Validation of an air temperature gradient using computational fluid dynamics in a semi-open type greenhouse and determination of kimchi cabbage physiological responses to temperature differences

Vegetable crops production in the field and changes in physiological aspects of crops during the growing season may be affected by the increased temperatures associated with climate change. The objectives of this research were to evaluate the performance of an air temperature gradient using the computational fluid dynamics (CFD) technique and validation of performance throughout Kimchi cabbage growth and physiological responses to air temperature in a greenhouse temperature gradient (GTG). We simulated temperature differences with CFD in a semi-closed plastic tunnel, which is a GTG. The accuracy of CFD improved by vertical and horizontal temperature profiles was evaluated for the performances of a GTG. The growth of Kimchi cabbage was examined and validated using a temperature gradient within a GTG. Correlation coefficients of measured heights were 1.120, 0.597, and 0.459. Root mean square error was below 0.103, which means the CFD simulation values were highly accurate. The error analysis showed that it was possible to accurately predict temperature gradient changes within a GTG using CFD techniques. CFD results showed an average error of 0.597 °C compared to field monitoring results. The maximum temperature difference of the GTG was 5.7 °C, suggesting a well-controlled set point (6 °C difference between outside conditions and inside conditions of the GTG). On a cloudy day, the GTG set differential temperature (dT) was well maintained, while the accuracy of the GTG’s dT was degraded on sunny days because of interference by solar radiation. There was a significant difference in the growth, net photosynthetic rate, transpiration rate, and intercellular CO₂ concentration along with temperature differences in the GTG. CFD can simulate temperature gradient distribution in a GTG and predict the temperature difference for equipment with different specifications. These facilities can be used in climate change-related studies, such as assessment of crop production area optimization, crop physiological response to temperature, vulnerability assessment of crop production under increasing temperatures, or extreme weather.