Sequential RGB light optimization across developmental stages enhances lettuce growth through carry-over effects

Light is a critical factor regulating plant development and productivity under controlled environment conditions. However, the light conditions are often kept static throughout the cultivation period, potentially overlooking plants' dynamic responses to changing environmental stimuli over time. This study proposes a stage-specific optimization strategy to maximize lettuce growth, based primarily on shoot fresh weight by adjusting red:green:blue (R:G:B) light ratio at different growth stages. After transplanting 2-week-old seedlings, their growth period was divided into an early stage (ES, the first 2 weeks) and a late stage (LS, after 2 weeks). To account for potential carry-over effects, the ES optimization was designed to evaluate how early-stage light conditions influence final growth performance. Response surface methodology was then employed to identify the optimal spectral combinations for each stage. The optimal R:G:B light ratios were determined to be 44.2:55.8:0 for ES and 25.2:57.8:16.9 for LS. These results suggest that excluding B light during ES promotes morphological traits favorable for light interception, presumably at the expense of immediate photosynthetic efficiency, and ultimately supporting enhanced biomass accumulation during LS. A sequential-optimized lighting strategy combining these two stage-specific light ratios was then evaluated against other lighting strategies, including a static-optimized, a reference, two white LED treatments with different color temperatures of 2700 and 5000 K. While the static-optimized treatment with an R:G:B ratio of 77:23:0 produced the highest shoot fresh weight during ES, the sequential-optimized ultimately delivered the greatest biomass by the end of the growth stage. These findings highlight the importance of stage-specific light requirements and demonstrate that dynamic light management aligned with developmental physiology can significantly enhance crop productivity. This study provides a practical framework for implementing adaptive light strategies in controlled environment systems.