Microgreens are a nutritious but highly perishable vegetable. Local production in Controlled Environment Agriculture (CEA) including greenhouses and vertical farms may be economically viable but there are issues with high operational costs and energy expenses. The objective of this research is to find optimal light (Daily Light Integral) conditions of the growing environment as well as learn about other methods of analyzing plant growth and plant performance, with a goal towards understanding whole-system optimization, which is an important step for future implementation of microgreens and CEA, for example, in urban spaces. The requirement for reduced energy consumption in CEA is crucial and new methods of such systems’ optimization are required. Microgreens species arugula (Eruca sativa), mustard (Brassica juncea), and kale (Brassica oleracea) were sown at a density of 217 grams per m2 on a hemp substrate. Plants were grown in a vertical tower with 5 different light treatments (12, 15, 16, 18, and 21 hours/ day) under white LED lights with a varying light gradient (from ~100 to ~160 μmol·m-2·s-1). A total of four replicate crop cycles have been grown and analyzed. Microgreens were assessed for days to germination, days to harvest (first true leaf is 1 cm long), height at harvest, fresh and dry mass. Ranges of optimal DLI conditions for each species were determined through ANOVA and analytical regression analyses. For instance, it was recommended not to increase the DLI levels above 7-8 mol·m-2·hour-1 if the objective is to increase the height of the produced crop. In addition, an image processing technique, and a Convolution Neural Network (CNN) were integrated which allowed for a real-time monitoring of plant performance, laying the groundwork for future development of predictive growth models for a diverse range of microgreens. Electron Spin Resonance (ESR) spectroscopy was used to evaluate plant responses to different Daily Light Integrals (DLIs) and was proposed as a method of tuning future systems for optimized performance. It was recommended to segment a plant for the future study of plants’ oxidative stress responses with the use of ESR, in which ESR spectroscopy would allow to assess the concentration of free radicals in plants.