STTR Phase I: Visual Information eNvironment for Effective agricultural management and Sustainability

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project will be to develop technology to conserve scarce water resources and improve crop management practices. Agricultural production uses a great deal of water. In California alone, 80% percent of all water usage goes to agriculture. As communities expand and drought conditions develop, the competition for scarce and expensive water resources has become intense. Growers have to be able to minimize costs and water needs by making their irrigation practices more efficient. While new irrigation application technologies have reduced losses from wind drift, leakages and evaporation, large amounts of water are still be wasted as it washes through the soil past crop roots. The technology developed in this project will allow producers to track soil moisture movement through the soil profile and across fields. This will allow producers to develop irrigation strategies based on the unique conditions of their soil types and topography and reduce water waste. It will save producers money and enable them to stay in business and meet new governmental regulations regarding irrigation. Improvements in water management efficiencies and better crop management practices can increase crop production, reduce food costs, and help preserve the environment. This STTR Phase I project proposes to develop a science-based approach to optimally determine the number, location, and depths of sensors. The goal is to accurately measure and then model soil properties throughout the root zone and across the field for use in precise, effective and efficient water and crop management through the use of 3D proprietary precision soil mapping. Integrated enological, viticultural, and statistical predictive models will relate these environmental conditions and historical data to crop quality and volume, and long-term tree/vine health. Additionally, a novel interactive spatial and temporal visual analytics environment will organize the resulting massive data flows and novel predictive models to enable stakeholders to perform precision management of crops based on soil moisture conditions. By developing this optimal sensing strategy, affordable, precise soil maps and data-driven soil property models, crop composition and volume models based on environmental and historical data, and novel, understandable predictive visual analytic tools, this project will result in new crop science insights and environmental associations, as well as a much-needed precision water and crop management technology.