Publications

Wallor E., Kersebaum K., Lorenz K., Gebbers R. (2019). Soil state variables in space and time: first steps towards linking proximal soil sensing and process modelling. Precision Agriculture, 20(2), 313-334. doi:10.1007/s11119-018-9617-y

The benefits of process-oriented modelling for management recommendations at the field scale are constrained by high spatial variability of soil properties and lack of dense information on soil types, variability and patterns. Geo-electrical mapping provides dense information about the soil, but sen…

Heil , Schmidhalter (2019). Theory and Guidelines for the Application of the Geophysical Sensor EM38. Sensors, 19(19), 4293. doi:10.3390/s19194293

Characterization of spatial soil variability is key for a better understanding of soils. To arrive at such information geophysical techniques have been used in the last two decades. Due to its easy handling, the geophysical sensor EM38 has widely been used to characterize agricultural areas. The the…

Wallor E. (2018). A comprehensive data set demonstrating the spatial variability of soil properties and crop growth conditions at field scale. Open Data Journal for Agricultural Research, 5(), 1-10. doi:10.18174/odjar.v5i0.15888

A four-year (1999-2002) multivariable data set for one specific agricultural used field located in North Rhine-Westphalia is documented in detailed. The data set focusses on the small-scale heterogeneity of soil properties varying in the spatial and temporal dimension. Initial soil sampling was cond…

Boenecke E., Lueck E., Ruehlmann J., Gruendling R., Franko U. (2018). Determining the within-field yield variability from seasonally changing soil conditions. Precision Agriculture, 19(4), 750-769. doi:10.1007/s11119-017-9556-z

Crop yield variations are strongly influenced by the spatial and temporal availabilities of water and nitrogen in the soil during the crop growth season. To estimate the quantities and distributions of water and nitrogen within a given soil, process-oriented soil models have often been used. These m…

Heil K., Heinemann P., Schmidhalter U. (2018). Modeling the Effects of Soil Variability, Topography, and Management on the Yield of Barley. Frontiers in Environmental Science, 6(), . doi:10.3389/fenvs.2018.00146

A better understanding of processes involved in crop production as well as the use of models as tools for managing agricultural systems are main reasons for the development of growth models. During the last three decades, the complexity of models increased from simple input-output relationships to h…

Adamchuk, V.A., Ji, W., Viscarra Rossel, R., Gebbers, R., Trembley, N. (2018). Proximal soil and plant sensing. Madison, WI, USA: American Society of Agronomy.

Soil and plant sensing can be separated into remote sensing which is discussed in Chapter 8 and proximal sens-ing, where an instrument is placed within 2 m of the target (Viscarra Rossel et al., 2011). These sensors are used for a variety of purposes including quantifying spatial and temporal change…

Wallor E., Kersebaum K., Ventrella D., Bindi M., Cammarano D., Coucheney E., Gaiser T., Garofalo P., Giglio L., Giola P., Hoffmann M., Iocola I., Lana M., Lewan E., Maharjan G., Moriondo M., Mula L., Nendel C., Pohankova E., Roggero P., Trnka M., Trombi G. (2018). The response of process-based agro-ecosystem models to within-field variability in site conditions. Field Crops Research, 228(), 1-19. doi:10.1016/j.fcr.2018.08.021

Process-oriented agro-ecosystem models are increasingly applied to assess crop management options or impacts of climate change on agricultural production, food security and ecosystem services. Thereby, the aggregation of initial soil and climate information is a widely used approach for performing s…

Wallor E., Kersebaum K., Lorenz K., Gebbers R. (2017). Connecting crop models with highly resolved sensor observations to improve site-specific fertilisation. Advances in Animal Biosciences, 8(2), 689-693. doi:10.1017/s2040470017000358

High spatial variability of soil properties restricts the benefits of process-oriented modelling for management recommendations on field scale due to rare information about the soil inventory and its distribution. Geo-electrical mapping provides with a certain spatial pattern, but results are influe…

Käthner J., Ben-Gal A., Gebbers R., Peeters A., Herppich W., Zude-Sasse M. (2017). Evaluating Spatially Resolved Influence of Soil and Tree Water Status on Quality of European Plum Grown in Semi-humid Climate. Frontiers in Plant Science, 8(), . doi:10.3389/fpls.2017.01053

In orchards, the variations of fruit quality and its determinants are crucial for resource effective measures. In the present study, a drip-irrigated plum production (Prunus domestica L. “Tophit plus”/Wavit) located in a semi-humid climate was studied. Analysis of the apparent electrical conductivit…

Heil K., Schmidhalter U. (2017). Improved evaluation of field experiments by accounting for inherent soil variability. European Journal of Agronomy, 89(), 1-15. doi:10.1016/j.eja.2017.05.004

Well-controlled field experiments are used to test agronomic management practices and evaluate the performance of cultivars in highly managed plots at experimental stations, in breeding nurseries or on-farm. However, the performance of crops and therefore the interpretation of experiments is affecte…