AI optimizes insect breeding for sustainable protein production
Black soldier fly converts waste into high-quality proteins
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The FLY4FOOD research project is developing an AI-supported, digital platform to optimize the breeding of the black soldier fly as a sustainable source of protein and biomass. With the help of sensor technology, IoT, digital twins and predictive models, breeding conditions and feed utilization are precisely controlled. The aim is to achieve resource-efficient, scalable insect production that converts organic waste into high-quality proteins and bio-based raw materials, thereby contributing to sustainable nutrition and the bioeconomy.
The global demand for sustainable protein sources is growing rapidly, while at the same time enormous amounts of organic waste remain unused. The FLY4FOOD research project is tackling precisely this challenge: With a digital, AI-supported solution to optimize the breeding of the Black Soldier Fly (BSF), researchers want to establish a resource-efficient, scalable and climate-friendly protein production of the future.
FLY4FOOD focuses on the integration of state-of-the-art technologies - sensor technology, Internet of Things (IoT), digital twin models and artificial intelligence - to precisely control environmental conditions, feed mixtures and production processes in order to stabilize and optimize the breeding of BSF larvae. The BSF larvae can convert organic waste into high-quality proteins, fats and bio-based raw materials that can be used for food, animal feed and industrial applications.
The August-Wilhelm Scheer Institute is taking on the central role of digitalization and AI optimization in the project: building a scalable system architecture, developing and integrating predictive AI models, real-time monitoring using IoT sensors and implementing a digital twin to simulate and control breeding conditions. These technological building blocks form the basis for precision farming-oriented, data-driven insect production that is scalable worldwide.
Accompanying the technological development, the researchers are creating extensive data sets on BSF biology and breeding dynamics, developing non-invasive analysis methods for quality prediction and evaluating system components in real pilot environments. In addition, an ecological life cycle analysis (LCA) evaluates the sustainability effects of the optimized production process.
FLY4FOOD is funded as part of the Bioeconomy International program of the German Federal Ministry of Research and Technology. Partners in the project include Khon Kaen University, Suranaree University of Technology, BETAGRO Ltd.
With its innovative approach, FLY4FOOD combines digital technologies, AI methods and biotechnology to create a holistic solution for one of the key issues of our time: sustainable, climate-friendly food and raw material production from biogenic residues.
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
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