Optimizing the photon ratio of red, green, and blue LEDs for lettuce seedlings: a mixture design approach

Light control technology has been developed and studied for decades in controlled environment agriculture (CEA) for successful crop production. The effects of the light spectrum on plant growth can vary because plants have spectral specific responses, and mixed light elicits interactive combination effects. Response surface methodology (RSM) can be utilized with the design of experiments to optimize a response influenced by multiple inputs with limited data. In this study, we aimed to identify the optimal photon ratio in combination of red (R), green (G), and blue (B) light-emitting diodes (LEDs) for growing lettuce seedlings using RSM and a seedling-indicating parameter by performing a similarity analysis of response surfaces that elucidated the response tendency of different factors, such as light quality.

The highest shoot fresh weight was obtained from the R treatment (red LED 100%) at the end of the seedling stage. However, the RGB₁₄₁ (photon ratio of R:G:B = 1:4:1) treatment during the seedling stage resulted in the highest shoot fresh weight at the final harvest. The value of the leaf area multiplied by the leaf chlorophyll concentration (SPAD) was selected as the seedling-indicating parameter. The optimal RGB photon ratio that maximized this parameter was R:G:B = 30.6:44.0:25.4, and this ratio was verified by conducting identical cultivation experiments. During the first 6 days after transplanting, SPAD gradually increased in R-treated seedlings, while the optimal treatment maintained the value at a higher constant level, which supported our result of shoot fresh weight at harvest.

Thus, we confirmed that the mixture design method allowed us to optimize the combined RGB photon ratios for the seedling stage in order to maximize the growth index of mature lettuce plants and to select an appropriate seedling-indicating parameter that represents the final harvest results to benefit crop production in CEA.