Approval is a major milestone on the path to the commercialisation of crops that give off optical signals – detectible from as far away as space – when under attack from pathogens or short of water or nutrients
InnerPlant, the company creating a new category of seed technology that unlocks data and makes global farming more efficient and sustainable, announces the U.S. Department of Agriculture’s (USDA) Animal and Plant Health Inspection Service (APHIS) approved multiple Regulatory Status Review (RSR) requests.
The RSR approvals include:
InnerPlant’s first commercial product, a soybean fungal sensor currently undergoing field testing with farmer trials scheduled for 2024 and on track for commercial launch in 2025
An always-on soybean that emits a constant signal is used in the crop development process to calibrate and refine detection capabilities
“USDA approval confirms our due diligence around the safety of our technology and reduces the time and complexity of our commercial development cycle,” explains Randy Shultz, PhD, InnerPlant’s Senior Vice President of R&D, Commercialisation. “And it’s an encouraging proof point as we continue working toward global regulatory approvals.”
InnerPlant engineers crops to produce safe and long-studied proteins when under attack from pathogens or when short of water or specific nutrients. The proteins emit optical signals – detectable from as far away as space – that show farmers exactly what kind of help plants need within 48 hours of stress onset, which is as much as two weeks before stress is visible in the field.
Historically, farmers lacked early actionable data and broadly apply agrochemicals as a preventative measure. However, studies show that farmers lose as much as 40 per cent of yields or $220 billion worldwide due to pathogens in spite of overapplication that sees as much as 30 per cent or $250 billion of pesticides wasted – negatively impacting air, water and soil.
InnerPlant’s new category of seed technology delivers traits that tap directly into plants’ physiology and provide farmers with actionable data that is both early and specific to particular stresses in a scalable and economical way.
