NSF Award
1622215
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to create a new low cost decision support tool to help growers optimize resources and grow more crop per drop. The company is developing extremely low cost environmental sensors that will enable growers to capture highly granular environmental data in the field and derive optimal irrigation strategies through the application of data science. Water is a major contributor to crop yields and growers struggle to deal will water scarcity and quality, coupled with variability in the soils and irrigation systems. Through the use of a data driven, closed loop decision support tool, growers will be better equipped to deal with variability, make better resource use decisions and improve crop yields. This new approach has the potential to enable growers to increase yields by as much as 15% while maintaining or reducing water use.<br/><br/>This Small Business Innovation Research (SBIR) Phase I project will enable the detection of moisture and soil texture in soils using a low cost soil moisture sensor based on magnetics. Growers rely on field data, including soil moisture, to make daily decisions that impact plant health. The most significant decision is when to apply water and in what quantity. Current approaches to detecting soil moisture (and other soil characteristics) in an automated fashion are expensive and unreliable leaving growers searching for alternatives. The objective of this project is to develop a sensitive, accurate, and reliable sensor that measures soil moisture using a novel, magnetics based approach. During the project the team will build prototype sensors, test them in lab and field environments, develop algorithms for calibrating the sensor, and explore new approaches to presenting multidimensional field data to growers in a manner that facilitates understanding and decision making.
