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Quantifying heat and mass exchanges processes of plant leaves is crucial for detailed under-standing of dynamic plant-environment interactions. The two main components of these pro-cesses, convective heat transfer and transpiration, are inevitably coupled as both processes are restricted by the leaf boundary layer. To measure leaf heat capacity and leaf heat transfer co-efficient, we thoroughly tested and applied an active thermography method that uses a transi-ent heat pulse to compute τ, the time constant of leaf cooling after release of the pulse. We validated our approach in the laboratory on intact leaves of spring barley (Hordeum vulgare) and common bean (Phaseolus vulgaris), and measured τ-changes at different boundary layer conditions.By modelling the leaf heat transfer coefficient with dimensionless numbers, we could demon-strate that τ improves our ability to close the energy budget of plant leaves and that modelling of transpiration requires considerations of convection. Applying our approach to thermal im-ages we obtained spatio-temporal maps of τ, providing observations of local differences in thermal responsiveness of leaf surfaces.We propose that active thermography is an informative methodology to measure leaf heat transfer and derive spatial maps of thermal responsiveness of leaves contributing to improve models of leaf heat transfer processes.

[EN] The HyPlant imaging spectrometer is a high-performance airborne instrument consisting of two sensor modules. The DUAL module records hyperspectral data in the spectral range from 400-2500 nm, which is useful to derive biochemical and structural plant properties. In parallel, the FLUO module acquires data in the red and near infrared range (670-780 nm), with a distinctly higher spectral sampling interval and finer spectral resolution. The technical specifications of HyPlant FLUO allow for the retrieval of sun-induced chlorophyll fluorescence (SIF), a small signal emitted by plants, which is directly linked to their photosynthetic efficiency. The combined use of both HyPlant modules opens up new opportunities in plant science. The processing of HyPlant image data, however, is a rather complex procedure, and, especially for the FLUO module, a precise characterization and calibration of the sensor is of utmost importance. The presented study gives an overview of this unique high-performance imaging spectrometer, introduces an automatized processing chain, and gives an overview of the different processing steps that must be executed to generate the final products, namely top of canopy (TOC) radiance, TOC reflectance, reflectance indices and SIF maps., We gratefully acknowledge the financial support by the European Space Agency (ESA) for airborne data acquisition, development of the HyPlant processing chain and data analysis in the frame of the HyFLEX campaign (ESA contract no. 4000107143/12/NL/FF/If CCN3), the FLEXSense campaign (ESA Contract No. RFP/3-15477/18/NL/NA) and the HYPER project (ESA Contract No. 4000112890/14/NL/FF/gp). The Deutsche Forschungsgemeinschaft (DFG) provided additional financial support by the SFB/TR 32 'Pattern in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation' project D2. Moreover, this work has partially been funded by the German Federal Ministry of Education and Research within the German-Plant-Phenotyping Network (DPPN) (project identification number: 031A053), the European Union in the frame of the INTEREG project 'Sensor Products for Enterprises Creating Technological Opportunities in airborne Remote Sensing' (SPECTORS) (project identification number: 143081) and the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number 721995 in the frame of the 'Training on Remote Sensing for Ecosystem Modelling' (TRuStEE) network.

Imaging and non-imaging spectroscopy employed in the field and from aircraft is frequently used to assess biochemical, structural, and functional plant traits, as well as their dynamics in an environmental matrix. With the increasing availability of high-resolution spectroradiometers, it has become feasible to measure fine spectral features, such as those needed to estimate sun-induced chlorophyll fluorescence (F), which is a signal related to the photosynthetic process of plants. The measurement of F requires highly accurate and precise radiance measurements in combination with very sophisticated measurement protocols. Additionally, because F has a highly dynamic nature (compared with other vegetation information derived from spectral data) and low signal intensity, several environmental, physiological, and experimental aspects have to be considered during signal acquisition and are key for its reliable interpretation. The European Cooperation in Science and Technology (COST) Action ES1309 OPTIMISE has produced three articles addressing the main challenges in the field of F measurements. In this paper, which is the second of three, we review approaches that are available to measure F from the leaf to the canopy scale using ground-based and airborne platforms. We put specific emphasis on instrumental aspects, measurement setups, protocols, quality checks, and data processing strategies. Furthermore, we review existing techniques that account for atmospheric influences on F retrieval, address spatial scaling effects, and assess quality checks and the metadata and ancillary data required to reliably interpret retrieved F signals.

Plants almost always grow within a population, however, most of our knowledge of plant growth comes from plants grown as single plants. To identify traits relevant to field, i.e. agronomic conditions, it is critical to investigate plants in populations and not only as single plants. Individuals growing in the same substrate will interact with each other within a defined volume over time. The extent, however, to which the variability of traits, especially root traits, in single plants and individuals in a population differs from each other was still unclear. Further, even less was known about sowing density effects on the whole plant: allocation between root and shoot as a consequence of sowing density.In my PhD, I studied the influence of sowing density on plant shoot and root growth and architecture. I performed various experiments (field experiments, rhizotron experiments, one pot experiment) using two spring barley (Hordeum vulgare L.) cultivars and one introgression line (a cross of a German spring barley cultivar and an Israeli wild accession). I grew the plants as single plants and at different sowing densities and collected data on both shoot and root. In the field experiments, I found that sowing density affected root length density, specific root length, tiller formation, and yield in the field. The alterations in root traits could be explained by changes in seminal and nodal root counts. Further, I will discuss sowing density in the context of lab to field translation, illustrating the challenge by a case study. In the case study, the high tillering and high rooting phenotype of an introgression line in comparison to its German parent, selected in the greenhouse, was only partly expressed in the field, depending on sowing density.

Imaging and non-imaging spectroscopy employed in the field and from aircraft is frequently used to assess biochemical, structural, and functional plant traits, as well as their dynamics in an environmental matrix. With the increasing availability of high-resolution spectroradiometers, it has become feasible to measure fine spectral features, such as those needed to estimate sun-induced chlorophyll fluorescence (F), which is a signal related to the photosynthetic process of plants. The measurement of F requires highly accurate and precise radiance measurements in combination with very sophisticated measurement protocols. Additionally, because F has a highly dynamic nature (compared with other vegetation information derived from spectral data) and low signal intensity, several environmental, physiological, and experimental aspects have to be considered during signal acquisition and are key for its reliable interpretation. The European Cooperation in Science and Technology (COST) Action ES1309 OPTIMISE has produced three articles addressing the main challenges in the field of F measurements. In this paper, which is the second of three, we review approaches that are available to measure F from the leaf to the canopy scale using ground-based and airborne platforms. We put specific emphasis on instrumental aspects, measurement setups, protocols, quality checks, and data processing strategies. Furthermore, we review existing techniques that account for atmospheric influences on F retrieval, address spatial scaling effects, and assess quality checks and the metadata and ancillary data required to reliably interpret retrieved F signals. ISSN:2072-4292

Plant physiological link between drought stress and SIF emission  Drought stress is the combined effect of high VPD and low soil water potential  Stomata are closed, reducing sub stomatal CO2 concentrations  Drought stress slows down Calvin cycle but drought stress as such does not reduce light absorption  Fluorescence and NPQ provide alternative electron sinks Research questions 1. How does the SIF signal react to drought stress at different time horizons and stress levels? 2. How is the SIF emission related to plant processes? 3. Can we improve the estimations of transpiration and photosynthesis rates of crops under stress conditions by assimilating SIF observations into plant growth models?

The ability to investigate the Earth’s environment will be greatly improved by hyperspectral satellite data. The FLuorescence EXplorer (FLEX) will be the first hyperspectral mission designed to monitor the photosynthetic activity of the terrestrial vegetation layer by using a completely novel technique measuring the sun-induced chlorophyll fluorescence (SIF) signal that originates from the core of the photosynthetic machinery. In preparation of the upcoming FLEX satellite mission that will be launched in 2022 a large field campaign, namely FLEXSense, was conducted in summer 2018 including representative study sites at several locations in middle and south Europe as well as North America.During the different/various field activities, airborne data was acquired with the hyperspectral airborne imager HyPlant, whichthat consists of two sensor heads. The DUAL module is a line-imaging push-broom sensor, which providinges contiguous spectral information from 370 to 2500 nm. The vegetationchlorophyll fluorescence signal is measured with a separate push-broom sensor, the FLUO module, which produces data at high spectral resolution (0.25 nm) in the spectral region of the two oxygen absorption bands covering a range from 670 to 780 nm. Currently, two different algorithms are used routinely to retrieve red (SIF680) and far-red SIF (SIF760) from HyPlant data. Both methods are based on the oxygen absorption bands., but wWhile the improved Fraunhofer Line Depth (iFLD) method employs a semi-empirical atmospheric correction (i.e., bare-soils), the Spectral Fitting method (SFM) makes useis based onof a physically-based atmospheric modeling (MODTRAN5 code). A common method of testing the reliability of remotely-sensed SIF (in this study airborne maps) is the comparison with “ground truth” data. In many cases, however, ground measurements of SIF are not available or are too work-intensive to be measured at regional level. For that reason we developedwant to present an alternative approach how the quality of airborne SIF maps can be assessed. For this purpose we applyhave developed so-called ’quality criteria’, which should help to find errors and artefacts that have arisen during the SIF retrieval. This method was applied to determine the quality of individual SIF maps derived from HyPlant images acquired during the 2018 FLEXSense campaign. The application of the proposed quality features proved to be a valuable tool for assessing the quality of SIF maps derived from HyPlant airborne data. Therefore, we propose to apply the different criteria even in the case of a with sufficient number of ground reference measurements are available, as because they provide important additional information about the quality of spatial SIF products is provided, especially when comparing the outputs of different retrieval methods.

Lettuce cultures are prone to aphid infestations, but consumer tolerance for aphids in fresh lettuce is close to zero. To avoid losses of harvest due to aphids, lettuce plants are routinely sprayed with pesticides. Broadcast spraying of pesticides are costly, pollute the environment and may lead to pesticide residues in lettuce. Typically, early aphid infestation of lettuce cultures is not uniform, but shows a heterogeneous distribution. An early identification of aphid-infested lettuce plants prior to widespread infestation of whole fields would allow for selective spraying which reduces the use of pesticides. Although aphids have been shown to trigger physiological adjustments in plants, optical detection methods for aphid-infested lettuce plants based on their biotic stress response have yet to be developed. For other crop plants, aphid infestation has been shown to change the optical properties of leaves and canopies. Spectral reflectance measurements of wheat and soybean revealed an increased reflectance in the visible spectrum, but decreased reflectance in the near-infrared (NIR) due to changed chlorophyll content and structural characteristics of leaves. In our first experimental approach, we compared spectral reflectance of field-grown plants with and without aphid infestation. Here, we used aphid-proof enclosures with control plants and plants subjected to manual infestation with the potato aphid Macrosiphum euphorbia, a generalist aphid commonly found on lettuce plants. Three weeks after initial infestation, we counted an average of 130 aphids per plant, which were mainly found on the abaxial side of outer lettuce leaves, while control plants were mainly uninfested. A comparison of leaf-level spectral reflectance of control and aphid-infested plants revealed minor variation in spectral reflectance patterns. We conclude that despite high infestation levels, plants did not exhibit a strong systemic stress response to aphid infestation. This experiment is only the beginning of a row of field and laboratory experiments to find a non-invasive detection technique suitable to indicate the biotic stress response of lettuce plants, and will be followed by experimental approaches using plant- and canopy-level spectral reflectance measurements, chlorophyll fluorescence measurements and thermal imaging.

The process of photosynthesis feeds almost all living organisms on the planet, plays an important role in the global carbon cycle and directly impacts the climate on earth. Remote sensing of sun induced chlorophyll fluorescence (SIF) is applied for non-invasive monitoring of photosynthesis in terrestrial vegetation on various scales. However, the direct understanding of SIF as a proxy for photosynthesis is a field of ongoing research. Tower-based SIF retrieval by field spectrometers for autonomous long-term observation of vegetation aspires to gain further insight into ecosystem-specific seasonal dynamics of photosynthesis activity.

Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost. In this study, the potential of UAV imagery was evaluated to quantify lodging percentage and lodging severity of barley using structure from motion (SfM) techniques. Traditionally, lodging quantification is based on time-consuming manual field observations. Our UAV-based approach makes use of a quantitative threshold to determine lodging percentage in a first step. The derived lodging estimates showed a very high correlation to reference data (R2 = 0.96, root mean square error (RMSE) = 7.66%) when applied to breeding trials, which could also be confirmed under realistic farming conditions. As a second step, an approach was developed that allows the assessment of lodging severity, information that is important to estimate yield impairment, which also takes the intensity of lodging events into account. Both parameters were tested on three ground sample distances. The lowest spatial resolution acquired from the highest flight altitude (100 m) still led to high accuracy, which increases the practicability of the method for large areas. Our new lodging assessment procedure can be used for insurance applications, precision farming, and selecting for genetic lines with greater lodging resistance in breeding research.

Photosynthetic phenotyping requires quick characterization of dynamic traits when measuring large plant numbers in a fluctuating environment. Here, we evaluated the light-induced fluorescence transient (LIFT) method for its capacity to yield rapidly fluorometric parameters from 0.6 m distance. The close approximation of LIFT to conventional chlorophyll fluorescence (ChlF) parameters is shown under controlled conditions in spinach leaves and isolated thylakoids when electron transport was impaired by anoxic conditions or chemical inhibitors. The ChlF rise from minimum fluorescence (Fo) to maximum fluorescence induced by fast repetition rate (Fm−FRR) flashes was dominated by reduction of the primary electron acceptor in photosystem II (QA). The subsequent reoxidation of QA− was quantified using the relaxation of ChlF in 0.65 ms (Fr1) and 120 ms (Fr2) phases. Reoxidation efficiency of QA− (Fr1/Fv, where Fv = Fm−FRR − Fo) decreased when electron transport was impaired, while quantum efficiency of photosystem II (Fv/Fm) showed often no significant effect. ChlF relaxations of the LIFT were similar to an independent other method. Under increasing light intensities, Fr2′/Fq′ (where Fr2′ and Fq′ represent Fr2 and Fv in the light-adapted state, respectively) was hardly affected, whereas the operating efficiency of photosystem II (Fq′/Fm′) decreased due to non-photochemical quenching. Fm−FRR was significantly lower than the ChlF maximum induced by multiple turnover (Fm−MT) flashes. However, the resulting Fv/Fm and Fq′/Fm′ from both flashes were highly correlated. The LIFT method complements Fv/Fm with information about efficiency of electron transport. Measurements in situ and from a distance facilitate application in high-throughput and automated phenotyping., Photosynthesis Research, 140 (2), ISSN:0166-8595, ISSN:1573-5079

International audience; The photosynthetic, optical and morphological characteristics of a chlorophyll-deficient (Chldeficient) “yellow” soybean mutant (MinnGold) were examined in comparison with two green varieties (MN0095 and Eiko). Despite the large difference in Chl content, similar leaf photosynthesis rates were maintained in the Chl-deficient mutant by offsetting the reduced absorption of red photons by a small increase in photochemical efficiency and lower non-photochemical quenching (NPQ). When grown in the field, at full canopy cover, the mutants reflected a significantly larger proportion of incoming shortwave radiation, but the total canopy light absorption was only slightly reduced, most likely due to a deeper penetration of light into the canopy space. As a consequence, canopy-scale grossprimary production and ecosystem respiration were comparable between the Chl-deficient mutant and the green variety. However, total biomass production was lower in the mutant, which indicates that processes other than steady state photosynthesis, caused a reduction in biomass accumulation over time. Analysis of NPQ relaxation and gas exchange in Chl-deficient and green leaves after transitions from high to low light conditions suggested that dynamic photosynthesis might be responsible for the reduced biomass production in the Chl-deficient mutant under field conditions.