Abstract
Proximal sensors in controlled environment agriculture (CEA) are used to monitor plant growth, yield, and water consumption with non-destructive technologies. Rapid and continuous monitoring of environmental and crop parameters may be used to develop mathematical models to predict crop response to microclimatic changes. Here, we applied the energy cascade model (MEC) on green- and red-leaf butterhead lettuce (Lactuca sativa L. var. capitata). We tooled up the model to describe the changing leaf functional efficiency during the growing period. We validated the model on an independent dataset with two different vapor pressure deficit (VPD) levels, corresponding to nominal (low VPD) and off-nominal (high VPD) conditions. Under low VPD, the modified model accurately predicted the transpiration rate (RMSE = 0.10 Lm−2), edible biomass (RMSE = 6.87 g m−2), net-photosynthesis (rBIAS = 34%), and stomatal conductance (rBIAS = 39%). Under high VPD, the model overestimated photosynthesis and stomatal conductance (rBIAS = 76–68%). This inconsistency is likely due to the empirical nature of the original model, which was designed for nominal conditions. Here, applications of the modified model are discussed, and possible improvements are suggested based on plant morpho-physiological changes occurring in sub-optimal scenarios.
Highlights
Environmental control is a key factor to increase plant productivity in controlled environment agriculture (CEA) [1]
We report an application of the MEC model on butterhead lettuce (Lactuca sativa L. var. capitate) cultivated under controlled conditions, presenting a modification to the original model
Chlorophyll “a” fluorescence analyses were performed by means of a portable fluorimeter (ADC Bioscientific) on 3 expanded leaves per 4 green- and 4 red-lettuce plants every day, in order to highlight the leaf-age-driven variations in canopy quantum yield of photosystem II (PSII) (CQY), according to Genty et al
Summary
Environmental control is a key factor to increase plant productivity in controlled environment agriculture (CEA) [1]. As we progress in adopting technological advancement, issues related to sensor loss of control or breakage may be experienced Such phenomena would be responsible for modifications occurring at the plant level during the cultivation cycle, such as alterations in plant growth, morphogenesis, and development. There are numerous models which simulate different photosynthetic and plant productivity processes, often focusing on very specific aspects of plant physiology, such as: protection of photosynthetic apparatus through the non-photochemical quenching, mesophyll conductance to CO2 , genotype-environment interactions [20,21,22,23] Among these models, the energy cascade model (MEC) has already been tested to implement crop growth in small prototypes for bioregenerative life support systems (BLSSs) studies and in a lunar/Martian greenhouse [12,24]. This latter trial allowed the portrayal of the model parameters for nominal and off-nominal scenarios for green- and red-leaf plants, since non-identical behavior often occurs for different cultivars/varieties even under the same growth conditions
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