Browsing by Person "Schmierer, Marc"

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Chamber‐based system for measuring whole‐plant transpiration dynamics
(2022) Pieters, Alejandro; Giese, Marcus; Schmierer, Marc; Johnson, Kristian; Asch, Folkard
Most of our insights on whole‐plant transpiration (E) are based on leaf‐chamber measurements using water vapor porometers, IRGAs, or flux measurements. Gravimetric methods are integrative, accurate, and a clear differentiation between evaporation and E can be made. Water vapor pressure deficit (VPD) is the driving force for E but assessing its impact has been evasive, due to confounding effects of other climate drivers. We developed a chamber‐based gravimetric method, in which whole plant response of E to VPD could be assessed, while keeping other environmental parameters at predetermined values. Stable VPD values (0.5–3.7 kPa) were attained within 5 min after changing flow settings and maintained for at least 45 min. Species differing in life form and photosynthetic metabolism were used. Typical runs covering the range of VPDs lasted up to 4 h, preventing acclimation responses or soilborne water deficit. Species‐specific responses of E to VPD could be identified, as well as differences in leaf conductance. The combined gravimetric‐chamber‐based system presented overcomes several limitations of previous gravimetric set ups in terms of replicability, time, and elucidation of the impact of specific environmental drivers on E, filling a methodological gap and widening our phenotyping capabilities.
Estimating the quantum requirements for plant growth and related electricity demand for LED lighting systems
(2021) Schmierer, Marc; Brueck, Holger; Asch, Folkard; Sauerborn, Joachim
Indoor plant production systems with artificial lighting are considered an emerging technology contributing to biomass-based value webs. The viability of this concept greatly relies on the energy requirements (ER, Watt) for lighting. We estimated the ER for plant growth by calculating the conversion efficiency of electricity to light of solid-state light-emitting diodes (LED) and the quantum requirements for plant growth of a fictional plant stand producing 2500 g of dry weight per m2 of ground during 100 days, representing a high productivity benchmark of field crops. The quantum output (µmol s−1 W−1) of eight LEDs of different colours varied between 0.78 for green and 2.54 for deep red. Uncertainty in the H+ demand for ATP synthesis during photosynthesis, the relative portion of photorespiration and the fraction of light intercepted by plant canopies (fabs) were considered in a pessimistic (PA) and optimistic (OA) approach of calculation of ER. Cumulative ER were 606 and 265 kWh m−2 for the PA and OA scenarios. The energy conversion efficiencies in the PA and OA scenarios were 2.07 and 4.72%. Estimates of energy savings by suppressing photorespiration and increasing fabs vary between 24 and 38%. The peak daily ER were 9.44 and 4.14 kWh in the PA and OA scenarios. Results are discussed in the context of the design of lighting in indoor plant production systems and commercial greenhouses where natural fluctuation in solar radiation could be balanced by dimmable LED panels.
Photosynthesis, quantum requirements, and energy demand for crop production in controlled environments
(2020) Schmierer, Marc; Asch, Folkard
In this work, energy costs for LED (light emitting diodes) lighting of a virtual plant stand exhibiting C3photosynthesis have been calculated via a model considering the quantum demand to build-up dry matter and energy efficiency of state-of-the art LEDs. Optimistic and pessimistic scenarios have been calculated by taking into account uncertainties regarding the H+/ATP stoichiometry of photosynthesis and different management strategies for indoor plant production. Energy costs were between 265 and 606 kWh for a production cycle ranging over 100 days and resulting in 2500 g dry matter per square meter for the optimistic and the pessimistic scenario respectively. The conversion efficiencies from electrical energy to energy bound in phytomass at the end of the production cycle were 2.07 % and 4.72 % (pessimistic and optimistic scenario, respectively). This was lower than the theoretical maximum values calculated for C3 plants that are given as 9.5 % in the literature. However, when the losses that occur during the conversion from electrical energy to light energy were excluded and only the efficiency of the conversion from incident light energy to phyto-energy was calculated, values increased to 4.0 and 9.1 %. The differences between the optimistic and the pessimistic scenario was caused by decreased photorespiration via carbon dioxide fertilization, which increased the conversion efficiencies by 38 %, followed by different assumptions about the H+ requirement for ATP production (34 %) and an increased rate of active absorption of light energy (24 %). Considering cumulative as well as feedback effects of all of the mentioned parameters, the conversion efficiency in the optimistic scenario was 2.3 times higher than in the pessimistic scenario. A system for measuring gas-exchange of whole plants or plant stands was developed in order to be able to investigate and improve the above mentioned management strategies in the future. CO2 sensors and temperature and humidity sensors were used to detect water loss and CO2. Readily available off-the-shelf electronic and mechanical materials were used in order to build a low-cost system that can be used in high throughput experiments. The results indicate that around 90 % of the transpirational water was detected by the system. We conclude that parts of the transpirational water condensed on the surfaces thus not leaving the chamber. When checking the accuracy of the H2O and CO2 sensors using an industry quality infrared gas analyser (IRGA), we found significant deviations from the values given by the IRGA and used this data for calibration of the CO2 sensors. The responses of the CO2-sensors were also linearly coupled to the H2O concentrations (about -0.1 % ppm CO2 / ppm H2O). A regression analysis was performed and the coefficients were used to correct the sensor readings. Since LEDs exhibit a higher energy-to-light ratio when operated at lower light levels, we tested a very small growing gibberellin (GA) deficient super dwarf rice genotype in a climate chamber experiment under different illumination levels and different levels of nitrogen supply to assess its suitability for crop production in artificial environments. A 25 % reduction in illumination lead to a 75 % reduction in yield, mainly due to a 60 % reduction in formed tillers and 20 % reduction in kernel weight, and an 80 % reduction in illumination caused total yield loss. Whereas leaf area under reduced illumination was significantly lower, only marginal changes in the dimensions of single leaves were observed. Photosynthesis at growing light conditions was not different between control plants and plants under 75 % illumination. This was explained by a higher photochemical efficiency under lower light conditions and a reduced mesophyll resistance. Therefore, we conclude that this genotype is an interesting candidate for crop production in vertical plant production systems, especially because of its short stature and the absence of shade avoidance mechanisms, such as leaf elongation, that would complicate production in small-height growing racks under low-light conditions. Nitrogen concentrations of 2.8 and 1.4 mmol L-1 in the nutrient solution lead to no differences in plant growth. We conclude that a nitrogen concentration of 1.4 mmol L-1 is sufficient for this genotype under the light intensities that were applied here. A software tool for simulations of photosynthesis in the python programming language was developed. The software implements a classical Farquhar-von CaemmererBerry (FvCB) model of leaf photosynthesis coupled with a model for the estimation of stomatal behaviour dependent on environmental conditions. We want to emphasize that the use of such models is essential to understand the complex interactions between plant growth, leaf photosynthesis and the environment. Knowledge on those relationships is the key to improve the efficiency of plant production in controlled environments.