Dynamic modelling of lettuce transpiration for water status monitoring

Abstract

Real-time information on the plant water status is an important prerequisite for the precision irrigation management of crops. The plant transpiration has been shown to provide a good indication of its water status. In this paper, a novel plant water status monitoring framework based on the transpiration dynamics of greenhouse grown lettuce plants is presented. Experimental results indicated that lettuce plants experiencing adequate water supply transpired at a higher rate compared to plants experiencing a shortage in water supply. A data-driven model for predicting the transpiration dynamics of the plants was developed using a system identification approach. Results indicated that a second order discrete-time transfer function model with incoming radiation, vapour pressure deficit, and leaf area index as inputs sufficiently explained the dynamics with an average coefficient of determination of 2 = 0.93 ± 0.04. The parameters of the model were updated online and then applied in predicting the transpiration dynamics of the plants in real-time. The model predicted dynamics closely matched the measured values when the plants were in a predefined water status state. The reverse was the case when there was a significant change in the water status state. The information contained in the model residuals (measured transpirationmodel predicted transpiration) was then exploited as a means of inferring the plant water status. This framework provides a simple and intuitive means of monitoring the plant water status in real-time while achieving a sensitivity similar to that of stomatal conductance measurements. It can be applied in regulating the water deficit of greenhouse grown crops, with specific advantages over other available techniques.

Light and Low Relative Humidity Increase Antioxidants Content in Mung Bean (Vigna radiata L.) Sprouts

“…In this context, controlled environment agriculture (CEA) and, more specifically, urban farming (e.g., rooftop greenhouses, indoor-growing modules) is receiving increasing attention as a method to improve food security, enhance sustainability, and contribute to saving transportation and logistics costs [ 4 , 5 ]. Currently, we are witnessing a growing interest in urban agriculture, which has been well documented by backyard food production, local-sustainable-organic restaurants, and the rise of plant-based-diets, suggesting that people desire to “get closer to their food” [ 6 , 7 , 8 ]. Plant-derived fresh food not only has high nutritional value but also plays a role as a stress mitigator for citizens who are subjected to urbanicity effects [ 9 , 10 , 11 ].…”

Design Configuration of Water Quality Monitoring System in Surabaya

“…Depends on the monitoring type, the water monitoring methodologies are divided into offline, online, and remote-online monitoring methods. The offline monitoring methods were the conventional way to monitor the water quality which was not suggested anymore [15,24]. Online monitoring was a promising method to monitor the water quality.…”

“…Agriculture [15], aquaculture [16], and disaster prone [10] area can be categorized as one area category of water monitoring. In these areas, it was important to monitor the water especially the necessary amount of water which was used for irrigation [17].…”

“…Several parameters have been considered in water monitoring, such as Fluid Level [6], Viscosity [7], Water Needs [15,17], Leakage [23,24], Volatile Organic Compounds (VOC) [4,28], Environment Parameter (temperature, humidity, pollution) [25,16], and Water Quality Parameter (pH, oxygen, turbidity, conductivity, mineral content) [5,21] as shown in Figure 2. Not all the mentioned parameter directly related to water quality monitoring.…”

“…The plant water needs to be fulfilled, however the needs are not necessary to be fulfilled every time. Therefore, the water needs for plant are considered parameter to be monitored in agriculture area [8,15] which was determined by using external information such as the temperature surrounding the plant and internal information such as the leaf temperature [8]. The water needs speak about the water volume which has similarity to water usage.…”