Modeling and Simulation of Growth of Pagoda Sawi Plant (Brassica narinosa L.) with Hydroponic System in Plant Factory

Abstract

Pagoda mustard plant (Brassica narinosa L.) is one type of mustard vegetable that has high economic value. This study aims to analyze the effect of environmental variables on the growth of pagoda mustard greens (Brassica narinosa L.) in a plant factory-based hydroponic system and build a mathematical model of plant growth using simple linear regression and polynomial regression approaches. This research was conducted for 30 days of planting period. Environmental variables observed included temperature, light intensity, humidity, pH, nutrient content, and EC, while plant growth variables consisted of plant height, number of leaves, canopy area and wet weight. The main treatment was a variation of irradiation duration, namely 8 hours (RAK 1), 13 hours (RAK 2), and 18 hours (RAK 3). The analysis showed that all environmental variables influenced the growth of pagoda mustard plants. Model validation was conducted using the coefficient of determination (R²) and Root Mean Square Error (RMSE). The third order polynomial regression model provides the best prediction results with the highest R² value reaching 0.985 and the lowest RMSE of 0.0889 in RAK 1, R² of 0.989 and RMSE of 0.176 in RAK 2, and R2 of 0.99 and RMSE of 0.129 for plant height parameters. From the results, RAK 3 showed the highest productivity based on plant wet weight. The developed model has the potential to be used as a growth prediction tool in modern precision cultivation systems.