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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.

Blattläuse sind die Hauptschädlinge in Salatkulturen, da selbst ein geringer Befall von Konsumenten nicht toleriert und somit einen Ausschluss von der Vermarktung bedeutet. Aus diesem Grund werden Salatfelder bei hohem Befallsdruck regelmäßig mit Pestiziden behandelt, um jegliche Ausbreitung von Blattläusen zu unterbinden. In einem frühen Befallsstadium ist der Blattlausbefall innerhalb eines Feldes jedoch oft sehr heterogen, und nur ein kleiner Teil der mit Pestiziden behandelten Pflanzen ist tatsächlich von Blattläusen befallen. Ein selektiver Pestizideinsatz von befallenen Pflanzen im Sinne der Präzisionslandwirtschaft würde den Pestizideinsatz reduzieren, ohne dass es zu Ernteeinbußen kommt. Jedoch gibt es bisher keine Detektionsmethode für blattlausbefallene Salatpflanzen. Für andere Nutzpflanzen wie Weizen und Soja konnte bereits gezeigt werden, dass Blattlausbefall systemische Stressreaktionen in Pflanzen hervorrufen kann, die zu Veränderungen der optischen Eigenschaften von Blättern, Pflanzen und auf der Bestandseben führen. Messungen der spektralen Reflektion von Weizen haben gezeigt, dass Blattlausbefall zu einer erhöhten Reflektion im sichtbaren Wellenlängenbereich und einer erniedrigten Reflektion im nahinfraroten Wellenlängenbereich führt, die sich auf einen erniedrigten Chlorophyllgehalt und strukturelle Veränderungen der Blätter zurückführen lassen. Um die Auswirkungen von Blattlausbefall auf die spektrale Reflektion von Salat zu untersuchen, haben wir im Freilandversuch gezielt Salatpflanzen dem Blattlausbefall ausgesetzt. Hierzu wurden in drei von sechs blattlaussicheren Käfigen mit je fünf Salatpflanzen (Mini-Romana, Lactuca sativa ‚Thimble‘) grünstreifige Kartoffelläuse (Macrosiphum euphorbiae) ausgesetzt. Über einen Zeitraum von drei Wochen wurde der Blattlausbefall regelmäßig überprüft, und zweimal pro Woche die spektrale Reflektion von Blättern und Einzelpflanzen gemessen. Zusätzlich planen wir Experimente unter Laborbedingungen, in denen Blätter blattlausbefallener Salatpflanzen mittels hochauflösender hyperspektraler Bildgebungsverfahren untersucht werden. So wollen wir spektrale Charakteristika identifizieren, die Blattlausbefall anzeigen. Unsere Ergebnisse werden anschließend in die Entwicklung eines Prototyps zum selektiven Pestizideinsatz in Salatkulturen eingehen. Wir möchten damit dazu zu einer Etablierung der Präzisionslandwirtschaft im Pestizideinsatz beitragen, um die damit verbundenen Kosten und Umweltbelastungen zu minimieren.

Non-invasive geophysical fixed-boom multi-coil electromagnetic induction (EMI) instruments return apparent electrical conductivity (ECa) values that depend on subsurface soil properties. Using different transmitter-receiver coil separations and orientations, ECa values of different depths of investigation (DOI) are obtained. After calibration, the quantitative EMI data are inverted to obtain electrical conductivity (σ) changes over depth assuming a layered subsurface model. Airborne hyperspectral measurements are used to estimate plant performance and growth, however, the top- and subsoil structural changes influencing plant performance and growth is often ignored. Here, we have investigated the origin of observed patterns in sun-induced fluorescence data by performing quantitative large-scale EMI measurements and quantitative inversions. The fixed-boom multi-coil EMI ECa data of nine coil configurations indicated spatial patterns due to buried paleo-river channels. After inversion, the obtained layered quasi-3D electrical conductivity model showed a relatively homogeneous ploughing layer and the presence of the paleo-river channels at > 1 m depth. Contrary to often used assumptions, σ of the ploughing layer only showed minor correlation to fluorescence data (r ~ 0.35), while the subsoil returned a significant correlation (r ~ 0.65) indicating a substantial influence of the subsoil on the plant performance, especially during dry periods which is probably due to differences in soil water holding capacity. For the first time, we have related soil-depth specific 3D subsurface information obtained by quantitative multi-coil EMI data inversions with sun-induced fluorescence data and have shown that above surface plant performance is caused by subsoil structural changes. Consequently, the subsurface structures should be incorporated in plant modeling as well as in terrestrial system modeling tools to improve the understanding of soil-vegetation-atmosphere exchange processes.

Die große Salatblattlaus, Nasonovia ribisnigri, ist einer der Hauptschädlinge in Salatkulturen. Da das Vorkommen von Insekten in frischem Salat von Konsumenten nicht toleriert wird, bedeutet auch ein geringer Befall einen Ausschuss von der Vermarktung. Daher werden Salatfelder bei hohem Befallsdruck regelmäßig mit Pflanzenschutzmitteln behandelt. Da der Befall mit N. ribisnigri innerhalb eines Feldes in einem frühen Befallsstadium oft sehr heterogen ist, werden so auch unbefallene Pflanzen behandelt. Im Rahmen der sich entwickelnden Präzisionslandwirtschaft könnte der Einsatz von Sensoren zur Detektion von befallen Pflanzen eine selektive Behandlung befallener Pflanzen erlauben. Dadurch würde der Einsatz von Pflanzenschutzmitteln reduziert, ohne dass es zu Ernteeinbußen kommt. Studien mit Weizen, Hirse und Soja haben gezeigt, dass die systemische Stressreaktion der Pflanzen auf Blattlausbefall anhand spektraler Reflektanzmessungen detektiert werden kann (Alves et al., 2015, Elliott et al., 2015, Mirik et al., 2012). Bei diesen Messungen können Veränderungen der optischen Eigenschaften von Pflanzen mit relativ kostengünstigen Sensoren auf Ebene von Blättern, Einzelpflanzen und Beständen gemessen werden. In einer Reihe von Gewächshaus- und Freilandexperimenten haben wir Veränderungen der spektralen Reflektanz von Salatpflanzen, die mit Nasonovia ribisnigri befallen sind, untersucht. Hierbei lag der Fokus auf der Identifizierung charakteristischer Veränderungen der spektralen Reflektanz, die als Indikator für Blattlausbefall genutzt werden können. Zudem untersuchen wir, ab welcher Befallsdauer und –intensität eine zuverlässige Detektion möglich ist, da nur eine frühe Detektion von Blattlausbefall einen gezielten Einsatz von Pflanzenschutzmitteln ermöglicht. In Zusammenarbeit mit einem Salatproduzenten konnten wir unter Produktionsbedingungen im Feld messen. Zudem haben wir im Freilandversuch gezielt Salatpflanzen dem Blattlausbefall ausgesetzt, um temporale Veränderungen messen zu können. Zusätzlich wurden Einzelpflanzen unter Laborbedingungen mittels hochauflösender hyperspektraler Bildgebungsverfahren untersucht, um lokale und systemische Reaktionen der Pflanzen zu untersuchen. Durch die Etablierung eines sensorgestützten Pflanzenschutzmitteleinsatzes können langfristig die mit dem Pestizideinsatz verbundenen Kosten und Umweltbelastungen minimiert werden.

Sun-induced chlorophyll fluorescence (F) is a novel remote sensing parameter providing an estimate of actual photosynthetic rates. A combination of this new observable and Monteith’s light use efficiency (LUE) concept was suggested for an advanced modeling of gross primary productivity (GPP). In this demonstration study, we evaluate the potential of both F and the more commonly used photochemical reflectance index (PRI) to approximate the LUE term in Monteith’s equation and eventually improve the forward modeling of GPP diurnals. Both F and the PRI were derived from ground and airborne based spectrometer measurements over two different crops. We demonstrate that approximating dynamic changes of LUE using F and PRI significantly improves the forward modeling of GPP diurnals. Especially in sugar beet, a changing photosynthetic efficiency during the day was traceable with F and incorporating F in the forward modeling significantly improved the estimation of GPP. Airborne data were projected to produce F and PRI maps for winter wheat and sugar beet fields over the course of one day. We detected a significant variability of both, F and the PRI within one field and particularly between fields. The variability of F and PRI was higher in sugar beet, which also showed a physiological down-regulation of leaf photosynthesis. Our results underline the potential of F to serve as a superior indicator for the actual efficiency of the photosynthetic machinery, which is linked to physiological responses of vegetation.

Spatial Fluorescence patterns in a heterogeneous agriculture landscapeMaria Matveeva1, Patrick Rademske1, Alexander Damm2, Cosimo Brogi3, Guido Waldhoff4, and Uwe Rascher11 Institute of Bio- and Geosciences, IBG-2: Plant Sciences, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425 Jülich, Germany2 Remote Sensing Laboratories, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland3 Institute of Bio- and Geosciences, IBG-3: Agrosphere, Forschungszentrum Jülich GmbH, Leo-Brandt-Str., 52425 Jülich, Germany4 Institute of Geography, University of Cologne, Albertus-Magnus-Platz , D-50923 Cologne, GermanySun induced fluorescence (F) is a remote sensing signal that is emitted from the core of the photosynthetic machinery. The fluorescence signal has the potential to quantify the actual rate of photosynthesis and is closely related to vegetation stress and reflects functional limitations of photosynthetic carbon gain. F is a rather weak signal, but can be measured in the solar and atmospheric absorption lines using high performance spectrometers.The increased interest of the scientific community to the remote sensing of sun-induced chlorophyll fluorescence (F) leads to a large number of fruitful and interesting experiments on the field scale. On the other side, satellite data became available, from which fluorescence on the global scale can be derived. However, it is still an open question, how representative the results of field experiments are for a larger (regional) scale. Fluorescence of the same crop strongly varies depending on the season, soil moisture, nutrient availability, etc.To evaluate the heterogeneity of fluorescence (F) and vegetation indices (VI) within and between fields and for a better understanding of the link between F and biophysical parameters, the agriculture area in Nordrhein-Westfalen (Germany) was chosen for measurements. We have collected data using the high performance imaging spectrometer HyPlant, which is a dedicated fluorescence spectrometer and allows measuring radiance in the wavelength range between 400 nm and 2500 nm, and between 670 nm and 780 nm with a high spectral resolution of 0.26 nm allowing the measurement of both fluorescence peaks. Data were recorded with a spatial resolution of 3 meter per pixel for the whole region (ca. 14×14 km) and with 1 m resolution for the Selhausen area (ca. 1.5×5 km). That area was better characterized in terms of land use classification, soil moisture, geophysical measurements, leaf area index (LAI), defined soil properties and the presence of an Eddy Covariance tower.In this work, we investigate the within and between species variability of red, far-red, integrated fluorescence and vegetation indices, from which such biophysical parameters as LAI, chlorophyll content, fractional cover etc. can be calculated. Considering the land use classification it is possible to choose the fields with the same crop type in the whole investigated area and find a distribution of F emission of main regional crops such as winter wheat, winter barley, sugar beet and corn.

The effect that the canopy structure and the viewing geometry have on the intensity and the spatial distribution of passively measured sun-induced chlorophyll fluorescence at canopy scale is still not well understood. These uncertainties constrain the potential use of fluorescence to quantify photosynthesis at this level. Using a novel technique, we evaluated the diurnal changes in the spatial distribution of sun-induced fluorescence at 760 nm (F760) within the canopy as a consequence of the spatial disposition of the leaves and the viewing angle of the sensor. High resolution spectral and stereo images of a full sugar beet canopy were recorded simultaneously in the field to estimate maps of F760 and the surface angle distribution, respectively. A dedicated algorithm was used to align both maps in the post-processing and its accuracy was evaluated using a sensitivity test. The relative angle between sun and the leaf surfaces primarily determined the amount of incident Photosynthetic Active Radiation (PAR), which in turn was reflected in different values of F760, with the highest values occurring in leaf surfaces that are perpendicularly oriented to the sun. The viewing angle of the sensor also had an impact in the intensity of the recorded F760. Higher viewing angles generally resulted in higher values of F760. We attribute these changes to a direct effect of the vegetation directional reflectance response on fluorescence retrieval. Consequently, at leaf surface level, the spatio-temporal variations of F760 were mainly explained by the sun–leaf–sensor geometry rather than directionality of the fluorescence emission. At canopy scale, the diurnal patterns of F760 observed on the top-of-canopy were attributed to the complex interplay between the light penetration into the canopy as a function of the display of the various leaves and the fluorescence emission of each leaf which is modulated by the exposure of the individual leaf patch to the incoming light and the functional status of photosynthesis. We expect that forward modeling can help derive analytical simplified skeleton assumptions to scale canopy measurements to the leaf functional properties.

Studies on the function of root traits and the genetic variation in these traits are often conducted under controlled conditions using individual potted plants. Little is known about root growth under field conditions and how root traits are affected by agronomic practices in particular sowing density. We hypothesized that with increasing sowing density, root length density (root length per soil volume, cm cm-3) increases in the topsoil as well as specific root length (root length per root dry weight, cm g-1) due to greater investment in fine roots. Therefore, we studied two spring barley cultivars at ten different sowing densities (24–340 seeds m-2) in 2 consecutive years in a clay loam field in Germany and established sowing density dose-response curves for several root and shoot traits. We took soil cores for measuring roots up to a depth of 60 cm in and between plant rows (inter-row distance 21 cm). Root length density increased with increasing sowing density and was greatest in the plant row in the topsoil (0–10 cm). Greater sowing density increased specific root length partly through greater production of fine roots in the topsoil. Rooting depth (D50) of the major root axes (root diameter class 0.4–1.0 mm) was not affected. Root mass fraction decreased, while stem mass fraction increased with sowing density and over time. Leaf mass fraction was constant over sowing density but greater leaf area was realized through increased specific leaf area. Considering fertilization, we assume that light competition caused plants to grow more shoot mass at the cost of investment into roots, which is partly compensated by increased specific root length and shallow rooting. Increased biomass per area with greater densities suggest that density increases the efficiency of the cropping system, however, declines in harvest index at densities over 230 plants m-2 suggest that this efficiency did not translate into greater yield. We conclude that plant density is a modifier of root architecture and that root traits and their utility in breeding for greater productivity have to be understood in the context of high sowing densities.

Wheat varieties with greater yields arise today mainly by selecting for harvested grain yield in field environments. This approach combines multiple favourable alleles. Gains are slow because the contributions of alleles to yield are largely unknown. The contrasting “pre-breeding” approach aims to introduce a single major enhancing trait (other than yield) into a variety. This approach can take ~20 years from idea to field, and there are few successful examples in wheat (Hall and Richards 2013). Phenotyping may bridge this gap between yield based and single-trait based breeding because multiple traits (alleles) can be measured on one line. Examples are presented where phenotyping technologies quantified shoot and root traits non-destructively on wheats of different genetic and pedoclimatic origins. For early growth traits in controlled conditions: root architecture differed in response to soil water gradients, but shoots did not (Nagel et al., 2015); shoot growth declined in response to reduced N supply, but root growth did not (Gioia et al 2015); and leaf area and water use varied differentially in response to drought (Nakhforoosh et al 2016). Field phenotyping during grain filling has shown that shoot and root development vary independently depending on plant stage, genotype and environment (Severini et al. in prep), and spectral properties of wheat heads and canopy are dynamic, requiring time-lapse systems (Ahrends et al., 2014). Hence phenotyping technologies quantify the high degree of variation at important establishment and grain development stages in wheat, and may increase certainty of incorporating multiple alleles of known effect within breeding.

In this study we present a hyperspectral flying goniometer system, based on a rotary-wing unmanned aerial vehicle (UAV) equipped with a spectrometer mounted on an active gimbal. We show that this approach may be used to collect multiangular hyperspectral data over vegetated environments. The pointing and positioning accuracy are assessed using structure from motion and vary from σ = 1° to 8° in pointing and σ = 0.7 to 0.8 m in positioning. We use a wheat dataset to investigate the influence of angular effects on the NDVI, TCARI and REIP vegetation indices. Angular effects caused significant variations on the indices: NDVI = 0.83–0.95; TCARI = 0.04–0.116; REIP = 729–735 nm. Our analysis highlights the necessity to consider angular effects in optical sensors when observing vegetation. We compare the measurements of the UAV goniometer to the angular modules of the SCOPE radiative transfer model. Model and measurements are in high accordance (r2 = 0.88) in the infrared region at angles close to nadir; in contrast the comparison show discrepancies at low tilt angles (r2 = 0.25). This study demonstrates that the UAV goniometer is a promising approach for the fast and flexible assessment of angular effects., Remote Sensing, 7 (1), ISSN:2072-4292

Background Combined assessment of leaf reflectance and transmittance is currently limited to spot (point) measurements. This study introduces a tailor-made hyperspectral absorption-reflectance-transmittance imaging (HyperART) system, yielding a non-invasive determination of both reflectance and transmittance of the whole leaf. We addressed its applicability for analysing plant traits, i.e. assessing Cercospora beticola disease severity or leaf chlorophyll content. To test the accuracy of the obtained data, these were compared with reflectance and transmittance measurements of selected leaves acquired by the point spectroradiometer ASD FieldSpec, equipped with the FluoWat device. Results The working principle of the HyperART system relies on the upward redirection of transmitted and reflected light (range of 400 to 2500 nm) of a plant sample towards two line scanners. By using both the reflectance and transmittance image, an image of leaf absorption can be calculated. The comparison with the dynamically high-resolution ASD FieldSpec data showed good correlation, underlying the accuracy of the HyperART system. Our experiments showed that variation in both leaf chlorophyll content of four different crop species, due to different fertilization regimes during growth, and fungal symptoms on sugar beet leaves could be accurately estimated and monitored. The use of leaf reflectance and transmittance, as well as their sum (by which the non-absorbed radiation is calculated) obtained by the HyperART system gave considerably improved results in classification of Cercospora leaf spot disease and determination of chlorophyll content. Conclusions The HyperART system offers the possibility for non-invasive and accurate mapping of leaf transmittance and absorption, significantly expanding the applicability of reflectance, based on mapping spectroscopy, in plant sciences. Therefore, the HyperART system may be readily employed for non-invasive determination of the spatio-temporal dynamics of various plant properties. Electronic supplementary material The online version of this article (doi:10.1186/s13007-015-0043-0) contains supplementary material, which is available to authorized users.

Priority effects occur when species that arrive first in a habitat significantly affect the establishment, growth, or reproduction of species arriving later and thus affect functioning of communities. However, we know little about how the timing of arrival of functionally different species may alter structure and function during assembly. Even less is known about how plant density might interact with initial assembly. In a greenhouse experiment legumes, grasses or forbs were sown a number of weeks before the other two plant functional types were sown (PFT) in combination with a sowing density treatment. Legumes, grasses or non-legume forbs were sown first at three different density levels followed by sowing of the remaining PFTs after three or six-weeks. We found that the order of arrival of different plant functional types had a much stronger influence on aboveground productivity than sowing density or interval between the sowing events. The sowing of legumes before the other PFTs produced the highest aboveground biomass. The larger sowing interval led to higher asymmetric competition, with highest dominance of the PFT sown first. It seems that legumes were better able to get a head-start and be productive before the later groups arrived, but that their traits allowed for better subsequent establishment of non-legume PFTs. Our study indicates that the manipulation of the order of arrival can create priority effects which favour functional groups of plants differently and thus induce different assembly routes and affect community composition and functioning.