Peter Horney’s research while affiliated with Julius Kühn-Institut and other places

Crop yields are increasingly affected by climate change-induced weather extremes in Germany. However, there is still little knowledge of the specific crop-climate relations and respective heat and drought stress-induced yield losses. Therefore, we configure weather indices (WIs) that differ in the timing and intensity of heat and drought stress in wheat (Triticum aestivum L.). We construct these WIs using gridded weather and phenology time series data from 1995 to 2019 and aggregate them with Germany-wide municipality level on-farm wheat yield data. We statistically analyze the WI’s explanatory power and region-specific effect size for wheat yield using linear mixed models. We found the highest explanatory power during the stem elongation and booting phase under moderate drought stress and during the reproductive phase under moderate heat stress. Furthermore, we observed the highest average yield losses due to moderate and extreme heat stress during the reproductive phase. The highest heat and drought stress-induced yield losses were observed in Brandenburg, Saxony-Anhalt, and northern Bavaria, while similar heat and drought stresses cause much lower yield losses in other regions of Germany.

The data descriptor represents a Germany-wide and spatio-temporally consistent 1 x1 km² analysis-ready time series of interpolated days of the year (DOYs). The data set covers 56 entry dates of phenological development stages of 9 main crop types for the period between 1993 and 2021. The derivation of the 1624 records is based on phenological observations provided by German Meteorological Service (DWD) and the PHASE model, which combines the concept of growing degree days (GDD) with a geostatistical interpolation procedure. Each data set is characterized by the global accuracy metrics R² and RMSE.The data are stored as datacubes in the rasdaman Array DBMS which also serves to offer it via APIs based on the open OGC standards.A main application of the resulting data set is the extraction of phenological windows for any available year and user-defined region. This information is relevant for agricultural applications such as weather or biodiversity index derivation, crop-type classification, soil erosion, crop yield modeling or integrated pest management.

The overarching goal of the PAM3D research project is to support farmer in complying with legal regulations, designed to protect terrestrial and aquatic ecosystems from pesticides contamination caused by run-off and erosion from sloping agriculture fields. This will be achieved by new algorithms which allow the automated calculation of elevation parameters (e.g., slope) at each point of the requested field across different spatial resolution. Our project consists of three parts. The first part includes a comparison of the most common digital elevation data from different sources (e.g., Tractor RTK-GNSS, drones, space borne data (SRTM, TanDem-X, AW3D30), and airborne laser data). This analyses aims to explore the accuracy and the suitability of these data sets for the use in the precision agriculture domain. The second part is the development of a 3D-web-service (PAM3D) primarily supposed to provide three-dimensional information of sloping fields in proximity to water bodies. In a third step, we will combine our 3D-service with the successfully tested Pesticide Application Manager (PAM) (Scheiber et al., 2016). PAM automatically uploads field and pesticide specific information on the tractor’s board computer and calculates buffer zones between fields treated with pesticides and adjacent protected biotops or other non-target areas. By now PAM does not consider legal regulations for sloping agriculture terrain. Thus, adding our 3D-service to the PAM system architecture will allow applying plant protection products sustainable and lawfully also in sloping terrain. PAM3D will be designed as a stand alone program and flexible as possible towards changing legal regulations and agriculture machine technology. This flexibility allows further applications as for example the improved control of agricultural machines in sloping fields (e.g., combine harvester). Moreover, our service can be extended to improve run-off models on managed agriculture fields and else where. Thus, the outcomes of our project have the potential to make pesticide application more efficient and to reduce its negative ecological impact. Our project PAM3D is a joint project of scientific institutions and industrial project partner. It is funded by the German Federal Ministry of Food and Agriculture (BMEL) from 2017 to 2020 and promoted by the German Federal Office of Agriculture and Food (BLE).

In response to the implementation of the EU-directive on sustainable pesticide use by Norway, the project SMARTCROP (funded by the Research Council of Norway), was started to address the challenges of developing and providing farmers with the necessary IPM tools. Towards this objective, SYNOPS, a risk indicator developed by the Julius-Kühn Institut, Germany, was adapted for Norway and provided with a graphical user interface such that a farmer or non-expert could perform risk assessments for field-specific pesticide applications. US-EPA PRZM5 and VFSMOD have been incorporated in SYNOPS for a more realistic modelling of the runoff/erosion modules and the functioning of the vegetated filter strip. The Norwegian tool, SYNOPS-WEB, Norway is available in both English and Norwegian. It uses Norwegian land-use, surface water and soil data, plant protection products registered for use in Norway, modified crop data for Norwegian conditions and station-based daily weather data. Risk assessments are carried out for specific field and application scenarios. Another important new feature is the implementation of various mitigation measures such as vegetated filter strips, hedges, tillage/mulch, and cover crops. Risk assessments can be performed for a combination of mitigation measures in order to select the optimal application strategy under specific field conditions. In this presentation, we describe and discuss the mitigation measures implemented in SYNOPS-WEB, Norway and the corresponding adjustments to the model input parameters. We provide example scenarios based on realistic application patterns, without and with mitigation measures. Aquatic and terrestrial risk indices are presented to the user as Exposure Toxicity Ratios (ETR) in the form of colour-coded tables for an easy visual appraisal of the environmental risk under different conditions. In addition the predicted environmental concentrations can be viewed on a daily basis for the selected time period.

SYNOPS a pesticide risk indicator model to assess environmental risk – contribution to and benefits of LOD

In 2015 Norway implemented the EU-Directive on sustainable use of pesticides. The project SMARTCROP addresses the associated challenges of developing and providing the farmers with sufficient IPM tools. One of the objectives was to provide the farmers an easy-to-use online tool to carry out Environmental Risk Assessments (ERA) of their pesticide use under field-specific environmental conditions. We adapted the risk indicator SYNOPS towards this end. SYNOPS has been used in the framework of European projects and in the German NAP since 1996 to evaluate risk to non-target organisms in aquatic and terrestrial ecosystems due to agricultural pesticide use. The runoff/erosion modules in SYNOPS were substituted with the Pesticide Root Zone Model (PRZM5) developed by the US-EPA. Norwegian data on land use, soil, weather and water bodies were incorporated. Users will be presented a list of crops and pesticide products relevant for Norway. All inputs to SYNOPS-core, the modeling component, are facilitated via a user-friendly GUI. The risk assessment is performed for a specific crop and application patterns under actual field conditions. The results are presented as colour-coded risk categories (Exposure Toxicity Ratios, ETR) for acute and chronic risk for surface water, soil, field margins and non-target arthropods. Options for simulating select mitigation measures are also provided. Here we present SYNOPS-WEB, the online counterpart of SYNOPS for use in Norway at field level with realistic application scenarios. We provide a brief description of the models implemented in SYNOPS-WEB, and the technical implementation, followed by a quick walkthrough of its usage.

In the framework of the project SMARTCROP, we adapted the risk indicator SYNOPS to provide the farmers in Norway an easy-to-use online tool to perform Environmental Risk Assessment (ERA) of their pesticide use under field-specific environmental conditions. SYNOPS has been used in the framework of European projects and in the German NAP since 1996 to evaluate risk to non-target organisms in aquatic and terrestrial ecosystems due to agricultural pesticide use. Norwegian Institute of Bioeconomy Research (NIBIO) carries out long-term monitoring of pesticide concentrations in the stream in the Skuterud catchment (Akershus county) near Oslo. Pesticide application data from during the monitoring period is also recorded. The Skuterud catchment covers 449 ha with an agricultural area of 62 % dominated by cereal production under ploughless tillage. It is representative of the main cereal cropping areas in South East Norway. The main soil type is silty clay loam developed on marine deposits and moraine. The climate in the area is characterized by warm summers and unstable winter conditions with annual rainfall of 785 mm and mean annual temperature of 5.3°C (1961-1990). We selected a small sample of pesticides most frequently detected from a select year of monitoring data to evaluate SYNOPS-WEB for Norwegian conditions. Soil data comes from the digital soil map of Norway and weather data from Ås, Agrometeorology Norway. Toxicity values and other parameters for the active ingredients are extracted from the Pesticides Property Database (PPDB). Where the parameters required by PRZM were not available, default values from the EU-FOCUS Jokioinen SW scenarios were used. Pesticides concentrations for each pesticide in surface water calculated by SYNOPS are compared against monitoring data.