Browsing by Subject "Lumineszenzdiode"

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Exploring and modelling the influence of spectral light composition on soybean (Glycine max (L.) Merr.)
(2019) Hitz, Tina; Graeff-Hönninger, Simone
The development of soybean cultivars for the climatic conditions in Europe is an urgent need in order to increase the European production and to decrease the dependence of imported soybean. A speed breeding system can accelerate the process of developing new cultivars by growing more generations per season in climate chambers. The project MoLED-Plant aimed towards the development of a speed breeding system for soybean under LED lighting. The major objectives of this thesis were to: (i) construct a three dimensional model of an LED chamber to simulate micro-light climate, (ii) develop a functional-structural plant (FSP) model of soybean and derive a blue photon flux density (BPFD) response curve from simulations, (iii) apply the FSP model with the integrated response curve for spectral optimization, (iv) explore the influence of BPFD under constant photosynthetic photon flux density (PPFD), and (v) disentangle the influence of red to far-red ratio (R:FR) and PPFD on the shade avoidance response (SAR). The objectives were fulfilled with a combination of FSP modelling in the Growth Grammar-related Interactive Modelling Platform (GroIMP) and plant experiments under multiple spectra in LED chambers. The presented LED chamber model was the first three dimensional environment, which was developed for spectral optimizations in indoor farming using FSP modeling. Measurements performed with a spectrometer in multiple heights and orientations were compared to simulations recorded with a virtual sensor at the same locations. The model was evaluated as a tool for assessment of spectral light heterogeneity under an alternative placement of the LED modules. Applying the model can assist in choosing the best chamber design and placements of LEDs to assure homogeneous light conditions. Subsequently, static soybean plants were incorporated into the chamber model. Comparison of light simulations and measurements from below the soybean canopy in four reconstructed scenarios assured a good simulation of micro-light climate. The model was applied to simulate the effect of an increased plant density in an experiment in the chamber. The simulations of light homogeneity in the experimental setup can assist in choosing the optimal design. The developed dynamic FSP model of soybean within the chamber model represents the first FSP model with an integrated response to BPFD. The soybean model was calibrated with data from BPFD experiments. From simulations, a common response curve of internode elongation to the perceived BPFD was derived for the second and third internode. The response curve was integrated in the model and was applied for spectral optimization in a chamber scenario with an alternative high reflective bottom material. The soybean response to BPFD under constant PPFD and the influence of R:FR and PPFD on SAR was explored by designing specific spectra from LEDs. Soybean experiments were performed under six levels of BPFD (60-310 µmol m-2 s-1) and constant PPFD (400 µmol m-2 s-1). Plant height and biomass decreased, leaf mass ratio increased and the ratio of stem biomass (internode plus petiole) translocated to the internode decreased under high BPFD. Three soybean cultivars were grown under nine light treatments to disentangle the effect of R:FR and PPFD. Internode elongation responded mainly to low PPFD with an additive effect from low R:FR, whereas petiole elongation was influenced to a great extent by low R:FR. In the context of SAR, petiole elongation can be seen as the main response to the threat of shade (high PPFD and low R:FR) and both petiole and internode elongation as the response to true shade (low PPFD and low R:FR). This thesis showed how PPFD, BPFD and R:FR work both independently, antagonistically and synergistically on the physiology and morphology of soybean. The increased insight in these responses can e.g. support crop breeding and spectral optimization in indoor farming. Furthermore, interesting and important objectives for future research were identified. These experiments should include physiological measurements for a deeper understanding of interactions and underlying mechanisms. Spectral optimization of indoor farming depends on the purpose of the production. For instance, a high BPFD of 260 µmol m-2 s-1 was optimal for speed breeding, whereas an intermediate BPFD would be preferable to increase biomass. Comprehensive investigation of spectral influence on plant physiology and morphology is necessary to fully utilize the spectral flexibility of LED lighting. The developed FSP model of soybean in a virtual LED chamber represents an important step towards utilizing the advantages of FSP modelling by simulation of a wide variety of scenarios. The model can be adjusted or extended depending on the purpose of the model. It can be calibrated for other crop species and the setting of the chamber dimensions can be changed.
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.