of technology (and when they become widely available in the near future), a more favourable farming scenario may emerge. Furthermore, smart indoor farms could be viewed as a potential answer for meeting the demands of a sustainable agricultural revolution as we move closer to Agriculture 4.0. Finally, in order to adapt smart indoor farms and their study scope, our work has presented various research areas to potential researchers.

Bridging the Gaps in Traceability Systems for Fresh Produce Supply Chains: Overview and Development of an Integrated IoT-Based System

Traceability, namely the ability to access information about a product and its movement across all stages of the supply chain, has been emerged as a key criterion of a product’s quality and safety. Managing fresh products, such as fruits and vegetables, is a particularly complicated task, since they are perishable with short shelf lives and are vulnerable to environmental conditions. This makes traceability of fresh produce very significant. The present study provides a brief overview of the relative literature on fresh produce traceability systems. It was concluded that the commercially available traceability systems usually neither cover the entire length of the supply chain nor rely on open and transparent interoperability standards. Therefore, a user-friendly open access traceability system is proposed for the development of an integrated solution for traceability and agro-logistics of fresh products, focusing on interoperability and data sharing. Various Internet of Things technologies are incorporated and connected to the web, while an android-based platform enables the monitoring of the quality of fruits and vegetables throughout the whole agri-food supply chain, starting from the field level to the consumer and back to the field. The applicability of the system, named AgroTRACE, is further extended to waste management, which constitutes an important aspect of a circular economy.

Commercial techniques for preserving date palm (Phoenix dactylifera) fruit quality and safety: A review

The popularity of date palm (Phoenix dactylifera) fruit is increasing, therefore the demand for high-quality date palm fruit with less or no chemical treatment is the topic of interest for date producers and consumers. The quality of date palm fruit is much dependent on its postharvest handling and processing. For preventing the degradation and maintenance of the high quality of dates during the storage an appropriate harvest and post-harvest processes are required. The process should control the biotic and abiotic factors like insects, fungus, temperature, as well as handling and processing of dates. Therefore, in this work, we reviewed the literature related to the protection of date fruits during their post-harvest life. The commercially viable advance and updated techniques that can be used to avoid storage losses and problems while keeping fruit quality (nutritional, color, flavor, and texture) and microbial safety under optimal conditions are discussed.

Entrepreneurial Talent Building for 21st Century Agricultural Innovation

Agricultural innovation is a key component of the global economy and enhances food security, health, and nutrition. Current innovation efforts focus mainly on supporting the transition to sustainable food systems, which is expected to harness technological advances across a range of fields. In this Nano Focus, we discuss how such efforts would benefit from not only supporting farmer participation in deciding transition pathways but also in fostering the interdisciplinary training and development of entrepreneurial-minded farmers, whom we term "AgTech Pioneers", to participate in cross-sector agricultural innovation ecosystems as cocreators and informed users of developing and future technologies. Toward this goal, we discuss possible strategies based on talent development, cross-disciplinary educational and training programs, and innovation clusters to build an AgTech Pioneer ecosystem, which can help to reinvigorate interest in farming careers and to identify and address challenges and opportunities in agriculture by accelerating and applying advances in nanoscience, nanotechnology, and related fields.

Challenges and Opportunities of Coal Phase-Out in Western Macedonia

As part of the European Green Deal, the EU aims to become climate-neutral and reach net-zero greenhouse gas emissions by 2050. Ιn this context, EU member states are required to develop a national strategy to achieve the required emissions reductions under the Paris Agreement and EU climate goals. Western Macedonia is a region in North-western Greece with its economy largely dominated by lignite mining, lignite-fired power plants and district heating systems. In 2019, the Greek Government set the goal of withdrawing all lignite plants by 2028, with most units being withdrawn already by 2023. This decision has had an immense socio-economic impact on the region of Western Macedonia. This research work reflects the current situation at the socio-economic and socio-political level in Western Macedonia and discusses the policies implemented in the context of the lignite phase-out process to ensure a just transition for households and businesses of the region. Although there is not a ‘one-size-fits-all’ blueprint for successful low-carbon transitions of high-carbon intensive regional economies, the main target of our paper is understanding the impacts, challenges and opportunities of decarbonizing Western Macedonia.

Review: Anticipating alternative trajectories for responsible Agriculture 4.0 innovation in livestock systems

Technological change has been a constant feature of livestock systems leading to the third agricultural 'green' revolution of the mid-20th century. Digital technologies are now leading us into the fourth agricultural revolution, where sustainable food production is supported by technologies that collect data useful for farm and supply chain performance improvement, along with task automation and compliance. However, the potential benefits of digital agricultural futures are uncertain and plagued by unrealized expectations of previous innovations. The aims of this paper are to articulate current trends in technology and livestock systems and anticipate future trajectories for Agriculture 4.0 in relation to meeting sustainability and animal welfare outcomes for livestock systems. We use a 'Futures Triangle' approach to review the role of technology in livestock systems. The main findings are that previous work envisioning technological livestock futures have favoured pull of the future factors (techno-optimists) or weight of the past (techno-pessimists), rather than a balance of pull, push and weighting factors. Responsible Agriculture 4.0 innovation requires public-private collaboration of innovation system stakeholders, including policy makers, farmers, consumers, as well as technology developers, to enable development of transition pathways from a systems perspective. The use of responsible innovation processes, including anticipation on alternative futures, should also be built into innovation processes to support critical reflection on technological trajectories and related innovation system consequences, both desirable and undesirable.

Agriculture 4.0: Is Sub-Saharan Africa Ready?

A fourth agricultural revolution, termed agriculture 4.0, is gradually gaining ground around the globe. It encompasses the application of smart technologies such as artificial intelligence, biotechnology, the internet of things (IoT), big data, and robotics to improve agriculture and the sustainability of food production. To date, narratives around agriculture 4.0 associated technologies have generally focused on their application in the context of higher-income countries (HICs). In contrast, in this perspective, we critically assess the place of sub-Saharan Africa (SSA) in this new technology trajectory, a region that has received less attention with respect to the application of such technologies. We examine the continent’s readiness based on a number of dimensions such as scale, finance, technology leapfrogging, institutions and governance, education and skills. We critically reviewed the challenges, opportunities, and prospects of adopting agriculture 4.0 technologies in SSA, particularly with regards to how smallholder farmers in the region can be involved through a robust strategy. We find that whilst potential exist for agriculture 4.0 adoption in SSA, there are gaps in knowledge, skills, finance, and infrastructure to ensure successful adoption.