Agriculture

button-pdfAgriculture


For thousands of years mankind has struggled with the most efficient ways to grow food to feed the masses. Growers used experience and luck to manipulate variables in hopes of a bumper crop. Now data for variables such as soil composition, weather, insect management, environmental issues and maximum yield have caused the industry to turn to applying that data for answers. Data scientists apply agricultural based predictive analytics over a vast quantity of variables to gain insights on how to better feed the human population, as well as promote optimal levels of sustainability.

Environmental

  • Chemical optimization for pollution reduction
  • Field CO2 emission reduction
  • Predictive soil-mix analysis
  • Strategic workforce analysis
  • Predictive field characteristic analysis
  • Water usage reduction

Yield

  • Predictive field / product analytics
  • Predictive weather modeling
  • Predictive maintenance on machinery & equipment
  • Predictive maintenance on manufacturing equipment – reducing down times
  • Real time data decision making vs predetermined scheduling
  • Predictive asset utilization scheduling
  • Competitive intelligence 

Distribution

  • Logistic optimization to maximize yield / reduce waste
  • Predictive weather modeling
  • Temperature / climate decision making optimization
  • Seasonality workforce scheduling 

Contact Mosaic today to learn more.