Frits K. van Evert

The ModCom modular simulation system

Simulation models of agro-ecological systems are typically written in a manner that precludes reusability of parts of the model without a significant amount of familiarity with and rewriting of existing code. Similarly, replacing a part of a model with a functionally equivalent part from another model is typically difficult. The objective of this study was to develop a method to enable the assembly of simulation models from previously and independently developed component models. Recent advances in software engineering have enabled the development of software applications from smaller parts (called components) on the basis of an abstract decomposition of the relevant domain (called a framework). Based on a requirements analysis of existing simulation models we developed the ModCom simulation framework. ModCom provides a set of interface specifications that describe components in a simulation. ModCom also provides implementations of the core simulation services. The framework interfaces use well-defined binary standards and allows developers to implement the interfaces using a broad range of computer languages. Using this framework, simulation models can be assembled by connecting component models in much the same way that Lego blocks are put together to assemble a house. ModCom thus allows modelers to create models and modeling tools that are easily exchanged (in binary form or source code) with colleagues across the hall or across the globe.

A Mobile Field Robot with Vision-Based Detection of Volunteer Potato Plants in a Corn Crop'

Volunteer potato is a perennial weed that is difficult to control in crop rotations. It was our objective to build a small, low-cost robot capable of detecting volunteer potato plants in a cornfield and thus demonstrate the potential for automatic control of this weed. We used an electric toy truck as the basis for our robot. We developed a fast row-recognition algorithm based on the Hough transform and implemented it using a webcam. We developed an algorithm that detects the presence of a potato plant based on a combination of size, shape, and color of the green elements in an image and implemented it using a second webcam. The robot was able to detect potatoes while navigating autonomously through experimental and commercial cornfields. In a first experiment, 319 out of 324 images were correctly classified (98.5%) as showing, or not showing, a potato plant. In a second experiment, 126 out of 141 images were correctly classified (89.4%). Detection of a potato plant resulted in an acoustic signal, but future robots may be fitted with weed control equipment, or they may use a global positioning system to map the presence of weed plants so that regular equipment can be used for control. Nomenclature: Corn, Zea mays L, Potato, Solanum tuberosum L. Additional index words: Autonomous navigation, autonomous weeding, glyphosate, machine-vision, site-specific weed control. Abbreviations: DIPlib, Delft image-processing library; DSP, digital signal processor; GPS, global positioning system; JPEG, Joint Photographic Experts Group; NiMh, nickle metal hydride; PC, personal computer.

A robot to detect and control broad-leaved dock ( Rumex obtusifolius L.) in grassland

Broad-leaved dock is a common and troublesome grassland weed with a wide geographic distribution. In conventional farming the weed is normally controlled by using a selective herbicide, but in organic farming manual removal is the best option to control this weed. The objective of our work was to develop a robot that can navigate a pasture, detect broad-leaved dock, and remove any weeds found. A prototype robot was constructed that navigates by following a predefined path using centimeter-precision global positioning system (GPS). Broad-leaved dock is detected using a camera and image processing. Once detected, weeds are destroyed by a cutting device. Tests of aspects of the system showed that path following accuracy is adequate but could be improved through tuning of the controller or adoption of a dynamic vehicle model, that the success rate of weed detection is highest when the grass is short and when the broad-leaved dock plants are in rosette form, and that 75% of weeds removed did not grow back. An on-farm field test of the complete system resulted in detection of 124 weeds of 134 encountered (93%), while a weed removal action was performed eight times without a weed being present. Effective weed control is considered to be achieved when the center of the weeder is positioned within 0.1 m of the taproot of the weed—this occurred in 73% of the cases. We conclude that the robot is an effective instrument to detect and control broad-leaved dock under the conditions encountered on a commercial farm.

Advances in Variable Rate Technology Application in Potato in The Netherlands

Precision agriculture is a farming management concept based on observing, measuring and responding to inter- and intra-field variability in crops. In this paper, we focus on responding to intra-field variability in potato crops and analyse variable rate applications (VRAs). We made an overview of potential VRAs in potato crop management in The Netherlands. We identified 13 potential VRAs in potato, ranging from soil tillage to planting to crop care to selective harvest. We ranked them on availability of ‘proof of concept’ and on-farm test results. For five VRAs, we found test results allowing to make a cost-benefit assessment. These five VRAs were as follows: planting, soil herbicide weed control, N side dress, late blight control and haulm killing. They use one of two types of spatial data: soil maps or biomass index maps. Data on costs and savings of the VRAs showed that the investments in VRAs will pay off under practical conditions in The Netherlands. Savings on pesticide use and N-fertilizer use with the VRAs were on average about 25%, which benefits the environment too. We foresee a slow but gradual adoption of VRAs in potato production. More VRAs will become available given ongoing R&D. The perspectives of VRAs in potatoes are discussed.

Robotic Seeding: Economic Perspectives

Agricultural robotics has received attention for approximately 20 years, but today there are only a few examples of the application of robots in agricultural practice. The lack of uptake may be (at least partly) because in many cases there is either no compelling economic benefit, or there is a benefit but it is not recognized. The aim of this chapter is to quantify the economic benefits from the application of agricultural robots under a specific condition where such a benefit is assumed to exist, namely the case of early seeding and re-seeding in sugar beet. With some predefined assumptions with regard to speed, capacity and seed mapping, we found that among these two technical systems both early seeding with a small robot and re-seeding using a robot for a smaller part of the field appear to be financially viable solutions in sugar beet production.