Building a Sustainable Agrifood Supply Chain with New Technologies

From precision agriculture to connected food systems

A sustainable agrifood supply chain begins with decisions: how much water to apply, when to harvest, how to store food and where to deliver it. New technologies can make those decisions more informed by revealing conditions that were previously difficult to observe. Yet information alone changes little. Farmers, food processors, distributors and retailers need the digital competences to understand what the information means and translate it into practical improvements.

For the EU FooD Pact project, this relationship offers a useful way to connect digitalisation, sustainability and learning. The transition concerns both the tools businesses use and the capabilities of the people using them. A sensor may detect soil moisture, but someone must interpret its readings. A stock management platform may identify surplus food, but a team must coordinate a response. Sustainable change depends on technology, human judgement and cooperation working together.

In “Unlocking the Potential of Precision Agriculture for Sustainable Farming,” Mgendi (2024) describes precision agriculture as an approach that recognises differences within fields and adapts management accordingly. Rather than treating every location identically, farmers can use information about soil, crops and weather to target interventions. Getahun et al. (2024), in “Application of Precision Agriculture Technologies for Sustainable Crop Production and Environmental Sustainability: A Systematic Review,” examine how sensing, positioning systems and variable rate technologies can improve resource management. Authored by Sewnet Getahun, Habtamu Kefale and Yohannes Gelaye, this review supports the potential of these tools while identifying barriers involving affordability, infrastructure and expertise.

Water management illustrates the connection clearly. Soil moisture sensors, local weather measurements and irrigation software can help a grower assess when crops require water. Instead of relying exclusively on a fixed timetable, irrigation can respond to observed conditions. However, readings must represent the field accurately. Sensors need appropriate placement and maintenance, while decisions must consider crop development, soil characteristics and expected rainfall. The environmental benefit comes from better management, supported by reliable measurements (Getahun et al., 2024; Mgendi, 2024).

Nutrient application follows a similar principle. Geographic information systems can combine soil sampling results with field maps, while positioning technologies help equipment operate in defined locations. Variable rate application allows inputs to differ between management zones. This can reduce unnecessary application where nutrient availability already meets crop needs. Achieving that result requires sound agronomic advice and usable data. A colourful map becomes valuable only when its categories correspond to meaningful differences and appropriate actions (Getahun et al., 2024; Mgendi, 2024).

Remote sensing adds another perspective. Satellite images and drones can help identify variations in crop development or areas requiring inspection. They are particularly useful for directing attention across larger areas. Nevertheless, an unusual pattern does not automatically explain its cause. Water stress, nutrient deficiency, disease and other factors may produce overlapping signals. Workers need to compare digital observations with field inspections before selecting an intervention. Combining these perspectives improves decisions without assuming that imagery replaces agricultural experience (Getahun et al., 2024; Mgendi, 2024).

Artificial intelligence can support this process by finding patterns in datasets and generating forecasts or recommendations. Potential applications include identifying crop problems, anticipating demand and scheduling operations. Its usefulness depends on the quality and relevance of the information available. A model developed for one crop, climate or production system may perform poorly elsewhere. Businesses therefore need a way to check recommendations against local conditions, recognise uncertainty and retain human responsibility for consequential decisions (Mgendi, 2024).

The opportunity extends beyond primary production. Food processing businesses can use meters and production records to understand water and energy consumption across operations. Connecting resource use with individual batches can reveal avoidable losses or inefficient processes. For example, an unexpectedly high electricity requirement may prompt an equipment inspection or scheduling adjustment. These applications become more useful when teams compare equivalent products and operating conditions, rather than interpreting every fluctuation as evidence of a problem.

Storage and distribution introduce further opportunities. Temperature sensors can alert staff when refrigeration conditions move outside an agreed range. Digital inventory records can show which products require attention before their shelf life ends. Route planning software can support delivery coordination and identify opportunities to combine compatible shipments. Each tool addresses a specific operational problem. Its contribution to sustainability should be assessed through actual changes in food losses, energy use, transport activity and service quality (Manikas et al., 2014).

These examples demonstrate why a sustainable agrifood supply chain needs connected thinking. Saving resources on the farm is valuable, but part of that benefit can be undermined if food deteriorates during storage or remains unsold. In “Environmental Sustainability Initiatives in the Agrifood Supply Chain,” Manikas et al. (2014) examine environmental initiatives across supply-chain operations, encouraging attention beyond individual production activities. The chapter is authored by Ioannis Manikas, Petros Ieromonachou and Dionysis Bochtis. Digital transformation should therefore help organisations understand how their decisions affect subsequent stages and where cooperation can prevent waste.

Technology also has an environmental footprint. Equipment requires materials, batteries and maintenance, while computing and communication consume energy. Businesses should consider whether a proposed system solves a significant problem, whether existing equipment can perform the task and how devices will be repaired or replaced. Purchasing more technology is not itself evidence of sustainability. The relevant question is whether the system produces measurable improvements that justify its financial, organisational and environmental costs.

Digital Competences Turn Agrifood Technology into Sustainable Practice

The skills farmers, SMEs and supply-chain teams need

Digital competences in agriculture involve more than using an application or operating connected machinery. They include collecting reliable information, evaluating its meaning, collaborating through digital systems and protecting business data. These capabilities support everyday work across farms, processing facilities, warehouses and commercial teams. For EU FooD Pact, they provide a practical focus for discussing the human side of the transition: what people need to learn to make technology useful in their own roles.

The first capability is basic digital confidence. Workers need to navigate the systems relevant to their tasks, enter information correctly and retrieve records when required. They should understand how files are named, where information is stored and which version is current. These apparently simple routines matter because fragmented spreadsheets, duplicated entries and missing records can undermine more advanced tools. A reliable foundation makes it easier to introduce automation and maintain continuity when responsibilities change.

Data literacy builds on that foundation. Users need to distinguish a measurement from an estimate, check units and recognise incomplete information. They should ask when data were collected, what area or process they describe and whether comparisons are valid. For instance, a lower irrigation total may reflect wetter weather rather than improved efficiency. Understanding this distinction helps businesses avoid misleading conclusions and identify whether a new practice deserves to be maintained or adjusted.

Interpreting dashboards is another essential skill. A display may combine water use, energy consumption, stock levels and production outputs, but its design can obscure important differences. Staff need to understand indicator definitions and choose comparisons that support decisions. Total consumption and consumption per unit of product answer different questions. Both may be necessary: an efficiency improvement can coexist with higher overall resource use if production increases. Sustainability monitoring should make that relationship visible.

Digital information must also be connected to professional knowledge. Agronomists, production operators and logistics workers understand constraints that software may not capture adequately. Training should help them combine that experience with digital evidence. A grower might compare a sensor alert with soil observations, while a warehouse worker might check whether an inventory discrepancy reflects damaged stock or an incomplete entry. This combination makes digitalisation part of competent professional practice rather than a separate technical activity.

Problem solving matters because systems will occasionally fail. Users should recognise missing readings, implausible values, disconnected devices and inconsistent records. They need clear procedures for basic checks and for escalating problems to a specialist. Knowing when to seek assistance is itself a competence. Without these routines, unreliable information may influence decisions unnoticed, or staff may abandon a useful tool after a minor fault. Accessible support helps organisations sustain improvements after initial installation.

Cybersecurity is equally relevant. Connected equipment and shared platforms can expose operational information to unauthorised access or disruption. Workers should recognise suspicious messages, protect account credentials and use access permissions appropriate to their responsibilities. Businesses need workable backup and recovery arrangements, alongside clarity about who maintains them. Mgendi (2024) identifies data security among the challenges surrounding precision agriculture. Building awareness across the workforce helps protect both business continuity and confidence in digital systems.

Data governance introduces questions about responsibility and control. Before adopting a platform, a business should understand which information it collects, who can access it and whether records can be exported. Staff responsible for purchasing or managing systems need the confidence to discuss these conditions with providers. Accessible exports and clear documentation can support continuity when services change. They also help organisations avoid becoming dependent on a system they cannot connect with other essential tools (Mgendi, 2024).

Collaboration requires its own digital skills. Supply-chain partners need consistent product identifiers, understandable records and agreed ways to exchange information. A producer may describe a batch differently from a distributor, creating confusion when records are combined. Teams should learn how to establish shared definitions and resolve discrepancies. Interoperability involves both technical compatibility and working agreements between people. Its purpose is to make information usable across organisational boundaries without requiring repeated manual interpretation (Mgendi, 2024).

Training should therefore follow real tasks. A farmer can practise interpreting a moisture trend and deciding whether irrigation is justified. A processing team can compare energy use between comparable batches. A distributor can investigate a temperature alert and record the response. These exercises connect learning with operational decisions and environmental consequences. They also reveal where an apparently straightforward task depends on additional knowledge, clearer responsibilities or information from another organisation.

Vocational education and training providers can help bridge these gaps by working with businesses on realistic learning activities. Short modules, demonstrations and supported practice can accommodate people with different starting points. Assessment should examine what learners can do: identify an unreliable value, explain an indicator or respond appropriately to an alert. Completing a course is useful, but demonstrated capability offers stronger evidence that training has prepared someone to use technology effectively.

Regular review meetings can help teams identify emerging needs and keep learning aligned with daily operations.

Access deserves particular attention. Small businesses may lack specialist staff, reliable connectivity or time for extended training. In “Contribution of Information and Communication Technologies to Agricultural Sustainability: Case of Precision Farming,” El Bilali and Khairullina (n.d.) identify costs, rural connectivity and operators’ skills as barriers to agricultural digitalisation. Shared advisory services, cooperative purchasing and local demonstrations can help address these constraints. Within the EU FooD Pact conversation, an inclusive transition means making learning and practical support accessible to the people responsible for implementing change.

Turning Digital Transformation into Measurable Supply-Chain Progress

A practical pathway for EU FooD Pact stakeholders

A sustainable agrifood supply chain develops through focused improvements that organisations can test, understand and maintain. Businesses should begin by identifying an operational problem with a clear environmental consequence. Examples include excessive irrigation, losses during refrigerated storage, inefficient cleaning cycles or frequent deliveries with little cargo. This approach gives digital investment a purpose. It also helps teams decide which information they need and which competences will enable them to use it.

The next step is establishing a baseline. Before introducing a tool, the organisation should document current performance over an appropriate period. Depending on the problem, measures might include water per unit of production, electricity per batch, discarded product weight or distance travelled per delivery. Definitions should be recorded so future comparisons remain consistent. Where seasons, weather or product mix affect performance, those conditions should also be documented and considered when interpreting changes.

A limited pilot can then test both the technology and the working process. One field, production line or delivery route may provide a manageable starting point. The pilot should have a responsible person, an agreed objective and a review date. Teams need to know what action follows each relevant observation. Otherwise, the organisation may collect more information while continuing to work exactly as before. Learning whether staff can respond effectively is part of evaluating the investment.

Consider an illustrative cooperative handling fresh vegetables. Growers share harvest estimates, the packing facility records available quantities and the distributor provides confirmed orders. Bringing these records together could help the cooperative align harvesting, packing and dispatch more closely. The proposed benefit is reduced mismatch between supply and demand. This is an example of a possible application, not a reported EU FooD Pact result. Its effectiveness would depend on timely updates, trustworthy forecasts and practical coordination.

Temperature monitoring could complement that pilot. If a shipment experiences an unexpected change, designated staff would investigate promptly and record what happened. Inventory information could then help prioritise suitable products for dispatch. The organisation would still need appropriate food safety procedures and professional judgement. Digital alerts support those responsibilities; they do not establish that a product is safe or automatically determine its destination. Clear responsibilities make the information actionable and prevent alerts from being ignored.

Traceability can strengthen the same system by linking products with records of origin, handling and movement. Reliable batch identification helps partners locate relevant information and investigate problems more efficiently. It can also support sustainability communication when the underlying evidence is appropriate. However, traceability does not prove that a product has a low environmental impact. A recorded journey describes what happened; evaluating sustainability requires additional indicators, a defined assessment method and credible supporting information.

Blockchain is sometimes proposed for sharing records across organisations, but it should be assessed against the actual requirement. Many businesses can meet their needs through well managed databases and agreed access arrangements. A record that resists later alteration can still contain inaccurate information entered initially. The priority is therefore reliable collection, verification and governance. Choosing technology should follow an assessment of functionality, costs and partner readiness, rather than assumptions that a particular architecture guarantees trust.

Sustainability also depends on how cooperation is organised. In “Retail Governance and Agrifood Sustainability: Insights and Research Needs,” Fuchs et al. (2010) examine retail governance and raise questions about power within agrifood systems. The working paper is authored by Doris Fuchs, Katharina Glaab, Agni Kalfagianni and Richard Meyer-Eppler. This perspective matters when digital reporting requirements are introduced. Smaller suppliers may face additional work without receiving adequate support or access to resulting insights. Partners should discuss who contributes information, who benefits and how costs are distributed. A transition that transfers burdens to weaker participants may struggle to achieve lasting participation.

Results need to be evaluated honestly. Businesses should check whether observed improvements reflect the intervention or other changes, and whether benefits in one area create costs elsewhere. Lower food losses may accompany higher refrigeration energy use, for example. Teams should examine both outcomes and decide how to improve the balance. Environmental performance, affordability and staff workload should be considered together, since an approach that cannot be maintained is unlikely to deliver lasting gains.

Successful practices can then be expanded gradually. Scaling should include updated procedures, additional training and checks that information remains compatible across sites or partners. Organisations should preserve the ability to export records and reconsider tools as needs evolve. Sharing lessons from pilots, including difficulties and unsuccessful approaches, can help other businesses make informed choices. This is especially valuable for SMEs that have limited capacity to absorb costly implementation mistakes or repeat experiments independently.

For EU FooD Pact, the strongest message is that digital competences make sustainable innovation usable. New technologies can reveal opportunities to conserve resources, prevent food losses and coordinate supply chains, while learning enables people to act on those opportunities responsibly. Farmers, SMEs, educators and other stakeholders can contribute by connecting real operational challenges with practical skill development. Progress comes when reliable information leads to better decisions, cooperation and measurable improvements across the agrifood supply chain.