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Data-Driven Strategies for Reducing Food Waste and Advancing Sustainable Food Systems
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Author(s): Kukatlapalli Pradeep Kumar (Christ University, Bangalore, India), A. Nesan Daniel (Christ University, Bangalore, India), K. Sarath Chandra (Christ University, Bangalore, India), Tharun Jeevakanth (Christ University, Bangalore, India)and Parthiv Saha (Christ University, Bangalore, India)
Copyright: 2026
Pages: 28
Source title:
Revolutionizing Sustainable Food Production With Quantum Computing
Source Author(s)/Editor(s): Mong Fong Horng (National Kaohsiung University of Science and Technology, Taiwan), Osamah Ibrahim Khalaf (Al-Nahrain University, Iraq), Chin-Shiuh Shieh (National Kaohsiung University of Science and Technology, Taiwan)and Vishal Jain (School of Engineering and Technology, Vivekananda Institute of Professional Studies, New Delhi, India)
DOI: 10.4018/979-8-3373-3957-3.ch008
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Abstract
Food waste is a major global issue that affects the environment, economy, and society. About 1.3 billion tons of food, or one-third of what is produced worldwide, is wasted each year. This worsens food insecurity, increases greenhouse gas emissions, and depletes resources. As the population grows, the pressure on food systems increases. We need new strategies to reduce waste across supply chains. Using historical and real-time data, like sales trends, seasonal demand changes, consumer habits and outside factors like weather, the study suggests a data-focused approach to improve decision-making for everyone involved, including producers, retailers, and food services. The results show that predictive analytics helps to make proactive changes to orders, stock distribution, and promotion plans, which reduces overproduction and spoilage. Data-driven solutions can be scaled up and highlight their potential to connect economic goals with sustainability efforts. It provides useful insights for policymakers, businesses, and community groups to support circular food systems.
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