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Water deficit is the most severe stress factor in crop production threatening global food security. In this study, we evaluated the genetic variation in photosynthetic traits among 200 wheat cultivars evaluated under drought and rainfed conditions. Significant genotypic, treatments, and their interaction effects were detected for chlorophyll content and chlorophyll fluorescence parameters. Drought stress reduced the effective quantum yield of photosystem II (YII) from the anthesis growth stage on. Leaf chlorophyll content measured at anthesis growth stages was significantly correlated with YII and non-photochemical quenching under drought conditions, suggesting that high throughput chlorophyll content screening can serve as a good indicator of plant drought tolerance status in wheat. Breeding significantly increased the photosynthetic efficiency as newer released genotypes had higher YII and chlorophyll content than the older ones. GWAS identified a stable drought-responsive QTL on chromosome 3A for YII, while under rainfed conditions, it detected another QTL on chromosome 7A for chlorophyll content across both growing seasons. Molecular analysis revealed that the associated alleles of AX-158576783 (515.889 Mbp) on 3A co-segregates with the NADH-ubiquinone oxidoreductase (

Blattläuse sind häufig auftretende Schädlinge in Salatkulturen. Selbst ein geringer Befall wird von Konsumenten nicht toleriert und führt somit zu einen Ausschluss von der Vermarktung. Um Blattläuse im Produkt zu vermeiden, werden Salatfelder bei ersten Anzeichen von Befall mit Pflanzenschutzmitteln behandelt, um jegliche Ausbreitung von Blattläusen zu unterbinden. Der Befall mit Blattläusen ist innerhalb eines Feldes ist in einem frühen Befallsstadium jedoch oft sehr heterogen. Das heißt, dass nur ein kleiner Teil der mit Pflanzenschutzmitteln behandelten Pflanzen tatsächlich von Blattläusen befallen ist. Im Sinne der Präzisionslandwirtschaft könnte eine selektive Behandlung blattlausbefallener Pflanzen mit Pflanzenschutzmitteln den Pflanzenschutzmitteleinsatz reduzieren, ohne zu Ernteeinbußen zu führen. Jedoch gibt es bisher keine Detektionsmethode für blattlausbefallene Salatpflanzen. Für andere Nutzpflanzen wie Weizen, Soja und Hirse konnte bereits gezeigt werden, dass eine systemische Stressreaktion der Pflanzen auf Blattlausbefall durch Messung der spektralen Reflektion von Blättern und Pflanzen auf der Bestandsebene detektiert werden kann. Um zu untersuchen, wie sich Blattlausbefall auf die spektrale Reflektion von Salat auswirkt, haben wir eine Reihe von Experimenten unter Feld-, Freiland-, Gewächshaus und Laborbedingungen durchgeführt, um Unterschiede in der spektralen Reflektion von Kontroll- und blattlausbefallenen Pflanzen zu identifizieren. Hierbei wurden sowohl Punktsensoren zur Erfassung der systemischen Stressreaktion von Einzelpflanzen sowie hyperspektrale Bildgebungsverfahren zur Identifikation lokalisierter Stressreaktionen eingesetzt. Leider ließen sich keine charakteristischen Veränderungen der spektralen Reflektion unter Blattlausbefall identifizieren, anhand derer Blattlausbefall detektierbar wäre. Die Detektion der anscheinend subtilen biotischen Stressreaktion von Salatpflanzen auf Blattlausbefall mittels Punktsensoren wird durch die Kopfbildung der Pflanzen sowie weitere unter Feldbedingungen auftretende Einflussfaktoren wie Pflanzenalter, Sorte und abiotische Bedingungen erschwert. Als Fazit bleibt daher zu sagen, dass die frühzeitige Detektion von Blattlausbefall in Salat, d.h. der Befall durch einzelne Blattläuse, nicht anhand von Messungen der spektralen Reflektion detektiert werden kann. Der Einsatz von Messungen der spektralen Reflektanz zur Detektion von biotischem Stress auf Blattlausbefall ist daher vielversprechender bei Pflanzen mit offenerer Morphologie sowie einer höheren Schadschwelle für Blattlausbefall., Berichte über Landwirtschaft - Zeitschrift für Agrarpolitik und Landwirtschaft, Aktuelle Beiträge

With the upcoming L‐band Synthetic Aperture Radar (SAR) satellite mission Radar Ob-serving System for Europe L‐band SAR (ROSE‐L) and its integration into existing C‐band satellite missions such as Sentinel‐1, multi‐frequency SAR observations with high temporal and spatial resolution will become available. The SARSense campaign was conducted between June and August 2019 to investigate the potential for estimating soil and plant parameters at the agricultural test site in Selhausen (Germany). It included C‐ and L‐band air‐ and space‐borne observations accompanied by extensive in situ soil and plant sampling as well as unmanned aerial system (UAS) based multi-spectral and thermal infrared measurements. In this regard, we introduce a new publicly available SAR data set and present the first analysis of C‐ and L‐band co‐ and cross‐polarized backscattering signals regarding their sensitivity to soil and plant parameters. Results indicate that a multi‐fre-quency approach is relevant to disentangle soil and plant contributions to the SAR signal and to identify specific scattering mechanisms associated with the characteristics of different crop type, especially for root crops and cereals.

Additional file 1: Figure S1. Calibration curve of the miniature air flow transmitters. The straight line represents the overall regression (all sensors). Figure S2. Changes in ΔCO2 at different air flux levels when scrubbing the air with soda lime. The data show all ramps (i.e. different pump speeds) normalized from 0 to 1 and averaged every 20 seconds.

With the upcoming L-band Synthetic Aperture Radar (SAR) satellite mission Radar Observing System for Europe at L-band (ROSE-L) and its combination with existing C-band satellite missions such as Sentinel-1, multi-frequency SAR observations with high temporal and spatial resolution will become available. To investigate the potential for estimating soil and plant parameters, the SARSense campaign was conducted between June and August 2019 at the agricultural test site Selhausen in Germany. In this regard, we introduce a new publicly available, extensive SAR dataset and present a first analysis of C- and L-band co- and cross-polarized backscattering signals regarding their sensitivity to soil and plant parameters. The analysis includes C- and L-band airborne recordings as well as Senitnel-1 and ALOS-2 acquisitions, accompanied by in-situ soil moisture measurements and plant samplings. In addition, soil moisture was measured using cosmic-ray neutron sensing as well as unmanned aerial system (UAS) based multispectral and temperature measurements were taken during the campaign period. First analysis of the dataset revealed, that due to misalignments of corner reflectors during the SAR acquisition, temporal consistency of airborne SAR data is not given. In this regard, a scene-based, spatial analysis of backscatter behaviour from airborne SAR data was conducted, while the spaceborne SAR data enabled the analysis of temporal changes in backscatter behaviour. Focusing on root crops with radial canopy structure (sugar beet and potato) and cereal crops with elongated canopy structure (wheat, barley), the lowest correlations can be observed between backscattering signal and soil moisture, with R² values ranging below 0.35 at C-band and below 0.36 at L-band. Higher correlations can be observed focusing on vegetation water content, with R² values ranging between 0.12 and 0.64 at C-band and 0.06 and 0.64 at L-band. Regarding plant height, at C-band higher correlations with R² up to 0.55 can be seen compared to R² up to 0.36 at L-band. Looking at the individual agricultural corps in more detail, in almost all cases, the backscatter signals of C- and L-band contain a different amount of information about the soil and plant parameters, indicating that a multi-frequency approach is envisaged to disentangle soil and plant contributions to the signal and to identify specific scattering mechanisms related to the crop type, especially related to the different characteristics of root crops and cereals.

Vegetation responds at varying temporal scales to changing soil water availability. These process dynamics complicate assessments of plant-water relations but also offer various access points to advance understanding of vegetation responses to environmental change. Remote sensing (RS) provides large capacity to quantify sensitive and robust information of vegetation responses and underlying abiotic change driver across observational scales. Retrieved RS based vegetation parameters are often sensitive to various environmental and plant specific factors in addition to the targeted plant response. Further, individual plant responses to water limitation act at different temporal and spatial scales, while RS sampling schemes are often not optimized to assess these dynamics. The combination of these aspects complicates the interpretation of RS parameter when assessing plant-water relations. We consequently aim to advance insight on the sensitivity of physiological, biochemical and structural RS parameter for plant adaptation in response to emerging soil water limitation. We made a field experiment in maize in Tuscany (Central Italy), while irrigation was stopped in some areas of the drip-irrigated field. Within a period of two weeks, we measured the hydraulic and physiological state of maize plants in situ and complemented these detailed measurements with extensive airborne observations (e.g. sun-induced chlorophyll fluorescence (SIF), vegetation indices sensitive for photosynthesis, pigment and water content, land surface temperature). We observe a double response of far-red SIF with a short-term increase after manifestation of soil water limitation and a decrease afterwards. We identify different response times of RS parameter representing different plant adaptation mechanisms ranging from short term responses (e.g. stomatal conductance, photosynthesis) to medium term changes (e.g. pigment decomposition, changing leaf water content). Our study demonstrates complementarity of common and new RS parameter to mechanistically assess the complex cascade of functional, biochemical and structural plant responses to evolving soil water limitation.

Energy is required in all agricultural activities. Diagramming material flows needed by crop production systems supports the proper analysis of energy flows interactions within a system&rsquo, s boundaries. The latter complemented with an economic analysis gives a clear view of how beneficial a new practice within a crop cycle is&mdash, in this case, the variable slope (VS) land leveling (LL) operation. VS is a global navigation satellite system (GNSS, with real time kinematics&mdash, RTK&mdash, accuracy) LL technique used to create a smooth continuous surface with a constant slope, by cutting and filling topsoil layers only in those points presenting &ldquo, anomalies&rdquo, of micro-relief which make the movement of water difficult. This operation is important for paddy production since: (i) it enables to crop during dry seasons by harnessing the water of rivers and wells, and (ii) improves the production during rainy seasons, by allowing the farmer to manage the drainage timely and homogeneously. The present study aims to analyze, from the energy perspective, the effects of the VS leveling implementation in a paddy field (located in the Costa Rican Pacific), throughout input (labor, gas oil, etc.) and output (yield and price) data of five consecutive years (2011&ndash, 2015). A material flow diagram was created representing two scenarios: before and after leveling the land. The materials were converted into energy (MJ ha&minus, 1) data, used for the estimation of EROI (energy return on investment), EP (energy productivity) and EB (energy balance) indices, while looking for a clearer understanding of the LL impact on the use of energy within the agroecosystem. Moreover, in order to complement the energy perspective, an economic point of view was considered as well through a profitability analysis where the total gain obtained over the years with LL was compared with that obtained without LL. Results showed that the increase in energy consumed by incorporating VS leveling is compensated by the gradual increase of energy embodied in yield, increasing energy balance (EB) from 26,192 MJ ha&minus, 1 up to 91,166 MJ ha&minus, 1. Similarly, EROI and EP were duplicated with LL. Economic total gain after incorporating the VS increased from less than 500 USD ha&minus, 1 up to 1800 USD ha&minus, 1 in the third year after leveling. Yield is more affected under adverse weather conditions with irregular water supply, either limited or excessive, and effects are less pronounced when the yield limiting factor is associated with biotic stress unrelated to irrigation and drainage facts. An environmental positive impact should also be noted, since VS allowed the production benefits of having highly-efficient irrigation and drainage systems, while avoiding major damage to topsoil layers.

Chlorophyll fluorescence (ChlF) information offers a deep insight into the plant physiological status by reason of the close relationship it has with the photosynthetic activity. The unmanned aerial systems (UAS)-based assessment of solar induced ChlF (SIF) using non-imaging spectrometers and radiance-based retrieval methods, has the potential to provide spatio-temporal photosynthetic performance information at field scale. The objective of this manuscript is to report the main advances in the development of UAS-based methods for SIF retrieval with non-imaging spectrometers through the latest scientific contributions, some of which are being developed within the frame of the Training on Remote Sensing for Ecosystem Modelling (TRuStEE) program. Investigations from the Universities of Edinburgh (School of Geosciences) and Tasmania (School of Technology, Environments and Design) are first presented, both sharing the principle of the spectroradiometer optical path bifurcation throughout, the so called 'Piccolo-Doppio' and 'AirSIF' systems, respectively. Furthermore, JB Hyperspectral Devices' ongoing investigations towards the closest possible characterization of the atmospheric interference suffered by orbital platforms are outlined. The latest approach focuses on the observation of one single ground point across a multiple-kilometer atmosphere vertical column using the high altitude UAS named as AirFloX, mounted on a specifically designed and manufactured fixed wing platform: 'FloXPlane'. We present technical details and preliminary results obtained from each instrument, a summary of their main characteristics, and finally the remaining challenges and open research questions are addressed. On the basis of the presented findings, the consensus is that SIF can be retrieved from low altitude spectroscopy. However, the UAS-based methods for SIF retrieval still present uncertainties associated with the current sensor characteristics and the spatio-temporal mismatching between aerial and ground measurements, which complicate robust validations. Complementary studies regarding the standardization of calibration methods and the characterization of spectroradiometers and data processing workflows are also required. Moreover, other open research questions such as those related to the implementation of atmospheric correction, bidirectional reflectance distribution function (BRDF) correction, and accurate surface elevation models remain to be addressed.

Land surface temperature (LST) is a fundamental parameter within the system of the Earth’s surface and atmosphere, which can be used to describe the inherent physical processes of energy and water exchange. The need for LST has been increasingly recognised in agriculture, as it affects the growth phases of crops and crop yields. However, challenges in overcoming the large discrepancies between the retrieved LST and ground truth data still exist. Precise LST measurement depends mainly on accurately deriving the surface emissivity, which is very dynamic due to changing states of land cover and plant development. In this study, we present an LST retrieval algorithm for the combined use of multispectral optical and thermal UAV images, which has been optimised for operational applications in agriculture to map the heterogeneous and diverse agricultural crop systems of a research campus in Germany (April 2018). We constrain the emissivity using certain NDVI thresholds to distinguish different land surface types. The algorithm includes atmospheric corrections and environmental thermal emissions to minimise the uncertainties. In the analysis, we emphasise that the omission of crucial meteorological parameters and inaccurately determined emissivities can lead to a considerably underestimated LST; however, if the emissivity is underestimated, the LST can be overestimated. The retrieved LST is validated by reference temperatures from nearby ponds and weather stations. The validation of the thermal measurements indicates a mean absolute error of about 0.5 K. The novelty of the dual sensor system is that it simultaneously captures highly spatially resolved optical and thermal images, in order to construct the precise LST ortho-mosaics required to monitor plant diseases and drought stress and validate airborne and satellite data.

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.