Benson Hill Biosystems, an agricultural technology company that uses cloud biology to drive crop performance improvements, closed a Series B funding round at $25 million. The funding will be used to further advance CropOS, the company’s computational platform driven by data and machine learning, and to develop a portfolio of promising product candidates to increase crop yield without requiring additional inputs.
CropOS is designed to empower companies of all sizes to unlock the global genetic potential of plants to improve the sustainability of food, feed, fiber and fuel production.
“With this round of financing, our investor base is joined by a capable and strategically minded group of organizations that recognize the immense challenges and opportunities facing the food and agricultural industry,” says Matthew Crisp, CEO and co-founder of Benson Hill Biosystems. “We need a new model of innovation that can accelerate crop improvement to meet our global food and energy needs.”
This funding round was co-led by Lewis & Clark Ventures and Prelude Ventures, with other new investors including Fall Line Capital and S2G Ventures. Existing investors Alexandria Venture Investments, Cultivation Capital, iSelect Fund, Mercury Fund, Middleland Capital, Missouri Technology Corporation, Prolog Ventures and TechAccel also participated. As part of the financing, David Russell of Lewis & Clark Ventures and Mark Cupta of Prelude Ventures will join the Benson Hill board of directors.
Benson Hill leverages cloud biology, an intersection of cloud computing, big data analytics and plant biology to empower companies of all sizes to improve the genetics of any crop for a fraction of the time and cost traditionally required. CropOS is a cognitive engine that uses machine learning to continuously advance, enabling researchers to better predict which seeds will produce a desired trait. The platform outputs can be deployed in crop plants by using a spectrum of approaches and tools, from breeding to genome editing to transgenics.
Benson Hill’s first application of CropOS successfully identified traits to increase crop yields by improving photosynthesis, one of the most fundamental and complex plant systems. In corn hybrids, trait product candidates identified by CropOS have demonstrated significant crop yield increases in diverse environmental conditions.
