Lead Researcher: Joshua Craver
Contact: Joshua Craver
Industry Partners: Vertical Irrigation LLC  

Vertical indoor farming is capturing a larger market share of food production, yet problems in this nascent field remain. Indoor farming benefits from reduced water consumption by employing closed system techniques such as hydroponics and aquaponics, however, optimizations can be further improved with systems automation and waste reduction. Reducing operation expenses is achievable by deploying passive and reusable sensors that acquire actionable information that can then be used for machine learning optimizations. Our state-of-the-art opto-electronic and photonic sensors monitor environmental conditions, and, when paired with linear regression-based analysis techniques can correlate the signal outputs to product yield and operation efficiencies. The goal of this proposal is to study the efficacy of this “big-data” approach to agriculture by comparing profit margins of vertical farming systems with and without the use of our custom remote monitoring system over multiple grow cycles. We expect to see a simplified workflow by automating plant and systems monitoring, which reduces labor cost, and we expect a more uniform and high-volume product yield, both of which boost profit margins.

Vertical irrigation technologies can reduce some of the water and energy used for crop production and optimizing lighting in these irrigation systems may make it possible to significantly reduce other inputs.  

This project is focused on developing and testing computer vision techniques to measure microgreens growth in real time and determine if they can be used to dynamically and automatically adjust growing conditions to target a range of microgreen quality attributes while improving operational efficiency. The computer vision is being used to measure the height and fresh weight of various microgreens species as they grow and evaluating the effects of dynamic light-emitting diode (LED) lighting on yield, operating costs (e.g., electrical energy consumption and water use), and quality attributes of microgreens. 

Through active collaboration with industry partner Vertical Irrigation, the team has developed an imaging platform capable of non-destructively tracking changes in daily microgreen growth and has used it to research the influence of far-red light on the growth and morphology of cilantro, kohlrabi, mustard, and radish microgreens. These experiments were completed in January 2021; data analysis is underway.