How AI Can Reduce Food Loss and Impact World Hunger

The planet’s population is rapidly approaching 8 billion. And 821 million of us – currently over 10% of the world’s population – suffer from food insecurity, according to the UN.

At the same, scientists have concluded that global food production is and will be sufficient to feed the planet, even through 2050, when the population is expected to hit 9 billion. So why is there still hunger? Distribution of food resources – getting the food from where’s produced in excess to the hungry people – is a major issue. So is food wastage, and overreliance on inefficient protein sources like meat.

Yet one issue that gets somewhat less attention is the tremendous amount of  food loss in today’s food value chain. And it is here that AI-powered technology is beginning to make a positive impact.

How AI LowersFood Loss

Food loss is defined as “any food that is discarded, incinerated or otherwise disposed of along the food supply chain from harvest/slaughter/catch.” The primary reason behind food loss is spoilage, and a key reason for spoilage is supply chain inefficiency. It is here that AI-powered solutions have already begun to prove their worth at eliminating inefficiency, including in the agriculture space.

How is food loss mitigated today? Primarily through mechanical or chemical intervention. The food value chain comprises a secondary industry dedicated to mitigating food loss through fumigation, pesticides, manipulation and various other inorganic treatments designed to artificially preserve freshness. These methods are prevalent despite being ecologically questionable, economically impractical, and logistically complex.

The creation of a sustainable food ecosystem is contingent primarily on supply chain optimization – not artificial freshness or preservation techniques. Global food suppliers are turning to AI from companies like Centaur to address and rectify these systemic inefficiencies.

Using a combination of smart sensors, blockchain for provenance, and AI for predictive analytics, these innovators are already lowering food loss and food production waste dramatically.

AI solutions replace narrowly-focused traditional demand prediction – often conducted independently by food manufacturers and retailers. ai

tools can see across the entire value chain – optimizing individual production, inventory and order processes and enabling more accurate, more holistic demand prediction.

AI-powered solutions can also eliminate the need for mechanical and chemical freshness preservation interventions. How? By ensuring a shorter route from field to plate. Because enhanced value chain efficiency lowers time to market, meaning that grain, vegetables, fruits and other perishables spend less time in storage and transport. This not only ensures fresher produce and raw materials for processed foods, but also lowers the carbon footprint of the food value chain as a whole.

The Bottom Line

The UN reports that up to 14% of food is lost between harvest and retail. Yet precision agriculture today still stops at the field’s edge. Using AI-driven solutions, we can extend efficiency all the way to the consumer’s plate.

The effective digitization of post-harvest handling, storage, and shipping can and should replace existing and antiquated business models that have proven themselves not only ineffective but also ecologically and economically unviable. Leveraging AI, we can bring the food value chain in-line with modern standards of efficiency and transparency. And this can alleviate a significant portion of food loss – and the corresponding food insecurity – along the way.

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