Current mist irrigation practices in plant propagation do not represent the variable rate of water loss experienced in a greenhouse environment and often rely on grower experience for adjusting irrigation settings. Automated control logic for these systems can be improved by considering climate data to predict the real-time water loss in the propagation environment. The objectives of this study were to 1) identify the impacts of environmental parameters on the water loss of young plants in greenhouses and indoor environments and 2) develop an evapotranspiration model based on the key parameters identified to achieve weather-based mist irrigation control for resource-efficient plant propagation in controlled environment agriculture. Data sets that include climate data, water applied, and water loss were collected in greenhouse sunlight and indoor sole-source LED environments with unrooted chrysanthemum cuttings. Trials were completed in June and September in 2023 and February in 2024 to collect diverse minute-by-minute data in each environment. Measurements using load cells indicated highly variable water loss in the greenhouse environment. Conversely, in the indoor environment with lower and constant photosynthetic photon flux density (PPFD) and reduced vapor pressure deficit via a fog system, rate of water loss was lower and consistent over time. The key parameters for modeling water loss, found using stepwise regression, were PPFD, leaf temperature, and air vapor pressure (temperature and relative humidity). These climate parameters were correlated with water loss data over time to yield a simple evapotranspiration equation that could be programmed into commercial environmental control systems to improve current irrigation scheduling programs. By improving the control of mist irrigation to take climate data into account, growers have the potential to reduce crop losses (“shrinkage”), reduce rooting time, and improve water use efficiency.
