Acquisition and analysis of the optimal nutrient solution temperature range for lettuce using U-chord curvature

Extreme nutrient solution temperature significantly affects photosynthetic characteristics of hydroponic vegetables and gives rise to slow plant growth. In this study, a method was proposed to obtain the suitable nutrient solution temperature range of hydroponic crops. Nested experiments of net photosynthetic rates were designed. The experiments considered the impact of nutrient solution temperatures, air temperatures, photon flux densities, and CO₂ concentrations. Then we established a prediction model of photosynthetic rate based on a regression support vector machine. The results have shown that the coefficient of determination between the measured values and the predicted values of photosynthetic rate is 0.982, and the root mean square error is 0.990 μmol/m²·s. Taking the net photosynthetic rate prediction model as the objective function, the maximum photosynthetic rate could be found using multiple population genetic algorithms, and then the nutrient solution temperature response curve could be created. According to the U-chord curvature theory, the suitable nutrient solution temperature range was calculated. After optimization by the multi-population genetic algorithm, the coefficient of determination between measured values and optimized values of maximum photosynthetic rate was 0.989 and the mean square error was 0.003. An analysis of the calculation based on the theory of U-chord curvature indicated that the suitable nutrient solution temperature range to grow hydroponic lettuce is 20.04°C-26.32°C. The proposed method provides a solid foundation to accurately acquire the suitable nutrient solution temperature range for a crop grown in hydroponics.