The world needs to produce 50% more food by 2050 to feed 9 billion people. If that needs to happen, new technology is necessary.

Over the past decade, the agri-food sector has faced big challenges from climate change, population rise, resource constraints, and changing consumer behaviour. It's abundantly clear that food systems need to prioritise health, sustainability, inclusion, and the environment. This shift necessitates the adoption of a data-driven approach.

The digital era

The digital era has taken over basically every aspect of our lives. It has also permeated and reshaped farming and agricultural practices and opened new avenues for sustainable growth.

Amidst the complex agriculture and food production landscape, technology products and services have emerged as potential catalysts to initiate the next agricultural revolution.

If we take some basic tenets of sustainable agriculture, like conserving water and minimising waste to increase food production, the digital era has ushered in numerous possibilities. What does the digital era encompass? It's things like the digital economy, digital infrastructure, and information services. Simple examples include remote sensors and geospatial analysis.

Putting it into practice

Studies of food systems have shown that better data is needed to monitor and analyse food safety, food loss and waste, governance, food system resilience, etc.

Let's take the food supply chain as an example. With a growing population and demand for food, the supply chain is constantly under immense pressure. Data analytics can be a powerful tool to optimise this complex system. Analysing historical sales data and current market trends makes production and inventory management easier. The right amount of food is produced to meet the actual demand.

On the other end of that chain are consumers. It's tricky to gain consumer insights since tastes and preferences change. Data analytics can help uncover trends and patterns in purchasing habits. Producers can adjust their offerings and marketing strategies. Maybe more consumers prefer eco-friendly options. The supply chain can thus be tailored to meet their demands.

While data and analytics can be quite broad, there are a few important types:

Predictive: Statistical models and machine learning algorithms can forecast weather patterns, crop diseases, and pest infestations.

Prescriptive: This goes a step further. It not only predicts outcomes but also recommends specific actions. For example, the data and analysis might suggest the best time to plant, irrigate, or harvest based on current and future forecasts.

Diagnostic: Diagnostic analysis can help determine why a past event happened. For example, it might provide insights into why a particular crop failed or underperformed.

One of the better examples of how data is being used in agriculture is precision farming. Farmers employ sensors, GPS, and satellite technology to manage and monitor crops. More farmers now have access to soil conditions and climate forecast information.

By using soil moisture sensors, farmers can gather data on water needed by crops and formulate a schedule to ensure they get the required amount at the right time.

If we step outside the farm, valuable data can be leveraged by agricultural research institutions and private companies to conduct experiments and model scenarios. Multi-stakeholder platforms and data-sharing ventures can enable policymakers, researchers, and industries to work together to address sustainable agriculture challenges.

Room to grow and evolve

As advancements in agricultural technology continue, adoption by smallholders and women farmers remains a challenge. According to a McKinsey study, only 39% of farmers have adopted at least one technology service. That's because there's not much clarity on the return on investment.

Meanwhile, governments and others are using more advanced data analytics tools, including AI and Machine Learning. In the UAE, this is seeping into local food systems. Many hotel chains in the Emirates rely on AI tracking systems to reduce food waste. Hilton reduced food waste by 62% across its UAE properties over four months last year.

Granular data and analytics are just the beginning. At Smart Grow Farms, we use data and insights to make informed decisions on sustainable farming. It's more important now than ever.