Growth of algal biomass in laboratory and in large-scale algal photobioreactors in the temperate climate of western Germany.

Growth of Chlorella vulgaris was characterized as a function of irradiance in a laboratory turbidostat (1L) and compared to batch growth in sunlit modules (5-25L) of the commercial NOVAgreen photobioreactor. The effects of variable sunlight and culture density were deconvoluted by a mathematical model. The analysis showed that algal growth was light-limited due to shading by external construction elements and due to light attenuation within the algal bags. The model was also used to predict maximum biomass productivity. The manipulative experiments and the model predictions were confronted with data from a production season of three large-scale photobioreactors: NOVAgreen (<36,000L), IGV (2,500-3,500L), and Phytolutions (28,000L). The analysis confirmed light-limitation in all three photobioreactors. An additional limitation of the biomass productivity was caused by the nitrogen starvation that was used to induce lipid accumulation. Reduction of shading and separation of biomass and lipid production are proposed for future optimization.

Quantitative imaging of rhizosphere pH and CO2 dynamics with planar optodes.

BACKGROUND AND AIMS: Live imaging methods have become extremely important for the exploration of biological processes. In particular, non-invasive measurement techniques are key to unravelling organism-environment interactions in close-to-natural set-ups, e.g. in the highly heterogeneous and difficult-to-probe environment of plant roots: the rhizosphere. pH and CO2 concentration are the main drivers of rhizosphere processes. Being able to monitor these parameters at high spatio-temporal resolution is of utmost importance for relevant interpretation of the underlying processes, especially in the complex environment of non-sterile plant-soil systems. This study introduces the application of easy-to-use planar optode systems in different set-ups to quantify plant root-soil interactions. METHODS: pH- and recently developed CO2-sensors were applied to rhizobox systems to investigate roots with different functional traits, highlighting the potential of these tools. Continuous and highly resolved real-time measurements were made of the pH dynamics around Triticum turgidum durum (durum wheat) roots, Cicer arietinum (chickpea) roots and nodules, and CO2 dynamics in the rhizosphere of Viminaria juncea. KEY RESULTS: Wheat root tips acidified slightly, while their root hair zone alkalized their rhizosphere by more than 1 pH unit and the effect of irrigation on soil pH could be visualized as well. Chickpea roots and nodules acidified the surrounding soil during N2 fixation and showed diurnal changes in acidification activity. A growing root of V. juncea exhibited a large zone of influence (mm) on soil CO2 content and therefore on its biogeochemical surrounding, all contributing to the extreme complexity of the root-soil interactions. CONCLUSIONS: This technique provides a unique tool for future root research applications and overcomes limitations of previous systems by creating quantitative maps without, for example, interpolation and time delays between single data points.

Non-invasive approaches for phenotyping of enhanced performance traits in bean.

Plant phenotyping is an emerging discipline in plant biology. Quantitative measurements of functional and structural traits help to better understand gene-environment interactions and support breeding for improved resource use efficiency of important crops such as bean (Phaseolus vulgaris L.). Here we provide an overview of state-of-the-art phenotyping approaches addressing three aspects of resource use efficiency in plants: belowground roots, aboveground shoots and transport/allocation processes. We demonstrate the capacity of high-precision methods to measure plant function or structural traits non-invasively, stating examples wherever possible. Ideally, high-precision methods are complemented by fast and high-throughput technologies. High-throughput phenotyping can be applied in the laboratory using automated data acquisition, as well as in the field, where imaging spectroscopy opens a new path to understand plant function non-invasively. For example, we demonstrate how magnetic resonance imaging (MRI) can resolve root structure and separate root systems under resource competition, how automated fluorescence imaging (PAM fluorometry) in combination with automated shape detection allows for high-throughput screening of photosynthetic traits and how imaging spectrometers can be used to quantify pigment concentration, sun-induced fluorescence and potentially photosynthetic quantum yield. We propose that these phenotyping techniques, combined with mechanistic knowledge on plant structure-function relationships, will open new research directions in whole-plant ecophysiology and may assist breeding for varieties with enhanced resource use efficiency varieties.