The global food and agricultural sector is currently undergoing substantial transformations, driven by population growth, shifting consumer consumption behaviours, digital technological advancements, evolving food value chains, and the pressing challenges of food security and environmental sustainability¹. Amidst these changes, digital technology emerges as a pivotal force capable of significantly enhancing the efficiency of our food system while opening up new markets and opportunities.

Digital technology or digitalisation refers to the creation and practical use of digital or computer-based devices, software, methods, systems, and processes for the betterment of humankind. It is the use of digital solutions to change a business model and provide new revenue and value-producing opportunities for the populace². In the agri-food sector, digital technologies help enhance efficiency, transparency, and trust. They facilitate process monitoring, cost reduction, and an enriched customer experience by utilising data analytics, digital models, automation, sensors, simulations, and other technological tools. Moreover, digitalisation effectively tackles sustainability challenges within food systems by enabling real-time data sharing and fostering stakeholder interaction, predicting food quality, improving energy efficiency, minimising food waste, and optimising resource management. From advancing genetic improvements to optimising farm management and transportation systems while meeting consumer needs, digital technologies have become omnipresent in boosting productivity and refining decision-making processes across every phase of food production.

One crucial aspect where digital solutions play an important role is in reducing food loss and improving energy efficiency in the horticultural value chain. By integrating software-driven solutions, stakeholders can minimise wastage at various points in the supply chain, thereby addressing climate mitigation and adaptation challenges. For instance, wireless sensors and IoT devices can enable real-time monitoring of crops during storage and transport, facilitating timely interventions to prevent spoilage or loss in the postharvest supply chain. Food manufacturers can also leverage robotics, smart materials, and AI-driven mobile apps to optimise process performance in drying, cooling, fermentation, extraction, packaging, and other postharvest processes, effectively reducing energy demand and waste. In essence, software and digital solutions serve as catalysts for sustainable practices, fostering energy efficiency, reducing food loss, and mitigating environmental impact throughout the entire food value chain. Here are some ways digitalisation can drive a sustainable agri-food system, especially for horticulture value chain:

• Digital technologies like wireless remote sensors, drones, and satellite imaging enable precision agriculture. Farmers can collect data on soil quality, moisture levels, and crop health, allowing them to optimise inputs like water, fertilisers, and pesticides. Additionally, integrating advanced software into farming practices facilitates the adoption of smart farming techniques, including automated irrigation systems, climate control in greenhouses, and data driven mobile or web crop management platforms. Farmers can greatly reduce resource waste, lower energy consumption, and minimise the environmental impact of farming practices through the precise use of farm inputs and harnessing real-time data. These digital tools can also help them make informed decisions, leading to enhanced resource efficiency and higher crop yields. Examples of such precision agriculture and smart farming digital tools include CropIn, AgriApp and Iberdrola. Digital tools such as AgriApp are tailored not just for large-scale farmers but also cater to smallholders. Increasing the access of these tools to marginal farmers contributes to enhancing the accessibility of the food system overall.

• Artificial Intelligence (AI) and Machine Learning integrated into software and mobile applications play a crucial role in achieving a sustainable agri-food system. By facilitating crop disease detection, pest control, yield prediction, supply chain logistics optimisation, and food quality prediction, these technologies significantly help enhance sustainable food systems. For instance, AI-powered apps like Plantix aid farmers in identifying crop diseases by analysing smartphone photos. Moreover, the predictive capabilities of AI and Machine Learning enable the anticipation of extreme weather events and potential disruptions in the supply chain. By predicting extreme weather and supply chain disruption, stakeholders in the food value chain, such as farmers, off-takers, and logistic providers, can proactively reduce wastage from such disruptions. This can lead to more efficient energy access and improved food availability, especially for domestic supply chains in low- and middle-income countries. Through these advancements, AI-driven solutions not only assist in ensuring the resilience of food production but also optimise resource utilisation, thereby contributing to sustainable food systems and augmenting global food accessibility.

• Digital marketplace connecting farmers directly to buyers enables streamlined transactions, fair pricing, and reduced postharvest food waste by eliminating intermediaries and ensuring fresher produce reaches consumers. Additionally, by streamlining the supply chain, farmers can better match supply with demand, reducing the need for excessive energy consumption in producing, storing, and transporting surplus goods that might otherwise go to waste. Moreover, implementing a digital marketplace platform significantly augments the scalability and transparency of the fresh produce supply chain. Examples include Farmcrowdy in Nigeria and AgroStar in India.

• Digital food Sensors and IoT Devices play a pivotal role in improving the agricultural landscape by continuously monitoring various factors such as temperature, humidity, and storage conditions. These tools help to significantly reduce postharvest losses by ensuring optimal conditions during storage and transportation to improve the end fruit quality. An Internet of Things (IoT) system comprises networks of physical objects embedded with technology to sense, communicate, and interact with their internal states or the external environment³. Key enablers for such systems encompass RFID, printed sensors, web services, machine-to-machine communication (M2M), WSN, imaging systems, and multi-sensors, though not always collectively employed⁴. Various sensors cater to specific process parameters influencing fruit quality, measuring air temperature, humidity, fruit pulp temperature, airspeed, and mechanical responses to vibrations. Examples of these sensors include hydrothermal sensors like Ubibot WS1, and SENSITECH TempTale GEO Eagle, which facilitate wireless monitoring of environmental conditions. These innovative tools help to optimise the quality and preservation of agricultural produce for an energy-efficient and sustainable global food supply chain.

• Implementing blockchain in postharvest supply chains enhances transparency and traceability, reducing food fraud and ensuring food safety. By using blockchain technology, the entire journey of produce, from its origin on the farm to its presence on the consumer’s table, becomes accessible for tracking and verification. Furthermore, the integrating blockchain technology not only safeguards against fraudulent activities but also promotes fair trade practices and ethical sourcing. It empowers consumers by providing them with information about the product’s origins, cultivation methods, and handling processes, thereby allowing them to make informed choices that align with their values and preferences. Basically, blockchain in postharvest supply chains catalyses trust among consumers, enhances food safety standards, and supports sustainable food supply chain practices. This, in turn, contributes to increased confidence in the food supply chain while promoting global food security and accessibility. IBM’s Food Trust and TE-Food are examples.

• Creating in-silico virtual models, known as digital twins or digital shadows, for crops aids in predictive analysis. These models enable farmers and other value chain stakeholders, such as logistics providers to simulate diverse scenarios, optimising strategies for increased yields, reduced losses, and more sustainable practices. A digital twin of an entire crop value chain, from planting to consumer, will help enhance energy efficiency, resource management, and sustainability throughout the process. Specifically, a digital twin of the food value chain represents essential fruit and system characteristics and simulates relevant physiological, metabolic, and hygro-thermal processes⁵. These simulations are interconnected with real-world processes through real-time sensor data⁶. This approach allows for example, the real-time assessment of how growing conditions and practices impact the postharvest quality of food. This kind of mechanistic or data-driven simulation of the food value chain enables the prediction of crucial metrics like weight loss, overall fruit quality, freshness, remaining shelf life, and spoilage at different stages. These simulations also quantify the impact of supply chain activities on food shipment greenhouse gas emissions via a life cycle assessment (LCA) method, serving as a tracking tool for environmental sustainability improvements. Additionally, integrating LCA models into the digital twin allows for shipment-specific environmental impact analysis, considering food losses, travel times, and energy consumption for cooling. This digital tool provides real-time LCA data, enabling statistical analysis for identifying environmental impact variability among shipments. In essence, a digital twin of a food value chain could help bring together the various functions of the digital innovation mentioned in a single platform to help improve energy access, reduce food waste, improve food quality and enhance sustainable agri-food system (see Figure 1)^7,8. Coldtivate is an example of such a digital tool that provides real-time food quality prediction for smallholder farmers using a decentralised cold room based on measured sensor air and humidity data. This mobile app uses AI to predict the market prices of different commodities and different locations up to 8 months into the future. This data empowers farmers, not only indicating optimal selling times but also identifying the most lucrative markets for their produce.

Overall, by leveraging digital solutions, the agri-food sector can optimise resource use, minimise environmental impact, and enhance overall sustainability. These efforts are essential in achieving a more resilient and sustainable agri-food system capable of mitigating and adapting to the impacts of climate change. While digitalisation holds the promise of enhancing food systems, it also brings forth a set of challenges that need careful consideration^7,8:

• The shift towards digitalisation may result in the consolidation of power among a select few large companies. This concentration can limit competition and stifle innovation within the sector.
• The use of digital technologies in food systems can raise concerns about data privacy and security, especially when it comes to sensitive information such as personal data and sensor data for business.
• The adoption of digitalisation may inadvertently exclude smallholder farmers and marginalised communities due to limited access to necessary infrastructure and resources.
• The increasing use of digital technologies in food systems can make them more vulnerable to cyber-attacks and data breaches. Such breaches could largely impact food safety and compromise the integrity of supply chains.

Addressing these challenges is crucial to ensuring that the process of digitalisation remains inclusive, equitable, and sustainable. This can be achieved through the government’s implementation of policies and regulations that foster competition, protect data privacy, and improve cybersecurity. Additionally, public and private investments in digital infrastructure and capacity building for smallholder farmers and other stakeholders in the food system are essential steps toward creating a more equitable and resilient digital landscape in agriculture.

Figure 1. A typical digital twin of a citrus export value chain

References:

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7. George, C. & Tomer, A. The potential—and pitfalls—of the digitalization of America’s
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   the-digitalization-of-americas-food-system/ (2023).
8. World Bank. Future of Food: Harnessing Digital Technologies to Improve Food
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   https://www.worldbank.org/en/topic/agriculture/publication/future-of-food-harnessing-
   digital-technologies-to-improve-food-system-outcomes (2019).

About the author:

Daniel Onwude is an Agricultural Engineer, Senior Scientist, and Project Lead at the Simulating Biological Systems (SimBioSys) group of the Swiss Federal Laboratories for Material Science and Technology, Empa, Switzerland. He earned his Ph.D. in Agricultural Process Engineering in 2018. Daniel has over 7 years of experience in Food Sciences and currently leads the Your Virtual Cold Chain Assistant initiative in Nigeria. He is also driving the use of a passive cooling blanket in Kenya, Uganda, and Nigeria. Dr. Onwude’s expertise encompasses food processing and preservation, food nutrition, computational food science, process modeling and simulation, and digital twinning.