Volker Dworak

Strategy for the Development of a Smart NDVI Camera System for Outdoor Plant Detection and Agricultural Embedded Systems

The application of (smart) cameras for process control, mapping, and advanced imaging in agriculture has become an element of precision farming that facilitates the conservation of fertilizer, pesticides, and machine time. This technique additionally reduces the amount of energy required in terms of fuel. Although research activities have increased in this field, high camera prices reflect low adaptation to applications in all fields of agriculture. Smart, low-cost cameras adapted for agricultural applications can overcome this drawback. The normalized difference vegetation index (NDVI) for each image pixel is an applicable algorithm to discriminate plant information from the soil background enabled by a large difference in the reflectance between the near infrared (NIR) and the red channel optical frequency band. Two aligned charge coupled device (CCD) chips for the red and NIR channel are typically used, but they are expensive because of the precise optical alignment required. Therefore, much attention has been given to the development of alternative camera designs. In this study, the advantage of a smart one-chip camera design with NDVI image performance is demonstrated in terms of low cost and simplified design. The required assembly and pixel modifications are described, and new algorithms for establishing an enhanced NDVI image quality for data processing are discussed.

Application of Terahertz Radiation to Soil Measurements: Initial Results

Developing soil sensors with the possibility of continuous online measurement is a major challenge in soil science. Terahertz (THz) electromagnetic radiation may provide the opportunity for the measurement of organic material density, water content and other soil parameters at different soil depths. Penetration depth and information content is important for a functional soil sensor. Therefore, we present initial research on the analysis of absorption coefficients of four different soil samples by means of THz transmission measurements. An optimized soil sample holder to determine absorption coefficients was used. This setup improves data acquisition because interface reflections can be neglected. Frequencies of 340 GHz to 360 GHz and 1.627 THz to 2.523 THz provided information about an existing frequency dependency. The results demonstrate the potential of this THz approach for both soil analysis and imaging of buried objects. Therefore, the THz approach allows different soil samples to be distinguished according to their different absorption properties so that relations among soil parameters may be established in future.

On-the-go Phenotyping in Field Potatoes Using Camera Vision

A camera sensor for detecting crop parameters, with the aim of implementing precision plant protection, has been developed at the Leibniz Institute for Agricultural Engineering. This sensor was tested in farmers’ potato fields regarding the phenotyping and monitoring of crop growth. Field trials were conducted in 2007, 2011 and 2012 to quantify the relationship between the sensor measurements of the coverage level by the green stem and leaf parts and two plant parameters: the fresh mass of the tops and the leaf area index. Within the fields, sampling points were chosen based on differences in crop development. At different dates, the sensor values (coverage level) and the two plant parameters were determined. Because of the shape of the obtained scatterplots between the two plant parameters and the coverage level, a linear regression model with a plateau was adapted. An on-the-go (on-line, real-time) technology for measuring the percentage of green coverage was tested to monitor the development of the potato crop during the growth period. The sensor was positioned on the left side of the tractor to scan the crop stand along transects. The coverage level was measured and recorded together with the geographical position using a data processing system. Areas showing different plant growth could be determined, as could differences in the temporal development of the crop in the various sections of the transect.

Precise Navigation of Small Agricultural Robots in Sensitive Areas with a Smart Plant Camera

Most of the relevant technology related to precision agriculture is currently controlled by Global Positioning Systems (GPS) and uploaded map data; however, in sensitive areas with young or expensive plants, small robots are becoming more widely used in exclusive work. These robots must follow the plant lines with centimeter precision to protect plant growth. For cases in which GPS fails, a camera-based solution is often used for navigation because of the system cost and simplicity. The low-cost plant camera presented here generates images in which plants are contrasted against the soil, thus enabling the use of simple cross-correlation functions to establish high-resolution navigation control in the centimeter range. Based on the foresight provided by images from in front of the vehicle, robust vehicle control can be established without any dead time; as a result, off-loading the main robot control and overshooting can be avoided.

Terahertz Spectroscopy for Proximal Soil Sensing: An Approach to Particle Size Analysis

Spatially resolved soil parameters are some of the most important pieces of information for precision agriculture. These parameters, especially the particle size distribution (texture), are costly to measure by conventional laboratory methods, and thus, in situ assessment has become the focus of a new discipline called proximal soil sensing. Terahertz (THz) radiation is a promising method for nondestructive in situ measurements. The THz frequency range from 258 gigahertz (GHz) to 350 GHz provides a good compromise between soil penetration and the interaction of the electromagnetic waves with soil compounds. In particular, soil physical parameters influence THz measurements. This paper presents investigations of the spectral transmission signals from samples of different particle size fractions relevant for soil characterization. The sample thickness ranged from 5 to 17 mm. The transmission of THz waves was affected by the main mineral particle fractions, sand, silt and clay. The resulting signal changes systematically according to particle sizes larger than half the wavelength. It can be concluded that THz spectroscopic measurements provide information about soil texture and penetrate samples with thicknesses in the cm range.

Vegetationserkennung für landwirtschaftliche Anwendungen mithilfe einer Ein-Chip-Kamera

Durch die Anwendung von Kameras bei der Prozesskontrolle in der Prazisionslandwirtschaft konnen Dunger, Pestizide, Maschinenzeit und Treibstoff eingespart werden. Trotz der hohen Forschungsaktivitaten auf diesem Gebiet verhindern hohe Preise fur geeignete Kamerasysteme die Anwendung in allen Bereichen der Landwirtschaft. Intelligente und kostengunstige Kameras, die fur landwirtschaftliche Anwendungen angepasst werden, konnen diesen Nachteil uberwinden. Der normalisierte differenzierte Vegetationsindex (NDVI) ist ein Algorithmus in der Bildanalyse zur Trennung von Pflanze und Boden (Hintergrund) und wird in der hier vorgestellten Untersuchung bei einer kostengunstigen Ein-Chip-Kamera implementiert und angepasst.