Technology developed by Indian scientists at Princeton University and Microsoft Research could significantly reduce food waste and usher in a new era in the food industry. The technology could be also be used to evaluate food quality, leading to even less waste.
Together, Microsoft's managing director of Research for Industry and Chief Technology Officer for Agri-Food, Ranveer Chandra, and Princeton's postdoctoral researcher, Subhajit Karmakar, from NIT Delhi and others, developed an accurate way to measure fruit quality that has the potential to revolutionize food distribution and reduce food waste around the world.
Chandra said that food wasted accounted for nearly 6 percent of the world’s greenhouse gas emissions. “When we look at the global challenges around food security, nutrition and environmental sustainability, the issue of food waste plays a major role,” he said in a news release. “If we could reduce food waste, it would help feed the population, reduce malnutrition, and help mitigate the impact of climate change, “ he emphasized.
In the food industry, determining when fruit is at its peak ripeness has been a major challenge. Current methods, such as looking at or touching fruit, are not always reliable. As a result, many edible items go to waste, including about a third of all food in the United States and half of all fruits and vegetables worldwide.
The new solution, presented at the 2023 ACM MobiCom conference on October 3, uses high-frequency wireless tech to scan fruit on a conveyor belt. These signals, called sub-terahertz, can see beneath the fruit's surface and measure things like sugar and dryness.
Unlike conventional methods that rely on surface characteristics, this innovation may pave the way for more sophisticated food sensing. It is crucial because fruits undergo significant changes as they ripen, and this technology provides a more precise assessment of their ripeness.
Significant obstacles were encountered by the researchers in the development of this cutting-edge technology, such as taking into account the structural complexity of fruits, which includes seeds, pulp, and skin. They were able to develop a model for determining ripeness by modeling waves, running simulations, and collecting a large amount of data.
The experiment initially focused on persimmons, avocados, and apples, which have smooth skins that are easier to measure. However, the researchers believe that with sufficient data and adjustments, this technology can be extended to assess the ripeness of most fruits.
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