Agri-Food 4.0: Volume 27

This study explores the thematic relationships within the field of sustainability of agri-food chains oriented toward Industry 4.0, focusing on the analysis of scientific production, through research articles and technological output according to patents worldwide. Agri-food Industry 4.0 is an expanding interdisciplinary field in which science and technology interactions are increasingly intensifying with a strong link to sustainable development.

This study has used high impact indexed publications (Web of science) and patents as proxy indicators of innovation, which are transformed into two sets of data, reflecting the scientific and technical backgrounds, respectively. On the one hand, both quantitative and qualitative analysis methodologies were used to examine the scientific papers through descriptive analysis, focused on collaborations networks by authors, institutions, and countries, as well as a content analysis of keywords. On the other hand, the analysis of technical background on patent families shows the temporal evolution of technologies with future challenging trends, text mining, main applicants, and geographical examination.

The results show that in the field of sustainability in agri-food chains oriented to Industry 4.0, most research is in the agricultural field in scientific articles, with high impact in climate-smart agriculture. Patent analysis reveals a marked increase in the patenting rate from 2012 and 2013, coinciding with the start of scientific production in this field of knowledge. In spite of the fact that China is the leader country in this technological field, India shows a significant change. Moreover, India is a country that is currently showing significant progress, both in the field of scientific production and in its categorization as an innovative country due to its growth in patent filings.

The Agri-Food supply chain (AFSC) conventionally suffers from multifaceted transparency, integration, traceability, product quality, and many more. Recently, various digital technologies have emerged, which reflect the potential to address the majority of such concerns. This chapter is an effort toward developing a vision for the future of the agri-food supply chain through digitalization. The technologies prominently covered in the chapter are the internet of things (IoT), blockchain, and artificial intelligence (AI). Different challenges the agri-food supply chain participants perceived in implementing digital technologies were identified through literature review and primary survey. The significant challenges are trained workforce, funds availability, and clarity on economic gains from digitalisation. In conclusion, few strategies toward the implementation of digital technologies in agri-food supply chains are discussed.

India's agri-food industry is rapidly expanding to keep up with the country's growing population. With the help of the fourth Industrial Revolution (Industry 4.0), modernization is creating a new revolution in the agri-food sector. Its applications in the food supply chain as a supply chain 4.0 (SC 4.0) have made it convenient to deliver products efficiently from farms to consumers. The various technologies such as the internet of things (IoT), artificial intelligence (AI), big data analytics and blockchain, etc., have impacted emerging supply chains. But many challenges are perceived by stakeholders toward the adoption of SC 4.0 technologies in India. The authors identified the challenges of adopting SC 4.0 for the agri-food sector and used the Total Interpretive Structural Modeling (TISM) tool to analyze those challenges. Based on literature research, nine major issues were diagnosed and then simulated using expert opinion. Primary data were also gathered with the help of a questionnaire to identify the status of acceptance level of these technologies. This study highlights the importance of government support, availability of sources of funds, customer orientation toward food safety, the commitment of management toward modernization, aware and well trained and motivated employees are a few of the major factors impacting the adoption of SC 4.0 technologies.

Creating systems designs by considering a balance between economic, environmental, and social effects is significant in today's sustainability concern. Sustainability has become an emerging topic, growing concerns and attention for companies. Especially companies operating on a global scale aim to develop strategies for sustainable supply chain management. When the supply chain is a food chain, that concern increases exponentially and sustainable management of the chain becomes a critical challenge requiring the development and implementation of innovative practices by all stages within value chains. According to the Food and Agriculture Organization (FAO), a significant amount of food is wasted or lost in the journey from farm to fork. This waste affects the global economy, food availability, as well as the environment negatively. In this work, we, therefore, focus on addressing these aspects by searching how food waste or food loss could be reduced throughout a supply chain network. We provide solution ways for the food waste/loss reduction obtained from current works in literature.

Amid rising environmental concerns, Industry 4.0 and blockchain technology (BCT) are transforming circular economy practices and prevailing business models. Recognizing the same, the current study examines the role of advanced technology in circular practices and their impact on eco-environmental performance, which influences organizational performance. The study collects data from 185 food processing enterprises that are located in Malaysian territories. By employing CB-SEM modeling, the study provides three key findings. First, Industry 4.0 significantly improves the circular economy practices. Second, circular economy practices help to improve firms' environmental performance but did not stimulate operational performance. Third, higher eco-environmental performance significantly boosts organizational performance. This study set out the foundations for participating countries/firms that help to achieve sustainable goals through the integration of blockchain technology in circular economy practices.

Food supply chain transparency and traceability is very important to address the issue regarding quality and safety. In traditional tracing system, with increasing the complexity of supply chain making product recalls difficult to manage and putting human lives at risk. To eliminate such types of risks, blockchain technology gives more efficient and reliable system for food tracing. Recently, there is an exponential rise in adoption of blockchain technology and most disparate IOT (Internet of things) devices in agriculture and food supply chain. It is an evolving technology that comforts the food supply chains by providing transparent data records and manage the food movement in the chain using distributed (P2P) network. That is more secured and there's no need for third party verifications. Our focus in this research will be on the Indian wheat supply chain and issues related to food losses caused by a lack of transparency and traceability. In order to improve the transparency of the wheat supply chain, we created an end-to-end smart wheat supply chain solution that combines blockchain technology, NFC tags, IoTs, and smart contracts. The solution is supported by entity relationship diagrams, information and money flow sequence diagrams, and a blockchain network diagram. We also used a security algorithm and the “NFC-Tag writer by NXP” program to validate and assess our system. This work could serve as a springboard for more in-depth research in this area. Depending on the existing situation in the industry, this research can also advise corporate procedures to deploy blockchain-based applications in the supply chain and logistics industry.

In this chapter, drone and vision camera technology have been combined for monitoring the crop product quality. Three vegetable crops such as tomato, cauliflower, and eggplant are considered for quality monitoring; hence, image datasets are collected for those vegetables only. The proposed method classified the vegetables into two classes as rotten and nonrotten products so the images were collected for rotten and nonrotten products. Three different features information such as chromatic features, contour features, and texture features have been extracted from the dataset and further used to train a Gaussian kernel support vector machine algorithm for identifying the product quality. The system utilized multiple features such as chromatic, contour, and texture features in classifier training which enhances the accuracy and robustness of the system. Chromatic features were utilized for detecting the crop while other features such as contour and texture features were utilized for further classifier building to identify the crop product quality. The performance of the system is evaluated based on the true positive rate, false discovery rate, positive predictive value, and accuracy. The proposed system identified good and bad products with a 97.9% of true positive rate, 2.43 % of false discovery rate, 97.73% positive predictive value, and 95.4% of accuracy. The achieved results concluded that the results are lucrative and the proposed system is efficient in agriculture product quality monitoring.

The Internet of Things (IoT) is becoming increasingly popular in agribusiness to help increase food production capacity for the ever-expanding global population. This chapter provides a holistic overview of the latest trends around the applications of IoT in agriculture. We begin by giving an overview of IoT and its capabilities, followed by a deep dive into the practical and realistic aspects of leveraging IoT into the agroecosystem. IoT is already being used for many intelligent agriculture applications, such as open-field agriculture, controlled environment agriculture (greenhouse), livestock breeding, agricultural machinery, and more. This chapter examines those applications and ventures beyond the farm into several other aspects of the ecosystem, including storage, warehouse ambiance control, agri-data analytics and decision control, logistics, environmental safety, etc. The contents of the chapter would be based on extensive studies and empirical analysis of the latest research papers on this subject from around the globe, accurately interpreted and transformed by the authors in light of their academic background and professional experience in the digital transformation arena.

This chapter presents the Smart Irrigation system using the Internet of Things (IoT). IoT Technology is a network of physical objects that are connected with sensors, software, etc. This chapter concludes the project based on the agriculture field that automates the irrigation process and on the agriculture field that automates the irrigation process and solves the challenge of water consumption in those areas. We have developed the system using different sensors like (1) Soil Moisture sensor, which measures the moisture present in the soil, (2) Humidity and Temperature Sensor (DHT11), which traces the temperature change. All these sensors are connected to the Node MCU ESP8266 microcontroller, which is also a Wi-Fi module. It uploads the data to the cloud and displays it in the form of readings detected by the Blynk Application. This sensor's reading values control the pump for emergency purposes, such as stopping the pump for irrigation. Thus, this project can automate the irrigation process by analyzing soil moisture and climatic conditions, covering essential aspects like less labor, power consumption, reliability, and cost.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

Globalization has increased the consumer's demand for safe and quality foods. To make food available to consumers from farm to fork, packaging plays a crucial role. The objective of packaging is to shield the foodstuff from degrading and to serve as the medium of communication between the processing industry and the consumers. Conventionally, several materials are used in the packaging such as laminates, plastics, glass, metal, etc., but with the advent of technology, newer and novel smart packaging technologies have entered this field. Smart packaging in the form of active and intelligent packaging not only acts as a barrier to external influences but also prevents internal deterioration. Oxygen scavengers, moisture controllers, antioxidants, CO₂ absorber/emitter, antimicrobial agents, etc., are some of the vital active packaging systems. On the other hand, an intelligent packaging system contains internal or external indicators and sensors that monitor the condition of packed food and gives information about its quality during storage and transportation. It seems that these interventions in packaging have very positive effects on the whole industry, but it is observed that this advancement in the packaging has also raised questions about its disposal. To overcome this issue, industries have started using smart packaging design along with the sustainable packaging trend. Communication with the recycling bodies at the time of development will ensure the smart packaging fit to be recycled. Considering such standards for smart packaging will not only create a healthy bond between industries and consumers but will also help in sustainable development. This chapter mainly focuses on the advancement of the packaging system associated with the agri-food sector. It also discusses how the implementation of these technological advancements will help the industries toward sustainable development.

The world is experiencing technological disruptions due to the dynamic business environment, technological advancements, customer preferences, increasing competitive pressure, globalization of supply chains, and environmental disruptions. Industry 4.0 technologies are paving the way for increased production efficiency and worker safety while optimizing resource utilization and improving sustainability. Industry 4.0 technologies find their applications in almost all sectors, but few studies explore industry 4.0 technologies in agriculture. The agri-food sector has experienced an upward trend in digitalization projects. The digital agri-food supply chains will help in the autonomous decision-making process, leading to enhanced visibility in the agri-food supply chains through real-time traceability solutions, thereby leading to improved food quality. It is anticipated that industry 4.0 technologies in the agri-food supply chains will impact climate change disruptions and improve the unequal distribution of resources in the agricultural sector. The present study highlights various industry 4.0 technologies and their applications in the agri-food supply chains. Based on the findings from a literature review, the study establishes 10 key performance indicators that will benefit decision-making in a digital, data-centered environment.

Improved production with quality, safety, and security is the biggest challenge of the food industry. Modern technologies, including robotics and automation systems, can help to cope with such issues. This chapter gives a brief view of robotics and automation for the sustainable food industry along with packaging, warehousing, distribution, marketing, and consumer services. It describes the recently implemented solutions of robotic automation in different supply chain operations and various food commodities. The benefits of robotic and automation technology for perishable and semi-perishable items have also been covered. The present research may assist the food industry professionals, supply chain managers, and academicians in implementing automation and robotics in the food industry.