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Article

Circular Economy for Supply Chain in Agriculture with Technology: A Literature Review

Luis Oswaldo Rodríguez Mañay1★★ Corresponding author

  1. 1Posdoctoral Program in Law, Economics, and Plural Society, Universidad Andina Simón Bolívar, Sede Ecuador.

CORRESPONDENCE

Luis Oswaldo Rodríguez Mañay

Phd Posdoctoral Program in Law, Economics, and Plural Society, Universidad Andina Simón Bolívar, Sede Ecuador.

lorodriguez@uce.edu.ec

Received: 09-02-2026; Revised: 24-04-2026; Accepted: 19-06-2026.

Volume 15, Issue 2 · pp. 570–582 · PUBLISHED May-Aug 2026 · DOI: 10.5530/jscires.20260260

View on JSR original site ↗

ABSTRACT

This study examines the role of digital technologies in enabling the transition to a Circular Economy (CE) within Agricultural Supply Chains (ASCs), identifying research trends, collaboration networks, and systemic barriers. A scientometric review of 277 publications from Scopus and Web of Science (WoS) (2009-2024) was conducted, using text mining and the Tree of Science (ToS) algorithm to map scientific production and disruptive innovations. The results indicate that Italy, the UK, and India lead research output in this field. Technologies such as blockchain, IoT (Internet of Things), and artificial intelligence emerge as key enablers for enhancing traceability, reducing waste, and optimizing resources. However, significant barriers persist, including scalabity issues, regulatory fragmentation, and limited cross-sector collaboration. The study concludes that effective implementation of circular models in ASCs requires integrated policies, longitudinal studies, and global partnerships to foster technological adoption and adaptive governance. This work synthesizes fragmented literature, highlights divergent hypotheses, and provides actionable insights for aligning CE strategies with the Sustainable Development Goals (SDGs).

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INTRODUCTION

The transition to a Circular Economy (CE) has emerged as a pivotal paradigm for achieving sustainability, driven by the urgent need to decouple economic growth from environmental degradation (Geissdoerfer et al., 2017; Ghisellini et al., 2016). CE principles -eliminating waste through design, maintaining products in use, and regenerating natural systems-offer transformative potential across sectors, particularly in agriculture, where supply chains face escalating challenges from climate change, resource scarcity, and inefficiencies (FAO, 2019; Kirchherr et al., 2017). Despite its promise, CE implementation encounters significant barriers, including technological gaps, regulatory fragmentation, and cultural resistance (Korhonen et al., 2018; A. Kumar et al., 2024).

These challenges in CE implementation are particularly evident in Agricultural Supply Chains (ASCs), which are especially critical yet vulnerable. ASCs contribute significantly to global greenhouse gas emissions while simultaneously facing persistent inefficiencies, post-harvest losses, and fragmented coordination among stakeholders (Gokarn and Kuthambalayan, 2017; Vermeulen et al., 2012). Although emerging technologies such as blockchain, Internet of Things (IoT), and artificial intelligence are increasingly recognized as enablers of circular practices -enhancing traceability, optimizing resource use, and reducing waste- their adoption remains uneven due to high costs, limited infrastructure and insufficient policy support (Kamble et al., 2020; Rejeb et al., 2021; Nayal et al., 2021; Sharma et al., 2021).

While previous studies have identified multiple gaps, including fragmented research streams, limited cross-sector collaboration, and a lack of longitudinal perspectives, a central gap remains insufficiently addressed: the absence of a comprehensive and integrated mapping of how digital technologies enable the implementation of CE within ASCs (Barbosa et al., 2025). This limitation restricts a systemic understanding of how technological innovations can effectively support circular transformation in agricultural systems (Ellahi et al., 2024; Marku et al., 2024).

To address this issue, this study adopts a scientometric approach. Scientometric analysis is particularly suitable for examining more than 15 years of dispersed literature, as it enables the identification of research evolution, thematic clusters, and collaboration networks. Compared to traditional narrative reviews, this method provides a more systematic and objective mapping of an emerging and fragmented research field.

Accordingly, this study aims to systematically analyze the intersection of CE, ASCs, and digital technologies through a scientometric review of publications indexed in Scopus and Web of Science (WoS) between 2009 and 2024. Specifically, it seeks to identify key drivers and barriers, examine the role of emerging technologies in enabling circular supply chains, and provide a structured overview of research trends and future directions. This work contributes by synthesizing fragmented literature, highlighting divergent perspectives (Korhonen et al., 2018), and advancing a more integrated understanding of technology-driven circularity in agricultural supply chains.

LITERATURE REVIEW

Circular Economy Principles

CE has emerged as a key paradigm for sustainability, founded on three core principles: eliminating waste and pollution through design, keeping products and materials in use via reuse, repair, and recycling, and regenerating natural systems to restore ecosystems. Research indexed in Scopus and WoS highlights that these principles not only reduce pressure on natural resources and lower greenhouse gas emissions but also create economic opportunities and jobs in sectors such as remanufacturing and recycling (Geissdoerfer et al., 2017; Ghisellini et al., 2016). However, its implementation faces significant challenges, including technological limitations, regulatory barriers, and cultural resistance, which demand innovation, coherent policies, and shifts in consumption behaviors (Kirchherr et al., 2017; Korhonen et al., 2018). Despite these obstacles, CE represents a crucial pathway for achieving the SDGs, fostering a balance between economic growth, environmental protection, and social equity-provided that multisectorial collaboration is strengthened and comprehensive strategies are promoted for large-scale adoption. Within this context, agricultural supply chains represent a critical domain where CE principles can be operationalized, given their complex material flowes and high levels of waste generation.

Agricultural Supply Chain (ASC) Challenges

Challenges in ASCs are multifaceted and influenced by factors such as globalization, climate change, price volatility, and sustainability demand. Research indexed in Scopus and WoS highlights that logistical inefficiencies, inadequate infrastructure, and fragmentation among supply chain actors lead to significant post-harvest losses, particularly in developing countries (FAO, 2019; Gokarn and Kuthambalayan, 2017). Furthermore, climate change exacerbates these issues by disrupting production patterns and increasing the frecuency of extreme weather events, which affects food availability and quality (Vermeulen et al., 2012). The growing demand for sustainable practices and traceability also pressures producers and distributors to adopt innovative technologies -such as blockchain and precision agriculture - to enhance transparency and reduce environmental impact (Kamilaris et al., 2019). However, implementing these solutions faces barriers such as high costs, lack of training, and resistance to change, underscoring the need for integrated policies, infrastructure investment, and public-private collaboration to build more resilient, efficient, and sustainable ASCs. Theses challenges highlight the need for innovative solutions, particularly technological ones, to operationalize CE principles is ASCs, enabling improved traceability, efficiency, and waste reduction.

Role of Emerging Technologies in CE

Emerging technologies are crucial in advancing the CE, particularly within ASCs, where they enable the operationalization of circular practices suchs as waste reducions, resource optimization, and enhanced traceability. The IoT enables real-time resource tracking and optimization, with Rajput and Singh (2019) highlighting its role in smart supply chains and efficient resource management. AI enhances decision-making by analyzing data to optimize resource use and improve recycling processes, as noted by Acerbi et al. (2021). Blockchain ensures transparency and traceability in supply chains, fostering trust and accountability, as discussed by Saberi et al. (2019). Additionally, advanced recycling technologies, such as chemical recycling and biodegradable materials, are essential for closing material loops, with Garcia and Robertson (2017) emphasizing their role in achieving a CE for plastics. Together, these technologies support the transition from linear to circular models specifically within agricultural supply chains.

METHODOLOGY

Search strategy

The scientific databases Scopus and WoS were systematically reviewed to collect data and conduct the necessary analysis. These databases were selected due to their broader coverage compared to Google Scholar, providing more comprehensive results for the targeted content (Rajit et al., 2025). Furthermore, Scopus and WoS demonstrate greater precision and reliability than Google Scholar (Adriaanse and Rensleigh, 2013). The data collection timeframe spanned from 2009 to 2024. The year 2009 was chosen as the starting point due to the unavailability of relevant data prior to this date.

The keywords were selected based on a literature analysis, topic brainstorming, and the “snowball sampling” method (Culot et al., 2020). As detailed in Table 1, Group I include terms related to the “Circular Economy” as the central focus of the search, while Group II encompasses keywords associated with the supply chain. To connect these terms, the Boolean operators “AND” and “OR” were used.

Table 1: Parameters used in Circular Economy for supply chain in agriculture with technology.
ParameterWeb of ScienceScopus
Range2008-2024
DateJanuary, 2025
Document TypePaper, book, chapter, conference proceedings
Words(“circular economy" OR "circular economies" OR "circular supply chain" OR "circularity”) AND (“supply chain" OR "supply chains" OR "value chain" OR "logistics”) AND (“technolo*" OR "digitalization" OR "smart technology" OR "IoT" OR "big data" OR "automation”) AND (“agr*”)
Results101267
Total (Wos+Scopus)277

This study applied an adapted PRISMA methodology Figure 1 to review the literature on the CE in ASCs enabled by technology. The search string combined key terms such as “circular economy”, “supply chain”, and “technolo” with the filter “agr”, retrieving 368 initial records (101 from WoS and 267 from Scopus). After removing 91 duplicates, 277 unique articles were selected. Academic documents such as journal articles, books, and conference proceedings were prioritized for their scholarly rigor and thematic relevance.

Figure 1: PRISMA diagram for preprocessing data. Source: own elaboration.

The search string was specifically designed to capture studies linking the CE with ASCs through key technologies. The combination of terms- “circular economy”, “supply chain”, and “technolo” (along with variants such as “IoT” and “digitalization”) -ensures the results address the intersection of these three thematic areas. The “agr” filter scopes the search to agriculture, preventing deviations into other sectors. Thus, the search strategy reflects the core objective of this review: to analyze how technology drives circular models in ASCs, from resource optimization to digital traceability.

The final selection of 277 documents resulted from requiring articles to simultaneously meet these criteria, balancing breadth (using OR operators for synonyms) and focus (combining concept blocks with AND operators). This approach guarantees that the reviewed literature is relevant for exploring both bibliometric trends and the practical implications of the topic.

During the processing phase, text mining and web scraping techniques were employed to extract metada, keywords, and supplementary data. This information was organized into 22 spreadsheets, one of which contains the results of the Tree of Science (ToS) analysis, which classifies articles into Roots, Trunk, and Branches. Inclusion criteria (focus on CE, technology, and agriculture) and exclusion criteria (duplicates and non-academic documents) were systematically applied.

To complement the PRISMA flow diagram, a scientometric analysis was conducted to map production by country, author, and journal. Furthermore, the Tree of Science methodology was used to identify foundational contributions (Roots), consolidated studies (Trunk), and recent advancements (Branches). Together, these methods provide a comprehensive mapping of the state of the art.

Scientific Mapping

Scientific mapping has become a well-established scientometric tool for analyzing academic literature, as evidenced by numerous recent studies. This methodology relies on bibliometric indicators related to authors and sources, facilitating the identification of patterns and trends in scientific output. A notable example of its utility is the detection of disruptive innovations, where scientometric analysis has emerged as an indispensable resource for exploring significant advances across various disciplines (Moral-Muñoz et al., 2020).

This study focuses on four key dimensions: scientific output, country, journal, and author analysis. This approach provides readers with a comprehensive overview of a research topic, starting from a broad perspective and culminating in a detailed examination of collaboration networks. To optimize citation analysis, we employed a method that constructs a collaboration network from references (Bornmann and Marx, 2014), enabling a more precise identification of underlying network structures within the scientometric data.

All procedures were conducted using the statiscal software RStudio (version 2023.12.0+369), along with its Bibliometrix extension (version 4.1.0), while visualizations were generated using the R packages ggraph (version 2.1.0) and Gephi (version 0.10.1).

Tree of science

The digital era has catalyzed exponential growth in the production and accessibility of academic, posing the challenge of efficiently managing the vast and continuously expanding volume of research. In this context, the Tree of Science (ToS) methodology has emerged as a pivotal tool for optimizing the identification of relevant publications within this academic landscape (Eggers et al., 2022). Based on graph theory, the ToS algorithm organizes articles into a tree-like structure, where classical or seminal works represent the roots, foundational studies form the trunk, and the most recent research occupies the leaves (Robledo et al., 2022; Zuluaga et al., 2022).

An advanced version of this algorithm, termed SAP, has significantly enhanced the precision of results, particularly in identifying recent studies (Valencia-Hernández et al., 2020). To facilitate its application, the Tosr package automates the SAP algorithm and streamlines data integration from Scopus and WoS.

Constructing a ToS requires users to download two files: a Scopus.bib file and a WoS.txt file, both containing article references. Next, users must initiate an RStudio Cloud session and load the Tosr, bibliometrix (Aria and Cuccurullo, 2017) and tidyverse (Wickham et al., 2019) libraries to process and analyze the data efficiently.

RESULTS AND DISCUSSION

Scientometric Analysis

Scientific Production

The graph titled Total Scientific Production vs Total Citations provides a comparative analysis of scientific output and total citations collected in Scopus and WoS, two of the most prominent bibliographic databases. Total scientific production represents the number of publications recorded in both platforms between 2018 and 2024, while total citations reflect references received by these publications during the same period (Figure 2).

Figure 2: Total Scientific Production vs Total Citations. Source: own elaboration.

Between 2018 and 2020, both indicators show gradual growth, attributable to research consolidation and increased digital visibility. The 2020-2021 period marks an inflection point, with a significant surge in scientific output (particularly in COVID-19 related fields) and a notable citation increase, reflecting the relevance of pandemic-era research. From 2021 to 2023, publication rates stabilized while citations continued growing, indicating sustained impact of prior work. For 2023-2024, a slight production decline is projected (potentially due to post-pandemic normalization), while citations keep rising, demostrating the enduring relevance of earlier research.

Regarding database comparisons, Scopus exhibits higher publication volumen due to its broader coverage, though its citations don´t consistently surpass WoS´s-suggesting differences in perceived quality or impact. Conversely, WoS, with fewer publications, shows higher citation counts, likely attributable to its journals’ greater impact factors or influence. This analysis highlights dynamic trends in scientific research and its temporal impact patterns.

Country Analysis

Table 2 reveals Italy and the United Kingdom as the countries with the highest citation counts. The most cited Italian study (De Corato, 2020) critically analyzes and compares the most promising technologies for on-site recycling of residual biomass into high-value soil amendments (compost) and plant treatments (compost tea). From the UK, a highly influential study by Maina et al. (2017) provides a comprehensive overview of current bioconversion methods for waste and by-product streams to advance biorefinery concepts.

Table 2: Top 10 most productive countries.
CountryProductionCitationQ1Q2Q3Q4
Count PercentageCount Percentage
India2810.18%4606.9%6025
Italy269.45%71310.7%10231
China196.91%2173.26%8011
United Kingdom155.45%6479.71%8011
Brazil145.09%1572.36%3020
Usa124.36%721.08%6100
Germany114%871.31%1201
Spain114%2533.8%5110
France103.64%5968.95%6111
Australia82.91%3004.5%3200

Figure 3 highlights a key finding from U.S. China collaborations: the impact of The Coca-Cola Company´s PlantBottle technology. Data indicate that since 2009, the distribution of over 30 billion units has resulted in an annual reduction of 315.000 metric tons of CO2 emissions. To expand this initiative, the company is collaborating with the Yangtze River Delta Circular Economy Technology Institute to convert agricultural waste into bioPET. The establishment of viable local production and supply chains for bio-MEG in China not only strengthens this partnership but could also catalyze the global transition toward recyclable plastics (Ren et al., 2015).

Figure 3: Country collaboration network. Source: own elaboration.

Journal Analysis

As shown in Table 3, the journal “Science of the Total Environment” exhibits the highest H-index. Its most cited article on this topic (De Corato, 2020) reports that the use of compost derived from agricultural waste-particularly as compost tea-offers significant benefits for soil and plant health by acting as a biological control agent against soil pathogens. However, the study also identifies barriers to its adoption, including high costs and complex regulatory frameworks within the European Union. Meanwhile, “Resources, Conservation and Recycling” ranks highest in terms of Impact Factor. Its most cited paper in this domain (Watari et al., 2020) presents a comprehensive assessment of demand projections and material dynamics for 48 critical metals up to 2050. The findings underscore an urgent need to improve demand forecasting -especially for emerging industries such as medical devices, robotics, and drones- and to address the social and environmental implications across the full metal lifecycle. The authors emphasize circular economy strategies, including reuse and recycling, as essential to mitigating these challenges.

Table 3: Top 10 most productive journals.
JournalWoSScopusImpact FactorQuartileH Index
Sustainability (Switzerland)0110.672Q1169
Journal of Cleaner Production8102.058Q1309
Resources, Conservation and Recycling082.77Q1196
Science of the Total Environment561.998Q1353
Circular Economy And Sustainability050.931Q121
Computer Aided Chemical Engineering040.103Q432
Energies240.651Q1152
Environmental Science and Pollution Research341.006Q1179
Journal of Enterprise Information Management331.648Q182
Journal of Environmental Management131.771Q1243

As shown in Figure 4, the journals “Chemosphere”, “Desalination”, and “Environmental Research” (Community 1) are highly pertinent to this research. Their relevance lies in their collective focus on specific aspects of the circular economy-such as nutrient recovery and anaerobic digestion-and their integration with technology applied to agricultural supply chains. Together, these publications provide a robust scholarly foundation for analyzing both the challenges and opportunities of implementing technology-driven circular economy models in agriculture (Soo and Shon, 2024; Subbarao et al., 2023).

Figure 4: Journal collaboration network. Source: own elaboration.

In Community 2, the journals “Journal of Environmental Management”, “Environmental Science and Pollution Research”, and “Frontiers in Energy Research”, align closely with the scope of this research. These journals consistently publish studies integrating circular economy principles, sustainability, and advanced technologies-such as Industry 4.0 and blockchain-into supply chain management, particularly within the agricultural sector (Munir et al., 2022; Perçin, 2022; Yontar, 2023). While “the Journal of Environmental Management and Environmental Science” and “Pollution Research” emphasize environmental management and sustainability, “Frontiers in Energy Research” focuses on innovative technologies like blockchain to enhance sustainable practices. Collectively, these publications cover environmental, social, and technological dimensions of circular economy applications in agricultural supply chains, forming a robust foundation for a systematic literature review on this topic. The highly cited articles within these journals demonstrate their direct engagement with both the challenges and opportunities of implementing technological solutions to achieve sustainable and circular agricultural supply chains.

Within Community 3, the journals “International Journal of Molecular Sciences” and “Molecules” are highly relevant to this research topic. They consistently publish studies on the valorization of agricultural waste, the application of advanced technologies such as ultrasound-and microwave-assisted extraction, and sustainable business models that integrate CE principles into agriculture. These publications address both the transformation of by-products into bioactive compounds, biomaterials, and bioenergy, as well as the optimization of supply chains through technological innovations. Their focus on bridging molecular science, resource efficiency, and circular business models makes them key sources for a comprehensive literature review on this subject (Di Maro et al., 2024; Nosratabadi et al., 2019).

Author Collaboration Network

Table 4 presents the most prolific authors. Researcher Shon, with the highest H-index among the authors analyzed, focuses his research on the applicaton of machine learning for nutrient recovery in the context of the urban CE, with an emphasis on waste management and its reuse in agriculture. This makes his work highly relevant to the research topic. His contribution lies in detailing how advanced technologies, such as drones and monitoring systems, optimize nutrient recovery and application within the agricultural supply chain, promoting sustainability and efficiency within a circular economy framework. For a literature review, this article is a key source for exploring the intersection between Smart technologies, waste management, and sustainable agricultural supply chains (Soo et al., 2023).

Table 4: Production by Author.
Sl. No.AuthorTotal PublicationsH- IndexAffiliation
1Al-Ansari T348Hamad Bin Khalifa University, Doha, Qatar
2Ghosh S378Laboratoire Leprince-Ringuet, Palaiseau, France
3Krstić M316Università del Salento, Lecce, Italy
4Kumar P310Indian Institute of Technology Hyderabad, Sangareddy, India
5Menezes B315Hamad Bin Khalifa University, College of Science and Engineering, Doha, Qatar
6Miglietta P321Università del Salento, Lecce, Italy
7Narkhede B342Indian Institute of Management Mumbai, Mumbai, India
8Raut R351Indian Institute of Management Mumbai, Mumbai, India
9Sehnem S319Universidade do Oeste de Santa Catarina, Joacaba, Brazil
10Shon H379University of Technology Sydney, Sydney, Australia

Research Ghosh, with an H-index of 78, focuses his research on providing a robust framework for understanding how the circular economy catalyzes decarbonization, with direct applications in agriculture. His emphasis on emission reduction, waste management, and multi-stakeholder collaboration is highly relevant to the proposed research topic, serving as a foundation for exploring how technologies can transform agricultural supply chains towards more circular and sustainable models (Ghosh and Ghosh, 2023).

Research Raut, with an H-index of 51, centers his research on the adoption of Industry 4.0 and the CE in industrial contexts, focusing on literature review and the analysis of factors that facilitate this adoption. Although not specifically focused on agriculture, it shares common ground with the proposed topic, particularly in the use of advanced technologies to promote CE practices. To relate it directly to the agricultural supply chain, it would be necessary to explore how the principles and technologies discussed in the document (such as IoT, big data, or automation) can be applied to specific agricultural challenges, such as waste management, resource optimization, or product traceability. A literature review focused on agriculture could use the document´s framework as a basis but should be complemented with studies specific to the agricultural sector to address its particularities (Kumar et al., 2021).

As identified in Figure 5 (Community 1), the research of Kumar P. focuses on the digitalization and sustainability of agri-food supply chains. His work highlights the application of emerging technologies-such as blockchain, IoT, artificial intelligence, and big data-to drive the CE, improve traceability, reduce food waste, and increase resilience against disruptions (Darshan et al., 2022). These themes are directly aligned with the proposed research topic, as the studies address barriers, opportunities, and technological applications for sustainable agricultural supply chains. The proposed review can leverage these works to map existing knowledge, identify gaps, and apply bibliometric approaches, providing a solid foundation for exploring the integration of technologies into the agricultural circular economy.

Figure 5: Author collaboration network. Source: own elaboration.

In Community 2, Al Ansari T and Menezes stand out. Their research on the CE in AFSC highlights the integration of Industry 4.0 technologies (IoT, Big Data, Blockchain) to improve traceability, transparency, and waste reduction, positioning them as key enablers of circularity. Emphasis is placed on waste management, transforming it into resources through processes like fermentation or anaerobic digestion, and on Life Cycle Assessment (LCA) to measure sustainability (Mohamed et al., 2021; Yaqot et al., 2023). Furthermore, technical, economic, and social barriers to the adoption of these technologies are identified, along with the need for optimization models and regulatory policies to drive circularity. This approach converges on practical applications, impact assessment, and the identification of gaps for future research, thereby strengthening sustainability in the agri-food sector.

In Community 3, Sehnem S stands out. Her research on the circular economy within the agri-food sector emphasizes the valorization of agro-industrial by-products, such as the conversion of waste (lactose, milk permeate, wheat by-products) into animal feed, and the use of advanced technologies (biorefineries, blockchain, machine learning, IoT) to optimize nutrient management, waste handling, and logistics, promoting Smart and sustainable supply chains (Manganda et al., 2024). These practices, supported by regulatory frameworks such as sustainability laws and international standards, along with initiatives like urban agriculture and phytoremediation, reinforce waste reduction, the integration of small farmers into sustainable markets, and soil decontamination. This work aligns with the SDGs 2,12, 13 and demonstrates practical applications in diverse global contexts (Provensi et al., 2025).

Tree of Science

Figure 6 presents a word network map visualizing key themes in sustainability, circular economy, and bioeconomy, grouped into orange clusters (production, technology, traceability), green (sustainable agriculture, circular development), and purple (bioeconomy, food security). Nodes such as “SUSTAINABLE”, “FOOD”, and “CIRCULAR” reflect interdisciplinary connections, highlighting trends in digitalization, agriculture, and bioenergy. However, the absence of terms related to public policies or climate change suggests research gaps. Future studies should employ quantitative analyses to explore these patterns and align priorities with the SDGs.

Figure 6: Internetwork with the three biggest clusters. Source: own elaboration.

Root

The analyzed documents explore diverse approaches and challenges of the CE across different contexts Kirchherr et al. (2017) identify that CE is commonly defined around the “3Rs” (reduce, reuse, recycle), but caution that its systemic change requirements and connections to social equity and future generations are rarely emphasized Ghisellini et al. (2016) highlight that CE aims to decouple economic growth from environmental pressure, citing successful waste management cases in developed countries. Meanwhile, Korhonen et al. (2018) argue that CE is an “essentially contested concept”, with research predominantly focused on technical aspects while neglecting social and cultural dimensions.

In practical applications, Kamble et al. (2020) highlight the potential of blockchain technology to enhance traceability in ASCs, particularly in India, where it can reduce intermediaries and ensure food security Genovese et al. (2017) demonstrate, through case studies in the chemical and food industries, that integrating the CE into supply chains reduces emissions and the use of virgin resources. Finally, Barros et al. (2020) emphasize the role of bioenergy in agriculture for cutting emissions, though they note that only 9% of the global economy is circular, with Europe leading research in this field. These studies agree on the need for interdisciplinary approaches, clear policies, and collaboration among stakeholders to advance toward truly circular and sustainable systems.

Trunk

The analyzed literature highlights the impact of digitalization and blockchain technology on Food Supply Chain (FSCs) and their contribution to sustainability Rejeb et al. (2021). conducted a bibliometric analysis of 2.140 articles, identifying technologies such as blockchain, artificial intelligence, and the IoT as pivotal for enhancing FSC resilience and efficiency, with a focus on food security, waste reduction, and CE practices. Meanwhile, Munir et al. (2022) explored blockchain´s potential to transform sustainable supply chains, emphasizing its ability to improve traceability, transparency, and resource efficiency in sectors like agriculture, manufacturing, and pharmaceuticals-though they noted persistent adoption challenges. Both studies emphasize that these technologies not only optimize economic processes but also promote environmental and social sustainability, providing researchers and professionals with tools to advance toward more circular and efficient systems.

Branch 1

The reviewed articles address the application of CE principles in food production systems and waste management, highlighting critical insights from diverse studies. Gkountani and Tsoulfas (2021) emphasize how CE can mitigate environmental and economic impacts in food processing and manufacturing stages, contrasting with traditional linear models. Danya et al. (2024) explore biorefineries as a solution to food waste, converting residues into bioproducts through microbial and enzymatic technologies-though they note challenges such as feedstock variability and industrial scalability.

Jemili et al. (2024) optimize Tunisia´s biogas supply chain, demonstrating its viability with levelized electricity costs of 14.2-19 cents/kWh, while Subbarao et al. (2023) underscore the potential of anaerobic digestion to reduce carbon emissions, particulary in India, where it could cut 3.5-3.8 kg of CO2 per capita annually.

Further, Ranjbari et al. (2022) identify four key themes in biomass and organic waste valorization, including conversion technologies and lifecycle assessments. Stempfle et al. (2021) map strategies for implementing CE in olive oil supply chains, and Lampridi et al. (2021) propose precision agriculture systems to optimize dairy value chains Sun and Fan (2020) review optimization methods for biomass supply chains, highlighting challenges like sustainability trade-offs and operational uncertainties. Finally, Chauhan (2020) stresses the role of digital platforms in reducing food waste in India, demonstrating their potential to enhance supply chain efficiency. These studies converge on the need for technological innovation, cross-sector collaboration, and robust policy frameworks to transition toward sustainable and circular systems.

Branch 2

The reviewed articles demonstrate blockchain´s transformative potential in integrating CE principles into agri-food supply chains Ellahi et al. (2024) highlight its ability to ensure transparency, traceability, and fraud reduction through immutable records and smart contracts, while identifying underexplored applications such as food redistribution and animal welfare (“Blockchain enhances data integrity and optimizes humanitarian initiatives”).

Santos et al. (2024) emphasize blockchain’s utility in reverse logistics for managing pesticide waste and prioritizing critical factors like food waste prevention and lifecycle traceability, supported by methods such as ANP-MAIRCA. Conversely, Pakseresht et al. (2023) underscore how blockchain mitigates information asymmetrics and promotes and promotes eco-efficiency, though the note gaps in empirical evidence regarding waste valorization (“Its capacity to monitor risks in recycled biomass remains understudied”).

Furthermore, barriers and facilitators are identified (Kumar et al., 2021; Sharma et al., 2021) highlight obstacles such as lack of government support and inconsistent policies, while proposing frameworks like the “12 R’s” for circularity, where traceability emerges as a key factor dependent on connectivity and information flow. Finally, Pandey et al. (2022) summarize blockchain´s global impact on authentication and logistics but warn of technical challenges (scalability, costs). Collectively, these studies demonstrate that blockchain not only optimizes sustainable supply chains but also requires regulatory frameworks and integrated technical solutions to overcome current limitations.

Branch 3

The reviewed articles reveal key consensuses and significant contributions on integrating CE principles into agricultural supply chains through disruptive technologies Manganda et al. (2024) highlight the role of Brazilian agtechs in adopting precision agriculture and artificial intelligence, which enhance efficiency and reduce waste, aligning with CE goals and sectoral resilience (e.g., ‘these innovations boost productivity while minimizing environmental impact’). Meanwhile, Vianna et al. (2024) emphasize agricultural waste valorization via biochemical technologies, identifying plastic recycling and biomass management as key opportunities, supported by a bibliometric analysis of 858 articles. From a technological perspective, Francisco Luis et al. (2022) underscore how industry 4.0 (digitization, IoT) and blockchain enable traceability and material cycle closure-critical for circular models in agri-food systems (‘blockchain ensures authenticity and reduces costs for SMEs’).

Furthermore, critical barriers are identified Ada et al. (2022) identify the ‘insufficient implementation of CE legislation’ as the primary obstacle for cooperatives, while Chauhan et al. (2021) highlight institutional and financial risks, as well as food losses due to por logistical practices. Proposed solutions include global regulatory frameworks and IoT-based Smart systems (Fatimah et al., 2020), which link CE to SDGs. Finally, Jabbour et al. (2020) emphasize the potential of big data for sustainable supply chains, though they caution about the need for enhanced analytical capabilites in firms. Collectively, these studies advocate for an integrated technological and policy transition, where innovations such as AI, blockchain, and IoT not only optimize resource use but also require institutional support to overcome systemic barriers.

This study addresses the main gap identified in the literature: the lack of a comprehensive understanding of how digital technologies enable CE in ASCs. The results show that technologies such as blockchain, IoT, and AI are key enablers for solving critical challenges related to traceability, waste reduction, and resource optimization. However, important gaps remain, including the limited presence of longitudinal studies, insufficient integration of social dimensions, and weak cross-sector collaboration. These findings highlight that the relationship between CE, ASCs, and technology must be understood as an interconnected system, where digital innovation acts as a key enabler of circular transformation.

Future research directions

Future research should focus on three main areas. First, longitudinal studies are needed to assess the long-term impact of digital technologies on circular performance in ASCs. Second, more empirical research is required in developing countries to evaluate adoption barriers and scalability. Third, interdisciplinary approaches integrating technological, economic, and social dimensions are essential to better understand the transition toward circular agricultural supply chains.

CONCLUSION

This study provides a comprehensive overview of the emerging field of the CE applied to agricultural supply chains with digital technologies, highlighting its rapid development and growing relevance. Based on an analysis of 277 publications, clear trends are identified, driven by sustainability concerns, climate change, and food security challenges. Technologies such as blockchain, IoT, and artificial intelligence stand out as key enablers for improving traceability, transparency, and efficiency in agricultural supply chains, reflecting a shift from theoretical approaches toward practical applications within the industry 4.0 framework.

The findings also show that the transition toward a CE in agriculture is a complex socio-technical process, where technology, although essential, is not sufficient on its own. Its effective implementation depends on integration with innovative business models, appropriate regulatory frameworks, and the ability to overcome social and economic barriers. From a theoretical perspective, the study extends approaches such as the Natural Resource-Based View (NRBV), emphasizing how circular and technological strategies contribute to environmental and competitive performance, while underscoring the need for a systemic approach that closes loops of materials, information, and value in supply chains.

Finally, the study offers relevant practical implications for key stakeholders. Policymakers should promote regulations and incentives that facilitate digitalization and waste valorization, while agricultural firms should invest in technological capabilities and collaborative pilot projects. At the same time, academia and the Agtech sector play a crucial role in developing accessible and interdisciplinary solutions. Overall, the future of circular agricultar supply chains will depend not only on technological innovation but also on strategic collaboration among governments, industry, and academia to build sustainable and scalable systems.

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Mañay, L. O. R. (2026). Circular Economy for Supply Chain in Agriculture with Technology: A Literature Review. Journal of Scientometric Research, 15(2), 570–582. https://doi.org/10.5530/jscires.20260260