Plant-Response-Based Control Strategy for Irrigation and Environmental Controls for Greenhouse Tomato Seedling Cultivation

Abstract

Most existing greenhouse decision support systems only consider external environmental factors, such as soil and atmosphere, rather than plant response. A conceptual plant-response-based strategy for irrigation and environmental controls for tomato (Solanum lycopersicum) seedling cultivation in greenhouse operations was proposed. Because stomatal conductance (gsw) is a comprehensive indicator of plants, soil moisture, and atmospheric conditions, this study used gsw to design a conceptual system by employing factors affecting gsw as the key for decision-making. Logistic regression was performed with independent variables (i.e., temperature (Tair), vapor pressure deficit (VPD), and leaf–air temperature difference) to predict the gsw status. When the gsw status was “low,” the system entered into the environmental control component, which examined whether the VPD and the photosynthetic photon flux density (PPFD) were in the normal range. If the VPD and the PPFD were not in the normal range, the system would offer a suggestion for environmental control. Conversely, when both parameters were in the normal range, the system would determine that irrigation should be performed and the irrigation amount could be estimated by the evapotranspiration model. Thus, the strategy only considered leaf temperature, Tair, VPD, and PPFD, and the overall error rate to characterize gsw was below 13.36%.

Using Artificial Intelligence Algorithms to Estimate and Short-Term Forecast the Daily Reference Evapotranspiration with Limited Meteorological Variables

“…Furthermore, greenhouse cultivation is rapidly growing and as the water demand cannot be met through rainfall, it must be supplied through irrigation. However, irrigation in greenhouses is often based on a fixed schedule or the grower's experience, often leading to insufficient irrigation or excessive waste of water resources [69]. Utilizing evapotranspiration information to determine the appropriate timing and amount of irrigation can greatly enhance the precision of greenhouse cultivation.…”

Exploring Efficient Methods for Using Multiple Spectral Reflectance Indices to Establish a Prediction Model for Early Drought Stress Detection in Greenhouse Tomato

“…Although irrigation refers to the atmospheric or soil conditions that improve plant growth and increase crop yield [16], conducting irrigation based on the plant response is sometimes more appropriate and accurate [17][18][19]. Initially, the plants respond to stress by reducing one or several physiological functions, and most plants activate their stresscoping mechanisms in this phase.…”