Plant-specific herbicide application requires sensor systems for plant recognition and differentiation. A literature review reveals a lack of sensor systems capable of recognizing small weeds in early stages of development (in the two- or four-leaf stage) and crop plants, of making spraying decisions in real time and, in addition, are that are inexpensive and ready for practical use in sprayers. The system described in this work is based on free cascadable and programmable true-color sensors for real-time recognition and identification of individual weed and crop plants. The application of this type of sensor is suitable for municipal areas and farmland with and without crops to perform the site-specific application of herbicides. Initially, databases with reflection properties of plants, natural and artificial backgrounds were created. Crop and weed plants should be recognized by the use of mathematical algorithms and decision models based on these data. They include the characteristic color spectrum, as well as the reflectance characteristics of unvegetated areas and areas with organic material. The CIE-Lab color-space was chosen for color matching because it contains information not only about coloration (a- and b-channel), but also about luminance (L-channel), thus increasing accuracy. Four different decision making algorithms based on different parameters are explained: (i) color similarity (ΔE); (ii) color similarity split in ΔL, Δa and Δb; (iii) a virtual channel ‘d’ and (iv) statistical distribution of the differences of reflection backgrounds and plants. Afterwards, the detection success of the recognition system is described. Furthermore, the minimum weed/plant coverage of the measuring spot was calculated by a mathematical model. Plants with a size of 1–5% of the spot can be recognized, and weeds in the two-leaf stage can be identified with a measuring spot size of 5 cm. By choosing a decision model previously, the detection quality can be increased. Depending on the characteristics of the background, different models are suitable. Finally, the results of field trials on municipal areas (with models of plants), winter wheat fields (with artificial plants) and grassland (with dock) are shown. In each experimental variant, objects and weeds could be recognized.

This study examined the effect of stripwise subsoiling and subsoiling combined with the incorporation of organic material on crop development in a two-year field trial with typical weather in the first year and hot, dry weather in the second. Subsoiling and its combination with incorporated organic materials had strong effects on plant development and crop yield of spring barley (2017) and winter wheat (2018). The subsoil was loosened in 30 cm wide furrows down to a depth of up to 60 cm with a tine (DL) or a spader machine (SM) and was compared with the same methods of subsoil loosening combined with the incorporation of compost from biological household wastes (DLB and SMB). Furthermore, green waste compost (SMG), chopped straw (SMCS) and sawdust (SMS) were incorporated with the spader machine only. DL successfully reduced penetration resistance underneath the furrow and enhanced root growth underneath and near the furrow over the whole experimental period. Grain protein content above the furrow was enhanced compared with the untreated control (C) in the first year, but grain yield did not increase. DLB also reduced penetration resistance and increased root growth, but furthermore caused considerable increases in soil mineral nitrogen underneath the furrow throughout the vegetation period. Consequently, both yield and grain protein content above the furrow were tendentially increased as compared with the C. In SMB, grain yield increased even more than in DLB, compared to C, in 2017 (84% for SMB vs. 19% for DLB) and nearly equally in 2018 (65.4% vs. 65.2%) while all other treatments tendentially decreased grain yield above the furrow as compared with C. The results indicate that subsoiling with the introduction of organic material can reduce mechanical impedance and increase soil nitrogen and thereby ensure stable yields during dry periods, which become more frequent under climate change.

An increasing challenge for agriculture in times of climate change is to sustainably ensure or increase the yield capacity of crop production. Low-yielding sites are particularly at risk in this respect. One strategy to counteract is to promote the use of the subsoil. This article describes the technical procedure and development of an implement for stripe-wise subsoil melioration with application of compost in a layer of 30–60 cm. These stripes are each 30 cm wide and 70 cm apart. A technology has been developed for process, which allows the described procedure to be used over a large area. The melioration is carried out in one pass by an implement in an arrangement of 3 rows resulting in a working width of 3 m. A hopper on top of the implements frame includes an embedded hydraulic system to feed compost into the injection coulter. Results from 4-year field trials with standard crop rotations verify yield increases of up to 20% still 5 years after melioration. An overview of these trials and results will also be presented.

Soil is the habitat for soil organisms and associated soil physical and chemical processes. The subsoil is a large reserve of water and nutrients. Soil and subsoil are thus significantly involved in the yield capacity of a site and its resilience in the case of unfavorable weather conditions. Subsoil can also retain water in drought phases and stores carbon. In times of climate change and scarcity of resources, many scientific activities involve subsoil and require sensors to assess subsoil conditions and properties. An electrically driven penetrometer with an integrated soil water content sensor could be an appropriate tool for such applications; however, such a subsoil measurement tool does not exist. One major reason for this is that, when penetrating compacted subsoil, high penetration forces (including friction) act on the penetrating thin rod (diameter 1 cm). The development of a tractor-mounted subsoil penetrometer for depths up to 2 m is described in this study. An ASABE standard cone is implemented, which can access heavy compacted layers. The rod, which includes wires for embedding an FDI moisture sensor in the cone tip, is covered by a protection tube. The penetration resistance measurement can be performed without being influenced by shaft friction. The rod, along with the sensor, is implemented in a tower that can be shifted laterally and can take probes in a single line without moving the tractor. To confirm the quality of the developed subsoil penetrometer, a suitable evaluation method is presented. Typical arable soil (loamy silt) was filled in boxes and compacted homogeneously using a hydraulic stamp so that different setups of the penetrometer could be compared and evaluated. The evaluation concludes that the distance between the free cone tip and the protection shaft should be at least 10 cm to measure the penetration resistance of soil without being influenced by the protection tube. Furthermore, the developed penetrometer has sufficient stability and precision for accessing subsoil. In field trials, the subsoil penetrometer was compared with a standard penetrometer and has proved its suitability.

In agriculture, efforts are being made to reduce pesticides and fertilizers because of the possible negative environmental impacts, high costs, political requirements, and declining social acceptance. With precision farming, significant savings can be achieved by the site-specific application of fertilizers. In contrast to currently available single sensors and camera-based systems, arrays or line sensors provide a suitable spatial resolution without requiring complex signal processing and promise significant potential regarding price and precision. Such systems comprise a cost-effective and compact unit that can be extended to any working width by cascading into arrays. In this study, experiments were performed to evaluate the applicability of a TrueColor sensor array in monitoring the nitrogen supply of winter barley during its growth. This sensor is based on recording the reflectance values in various channels of the CIELab color space: luminosity, green–red, and blue–yellow. The unique selling point of this sensor is the detection of luminosity because only the CIELab color space provides this opportunity. Strong correlations were found between the different reflection channels and the nitrogen level (R² = 0.959), plant coverage (R² = 0.907), and fresh mass yield (R² = 0.866). The fast signal processing allows this sensor to meet stringent demands for the operating speed, spatial resolution, and price structure.

INHALT Electrical Agricultural Machines Structuring of electrified agricultural machine systems – Diversity of solutions and analysis methods .....1 GridCON2 – Development of a Cable Drum Vehicle Concept to Power 1MW Fully Electric Agricultural Swarms ..... 11 GridCON Swarm – Development of a Grid Connected Fully Autonomous Agricultural Production System ..... 17 Fully electric Tractor with 1000 kWh battery capacity ..... 23 Soil and Modelling The Integration of a Scientific Soil Compaction Risk Indicator (TERRANIMO) into a Holistic Tractor and Implement Optimization System (CEMOS) .....29 Identification of draft force characteristics for a tillage tine with variable geometry ..... 37 Calibration of soil models within the Discrete Element Method (DEM) ..... 45 Automation and Optimization of Working Speed and Depth in Agricultural Soil Tillage with a Model Predictive Control based on Machine Learning ..... 55 Synchronising machine adjustments of combine harvesters for higher fleet performance ..... 65 A generic approach to bridge the gap between route optimization and motion planning for specific guidance points o...