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Abstract

Controlled environment agriculture (CEA) consists of producing crops within indoor settings rather than in open fields. This thesis explores the integration of emerging techniques and technologies in CEA through two complementary studies focused on lighting and nutrient management, testing two high-value crops: Cannabis (Cannabis sativa L.) and strawberry (Fragaria × ananassa (Duchesne ex Rozier)). My first study investigated the influence of LED light spectra on the metabolism of in vitro Cannabis in advanced growth chambers. Plantlets were exposed for seven days to one of three lighting conditions: full spectra control, red, or blue LED spectra. Meristematic tissue was then analyzed using a combination of commercial cannabinoid quantification, targeted metabolomics for plant hormones, and untargeted metabolomics for compound and pathway discovery. Blue light stimulated the accumulation of flavonoids and gibberellins, whereas red light led to increased concentrations of carboxylic acid derivatives. All treatments showed widespread amino acid conjugation. Many biosynthetic or metabolic pathways, particularly those involving tryptophan, tyrosine, and phenylalanine, were associated with shikimate and MEP/MVA pathways, connecting light to plant secondary metabolites. My second study developed and tested a proof-of-concept fertigation system for strawberries, an emerging greenhouse crop experiencing rapid market expansion in Canada. Using a Youden square experimental design, the study evaluated the performance of advanced agriculture technology, or agri-tech, sensor systems (Vivent BioSignals and Grodan GroSens) alongside conventional laboratory analysis (ICP-OES), under various fertilizer treatments delivered by an automated irrigation system (NourishLabs). The system was stable across treatments, indicating a limited capacity to modulate nutrient uptake only through fertilizers. My work established correlations between sensors and lab analyses, especially for manganese across plant, substrate, and leachate samples. Together, these studies provide insights into both the potential and the practical limitations of integrating emerging technologies into CEA.