A systematic literature review on machine learning applications for sustainable agriculture supply chain performance

Agriculture plays an important role in sustaining all human activities. Major challenges such as overpopulation, competition for resources poses a threat to the food security of the planet. In order to tackle the ever-increasing complex problems in agricultural production systems, advancements in smart farming and precision agriculture offers important tools to address agricultural sustainability challenges. Data analytics hold the key to ensure future food security, food safety, and ecological sustainability. Disruptive information and communication technologies such as machine learning, big data analytics, cloud computing, and blockchain can address several problems such as productivity and yield improvement, water conservation, ensuring soil and plant health, and enhance environmental stewardship. The current study presents a systematic review of machine learning (ML) applications in agricultural supply chains (ASCs). Ninety three research papers were reviewed based on the applications of different ML algorithms in different phases of the ASCs. The study highlights how ASCs can benefit from ML techniques and lead to ASC sustainability. Based on the study findings an ML applications framework for sustainable ASC is proposed. The framework identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability

Can Industry 5.0 Technologies Overcome Supply Chain Disruptions? - A Perspective Study on Pandemics, War, and Climate Change Issues

Industry 5.0 (I5.0) is the next industrial revolution that will leverage human intervention in collaboration with intelligent, logical, and smart machines to attain even more user-preferred and resource-efficient manufacturing and supply chain solutions. The main aim of this article is to study I5.0 technologies in supply chains when these are affected by disruptive phenomena such as those created by wars, climate change or pandemics. A systematic literature review methodology was conducted to understand the present knowledge connected with this theme. This study summarises 194 research articles from the period 2009 to 2022 to understand the present knowledge connected with this theme. The research findings show a significant gap related to the adoption of I5.0 technologies to prevent or overcome supply chain disruptions. 194 articles, including journal and review articles, were identified in the literature. The study provides a novel and insightful concept related to I5.0 within the context of supply chain disruptions. The potential applications of I5.0 and Industry 4.0 are elaborately discussed in three areas, namely: (1) disruptions in supply chains due to pandemics; (2) disruptions in supply chains due to war; and (3) disruptions in supply chains due to climate change. Finally, this study highlights research implications and proposes future research avenues that will contribute to further exploring the adoption of I5.0 technologies to prevent, manage and overcome disruptions in supply chains

Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture

[EN] The term "Agri-Food 4.0" is an analogy to the term Industry 4.0; coming from the concept "agriculture 4.0". Since the origins of the industrial revolution, where the steam engines started the concept of Industry 1.0 and later the use of electricity upgraded the concept to Industry 2.0, the use of technologies generated a milestone in the industry revolution by addressing the Industry 3.0 concept. Hence, Industry 4.0, it is about including and integrating the latest developments based on digital technologies as well as the interoperability process across them. This allows enterprises to transmit real-time information in terms behaviour and performance. Therefore, the challenge is to maintain these complex networked structures efficiently linked and organised within the use of such technologies, especially to identify and satisfy supply chain stakeholders dynamic requirements. In this context, the agriculture domain is not an exception although it possesses some specialities depending from the domain. In fact, all agricultural machinery incorporates electronic controls and has entered to the digital age, enhancing their current performance. In addition, electronics, using sensors and drones, support the data collection of several agriculture key aspects, such as weather, geographical spatialization, animals and crops behaviours, as well as the entire farm life cycle. However, the use of the right methods and methodologies for enhancing agriculture supply chains performance is still a challenge, thus the concept of Industry 4.0 has evolved and adapted to agriculture 4.0 in order analyse the behaviours and performance in this specific domain. Thus, the question mark on how agriculture 4.0 support a better supply chain decision-making process, or how can help to save time to farmer to make effective decision based on objective data, remains open. Therefore, in this survey, a review of more than hundred papers on new technologies and the new available supply chains methods are analysed and contrasted to understand the future paths of the Agri-Food domain.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCARISE-2015.Lezoche, M.; Hernández, JE.; Alemany Díaz, MDM.; Panetto, H.; Kacprzyk, J. (2020). Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture. Computers in Industry. 117:1-15. https://doi.org/10.1016/j.compind.2020.103187S115117Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: A review. 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Evaluating the intention to use Industry 5.0 (I5.0) drones for cleaner production in Sustainable Food Supply Chains:an emerging economy context

YesPurpose – The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains. Design/methodology/approach – We used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model (PLS-SEM) was conducted to assess the research’s hypothesised relationships. Findings – We provide empirical evidence to support the contributions of I5.0 drones for cleaner production. Our findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations such as reducing plant diseases which invariably enhances cleaner production. However, there is less inclination to drones adoption if the aim was pollution reduction, predicting seasonal output and addressing workers health and safety challenges. Our findings outline the need for awareness to promote the use of drones for addressing workers hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies. Originality – This is the first study to address I5.0 drones' adoption using a sustainability model. We contribute to existing literature by extending the sustainability model to identify the contributions of drones use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators

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The world is confronted with the grand challenge of food insecurity amidst growing populations and the climate crisis. Artificial intelligence (AI) deployed in agricultural decision support systems (AgriDSS) raises both hopes and concerns for increasing agricultural productivity in sustainable ways. In this paper, we conduct a scoping review to uncover the roadblocks to the use of AI-supported AgriDSS in sustainable agriculture. Based on the corpus of 121 articles, we find that the effective use of AI-supported AgriDSS is hindered at technical, social, ethical, and ecological levels. Then, drawing on the experiential learning perspective, we propose how conjoint experiential learning (CEL) can enhance sustainable agricultural practices by enhancing both AI and human learning and overcoming roadblocks in using AgriDSS. Based on this conceptual framework, we build a research agenda that suggests blind spots and possible directions for future research

Digitalization in food supply chains: A bibliometric review and key-route main path analysis

Technological advances such as blockchain, artificial intelligence, big data, social media, and geographic information systems represent a building block of the digital transformation that supports the resilience of the food supply chain (FSC) and increases its efficiency. This paper reviews the literature surrounding digitalization in FSCs. A bibliometric and key-route main path analysis was carried out to objectively and analytically uncover the knowledge development in digitalization within the context of sustainable FSCs. The research began with the selection of 2140 articles published over nearly five decades. Then, the articles were examined according to several bibliometric metrics such as year of publication, countries, institutions, sources, authors, and keywords frequency. A keyword co-occurrence network was generated to cluster the relevant literature. Findings of the review and bibliometric analysis indicate that research at the intersection of technology and the FSC has gained substantial interest from scholars. On the basis of keyword co-occurrence network, the literature is focused on the role of information communication technology for agriculture and food security, food waste and circular economy, and the merge of the Internet of Things and blockchain in the FSC. The analysis of the key-route main path uncovers three critical periods marking the development of technology-enabled FSCs. The study offers scholars a better understanding of digitalization within the agri-food industry and the current knowledge gaps for future research. Practitioners may find the review useful to remain ahead of the latest discussions of technologyenabled FSCs. To the authors’ best knowledge, the current study is one of the few endeavors to explore technology-enabled FSCs using a comprehensive sample of journal articles published during the past five decades

Smart Technology Trends, Smart Supply Chain Management Implementation, and Smart Supply Chain Innovation Performance in Developing and Developed Economies

Many companies and scholars predict that supply chain configuration will undergo a significant adjustment during this period of change in a digitally driven future. The supply chain and management industry view these risks as including the rising frequency of disruptions to the global trading system caused by both endogenous and exogenous risks, including extreme weather events, pandemics, cybersecurity threats, and financial crises, as well as the widespread use of technology created during the Fourth Industrial Revolution. Businesses that survive the upcoming changes in customer behavior will have invested in digitization and diversity. The researcher determines the association between smart supply chain management implementation and smart supply chain innovation performance, mediated by smart technology trends in developing and developed countries, using a descriptive quantitative approach. Results show that the performance of smart supply chain innovation and smart supply chain management are not correlated. Furthermore, smart supply chain management's ability to mediate smart technological advances is notably lacking. As a result, the researcher produced an implementation strategy to improve the optimization of smart technological trends in the smart supply chain, in both developed and developing nations