Ms. Kajal Gupta1 and Dr. A. Sangamithra2*

1PG Scholar & 2*Assistant Professor, Department of Food Science and Technology, Pondicherry University, Puducherry – 605 014

*asokmithra@gmail.com

Introduction

What would happen if we had the exact copy or twin of us? A digital doppelgänger, identical, exact in every aspect. The fascinating part is the working of our digital twin in an accurate rendering of our digital home and office. The concept of Digital Twin Technology (DTT) is becoming famous in academia and industry. It is becoming relevant to the fourth industrial revolution. However, have we ever wondered what digital twin technology is and how we employ it in the various sectors to get the desired results? This article will discuss DTT and how we can use it in the food and agriculture sectors to avoid losses and provide resilience and sustainability.

After the pandemic, many businesses transformed digitally. This digitization encompasses business units, IT sectors, automation, and AI for preparing the crew for this revolution. The adoption of traditional online and mobile technologies, as well as cloud-based services that expand business resources and accessibility to employees and customers, tops the list. The second method involves incorporating Internet of Things (IoT) technology to gather data from any chosen source, followed by using big data architectures and analysis methodologies to generate business choices. Additionally, machine learning algorithms and artificial intelligence (AI) can enhance the transformation process by forecasting trends, seeing correlations, and offering insights. The last resource is augmented reality (AR), which improves digitalization by giving system users an immersive experience.

Deploying these technologies in digitization requires the latest network technologies that allow users to visualize real-time situations. This technology is known as Digital Twin. A digital twin is a digital representation of a physical object, person, or process contextualized in a digital version of its environment. Digital twins allow an organization to simulate real situations and their outcomes, ultimately allowing it to make better decisions. In simpler terms, a digital twin is a virtual replica of a physical object, person, or process used to simulate its behaviour to understand better how it works in real life. Digital twins are linked to authentic data sources from the environment, which means that the twin updates in real-time to reflect the original version. Digital twins are layers of behavioural insights and visualizations acquired from data. When interconnected within one system, digital twins can form what is known as an enterprise metaverse: a digital and often immersive environment that replicates and connects every aspect of an organization to optimize simulations, scenario planning, and decision-making.

DTT in Food Supply Chain

DTT in the food supply chain is used as a virtual representation of the product for real-time monitoring and tracking. It improves the efficiency of product transportation, safe assessment of the product, collaboration, and better documentation and communication. DTT enhances the resilience and sustainability of the food supply chain. Resilience is the ability of supply chains and networks to adjust and adapt against shocks and disruptions. The use of digital twin technology in manufacturing is driven by the need to enhance flexibility, maintenance, innovation, and operation cost optimization.

Gaurvendra et al. 2023 used Grey Casual Modelling (GCM) to analyze the cause-and-effect relationships in a complex system, such as a supply chain. GCM considers factors, objectives, and outcomes to identify the best situation set for the cause-and-effect pairs. Their work highlights the significance of digitalization technologies in mitigating risks and ensuring a resilient and sustainable food supply chain system. Digital technologies can share information required for controlling and managing the food quality, safety, and transfer of food and ensure adequate shelf life for the consumers. They identified the fifteen key factors of DTT that affect the resilience and sustainability of FSC through expert opinions: risk assessment, quality, Bullwhip Effect, flexibility, coordination, efficiency, precision farming, safety, visibility, traceability, logistics capabilities, cold chain facilities, food security, governance, and weather forecasting. Out of these, seven factors are identified as causal factors and eight as effect factors. Through their analysis, ‘coordination, efficiency’ got the first rank, and the prime or decisive causal factor for achieving the dual objectives of resilience and sustainability in the food supply chain through DTT is ‘coordination.’ The digital twin technology enhances the coordination among the stakeholders, increasing the visibility of the food supply chain, reducing food waste, and increasing the efficiency of the food supply chain.

DTT in Product Simulation

Digital twins are handy for imitating the product. They provide insights into the thermal history of individual shipments. They are helpful for perishable products, such as mangoes, stored at low airflow rates. They offer a high spatial and temporal resolution of temperature and quality attribute data, capturing local temperature peaks and accurately quantifying the contribution of respiratory heat. Using digital twins improves the accuracy of predicting fruit quality and storage life compared to air temperature-based models.  DTT increases the cold storage and logistics capabilities of the food supply chain by proper monitoring of temperature and humidity in the storage space or refrigerated containers. Increased efficiency and decreased food waste can assist in achieving the economic and environmental sustainability pillars.

Defraeye et al. 2019, showed how digital fruit twin based on mechanistic modelling is very helpful in minimizing the environmental impact of the cold chain and optimizing logistics; a better knowledge of the fruit quality evolution within individual shipments would be precious. Mechanistic modelling enabled us to understand, record, and predict where temperature-dependent fruit quality loss occurs in each supply chain. In that way, digital twins can help to improve refrigeration processes and logistics to reduce food losses, thereby making the refrigerated supply chain greener.

A digital twin can also be used to formulate new recipes according to the given nutritional value or exceptional food, taking into account health preference, ethnicity, etc., and add or change the composition of raw ingredients based on their properties. The “digital twin” combines a variety of factors, from chemical composition and functional and technological properties to organoleptic indicators, by simulating the food product. Digital twins contain not only physical or chemical parameters but also the knowledge of dependencies of technological, structural, mechanical, and functional characteristics where small changes affect the whole recipe significantly. Testing in the virtual world saves time, money, and resources for physical scientific experiments.

DTT in Agro-Food Sectors

The goal of digital farming is to tackle many problems related to resource management, food security, and climate protection by utilizing information from agricultural assets. The incorporation of cutting-edge machine learning, artificial intelligence (AI), big data analytics and interpretation techniques, the Internet of Things (IoT), and information and communication technology (ICT) is one of the critical aspects of digitalization in agriculture. They streamline the decision-making process, lower expenses, and increase overall productivity. ICT tools offer benefits for decision support tools as well as efficiency, quality control, on-farm management, and the food supply chain. Big data and artificial intelligence (AI) enable more accurate and better agricultural management, data collection, analytics, and information extraction from sensors.

Nasirahmadi et al., 2022 demonstrated that the notions of digital twins in agriculture and food processing have yet to be fully utilized in research, suggesting areas for future improvement. Digital farming techniques can give farmers helpful information about :

  • how to use chemicals, fertilizers, seeds, and irrigation management techniques;
  • protecting the environment;
  • managing pests, climate, and crops;
  • market demands and business conditions

There are potential and problems for study at many levels of digital farming; however, developing digital twins in agriculture has concentrated on specific criteria. Digital twin systems can support farmers in lowering economic pressure and labour concerns, assist policymakers in boosting the agriculture industry, and help predict and address unforeseen issues in the fields. Researchers can investigate ways to track and monitor agricultural farm equipment.

Conclusion

This article explores the world of digital technology and how the food sector is affected by it. The process of implementation of digital twins in the agricultural and food supply chain has displayed promising advancements in addressing global challenges. Digital twin technology certainly makes many things more manageable, despite its many benefits rather than drawbacks.  Although there are encouraging signs of development in this sector, the practical application of this solution is still in its nascent phase. Furthermore, the digital twin technology and its possible uses in different sectors continue to be an intriguing field for investigation and discovery in the future.

References

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