2026 ASEE Annual Conference & Exposition

Incorporating anaerobic digester (AD) effluent into hydroponic systems presents a promising approach for recycling nutrients from organic waste streams such as food waste. However, successful implementation requires characterization of the digestate’s nutrient composition, appropriate dilution to prevent toxicity and imbalance, and pH adjustment. This study was conducted in two Controlled Environment Agriculture senior level courses (Fall 24 and Fall 25) in Appalachian State University’s Department of Sustainable Technology & the Built Environment. where students were split into teams to conduct a plant growth experiment, analyze results, and compile a research paper collaboratively. The pedagogical goal is to develop a semester-long class project that encourages experiential learning and a student scholar model of active participation in research.
Romaine lettuce (Lactuca sativa var. longifolia) was selected for its short growth cycle (≈60 days), cold tolerance, and suitability for hydroponic cultivation. Treatment 1 (control) used a commercial fertilizer at a “mild vegetative growth” concentration; Treatment 2 (nutrient limited) used a 5% dilution of the control; and Treatment 3 used AD effluent from food waste, added at 12% by volume to achieve similar electrical conductivity as the control. Electrical conductivity, pH, and temperature were monitored throughout the seven-week growing period. At harvest, plants were analyzed for fresh leafy biomass, root biomass, and tissue analysis, with growth visually documented through a photo log. Results showed that the control treatment produced 2.3 times the leafy biomass of the 5% dilution and 2.8 times that of the AD effluent. Root to shoot ratio was highest in the 5% solution, suggesting greater root allocation under nutrient-limited conditions.
The educational goal was for students to take leadership roles in a class project that instills closed-loop thinking, design, experimentation, and teamwork to connect key societal issues (organic waste management) and decentralized food production (hydroponics). A survey designed to assess student learning outcomes was sent to all 32 participants. Responses were recorded using a Likert (1-5) as well as free response. Survey results showed 4.8 (increased understanding of technical system components), 4.7 (increased my confidence in participating in a research team), and 4.5 (increased my confidence in data analysis and interpretation). The ability to conduct the grow experiment during the semester (from seed to harvest in 2 months), results with clear visual differences, unexpected results, peer to peer learning, and hands-on nature were all cited as positive factors for deep learning. This paper details the experiment, results, student learning outcomes, and recommendations for future work.