The Future of Farming: Ag Subcommittee Testimony

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  1. 1. The Future of Farming: Technological Innovations, Opportunities, and Challenges for Producers Roger Royse Royse Law Firm, PC Royse AgTech Innovation Network
  2. 2. Dynamics Food Security The Rise of Consumerism The Declining Labor Market The Changing Agricultural Markets Increased Rural Internet Connectivity Cannabis The Introduction of Venture Capital The Rise of Big Data
  3. 3. Food Security Factors: climate change, growing global population, rising food prices & environmental pressures Impact peoples physical, social & economic access to sufficient, safe & nutritious food
  4. 4. The Rise of Consumerism Grow Local Movement Growing middle class desire for convenience & year- round food Tech development: urban & vertical farming, waste, transport & packaging Transparency in supply chain GMO & gene editing practices Environmental sustainability
  5. 5. The Declining Labor Market Farm labor shortages resulted in increased labor costs Technologies (e.g. Farmbot & Blue River Technology) replace manual labor part of farming process
  6. 6. The Changing Agricultural Markets Harvested cropland & agricultural labor work force declined over time Agricultural production increased Productivity increase Agricultural methods have changed
  7. 7. Increased Rural Internet Connectivity Adoption & application of AgTech rests on availability of the Internet AgTech is new rural driver for Internet utilization 70% of U.S. farms had Internet connectivity (2012)
  8. 8. Cannabis High margin & high cost Most high value (legal) crop in the world Easier to develop or implement tech compared to other crops Lighting (e.g. LED tech), water conservation, hydroponics, aeronautics & robots
  9. 9. The Introduction of Venture Capital AgTech startups raised more than $320 million (2017) Increase in Series B financings Diverse range of investment themes Willing & active venture investors
  10. 10. The Rise of Big Data Farm data: site-specific data (e.g. info about seeding rates, soil nutrients, fertilizer, pesticides, water, yield data) Meta data (e.g. info about number of acres, inputs applied, crops) Big data (e.g. aggregation of farm data from numerous operations)