Reducing Food Waste with the use of AI
As much as a third of the world’s produce is wasted, costing the global economy a staggering US$1 trillion ($1.6t) a year. However, innovators are using artificial intelligence to fight back. How AI can be deployed to combat excess and maintain freshness in the supply chain is the focus of a major agrifood conference in Perth - evokeAG Agrifuture this week.
At the conference one of the presenters is American food systems entrepreneur Abi Ramanan, who has with her team used hyperspectral imaging, similar to fingerprint technology, to hone in on everything from avocados to seafood to stop waste and food fraud. Using AI, they installed cameras on a conveyor belt on an avocado production line where they scanned the fruit for freshness and ripeness. This allowed them to work out how much dry matter was in the fruit to determine when it would ripen, and which ones would be best suited for longer trips, such as when exported.
Artificial intelligence (AI) is increasingly playing a crucial role in combating the global issue of food waste. By leveraging AI technology, various industries within the food supply chain are finding innovative ways to minimize wastage and improve efficiency. ChatGPT is not the only game in town in terms of innovative AI. WWF, in collaboration with the Pacific Coast Food Waste Commitment (PCFWC), Afresh, and Shelf Engine, conducted pilots using AI purchasing systems in two different grocery retail chains to reduce food waste and improve profits. The results were impressive: food waste was reduced by 14.8% per store on average.
More specifically, AI is being leveraged to help with:
1. Demand Forecasting AI algorithms enable accurate demand forecasting by analyzing various data points such as historical sales, weather patterns, and seasonal trends. With this information, retailers and food manufacturers can optimize production schedules, reducing the likelihood of excess inventory that often leads to food spoilage.
2. Inventory Management AI-powered inventory management systems help businesses track perishable items in real-time. By monitoring factors like expiration dates and storage conditions, AI can alert stakeholders to prioritize products nearing expiry, thus reducing the chances of them being wasted.
3. Quality Control Through computer vision technology, AI can inspect food items for quality defects at a speed and accuracy unmatched by manual inspections. By identifying issues early in the production process, companies can take corrective actions promptly, ensuring that only high-quality products reach consumers.
4. Supply Chain Optimization AI facilitates supply chain optimization by analyzing vast amounts of data to identify inefficiencies and areas for improvement. By streamlining processes such as transportation routes and storage facilities, businesses can significantly reduce food waste resulting from logistical challenges .AI systems are helping to improve the overall harvest quality and accuracy – known as precision agriculture. AI technology helps in detecting disease in plants, pests, and poor nutrition of farms. AI sensors can detect and target weeds and then decide which herbicide to apply within the region.
5. Personalized Offers By leveraging AI-driven analytics, retailers can personalize promotions and discounts based on individual consumer preferences and purchasing behaviors. This targeted approach not only minimizes excess inventory but also encourages customers to make informed buying decisions, reducing the likelihood of impulse purchases that may lead to wastage.
In conclusion, AI's applications in reducing food waste are diverse and impactful. By integrating AI technologies across the food supply chain, businesses can not only minimize economic losses but also contribute to a more sustainable and efficient food system for the future.
