Modeling Lettuce Growth in Vertical Farms: Approaches and Strategies

Vertical farming is an advanced agricultural system that provides precise environmental control to promote uniform crop growth and enables planned year-round production.This study investigated lettuce growth in a fully controlled vertical farm over 31 days, measuring shoot fresh and dry weights to develop growth prediction models.Several mathematical models, in this case linear, quadratic, exponential, sigmoid, and expolinear functions, were evaluated for their suitability.Linear and quadratic models showed limited accuracy and practical limitations, while the exponential model did not account for the growth deceleration observed in lettuce, making it unsuitable.The sigmoid and expolinear models both effectively captured the biological growth pattern characterized by slow initial growth, a rapid mid-stage increase, and a late-stage plateau.Notably, the expolinear model demonstrated the highest predictive accuracy, with coefficients of determination exceeding 0.99 in the fitting data and 0.93 in validation data during the marketable growth period (up to 28 days after transplanting).Beyond this period, excessive leaf growth reduced market value, emphasizing the need for growth modeling focused on commercial quality maintenance.These findings highlight the expolinear model as a reliable tool for predicting lettuce growth and optimizing harvest timing in vertical farms.