Browsing by Subject "Site-specific"

Now showing 1 - 3 of 3

Development of a sensor-based harrowing system using digital image analysis to achieve a uniform weed control selectivity in cereals
(2021) Spaeth, Michael; Gerhards, Roland
Using intelligent sensor technology for site-specific weed control can increase the efficacy of traditional weed control implements. Several scientific studies successfully used intelligent sensors for automatic harrow control by taking many different parameters into account such as weed density, soil resistance factor, and plant growth. However, none of the systems was practically feasible because these factors made the control system too complex and unattractive for farmers. Defining only one parameter (crop soil cover) instead of many provides a new and simple approach which was investigated in this work. The first scientific publication focuses on the development, practical implementation and testing of the automatic harrow control system. Two RGB-cameras were mounted before and after the harrow and constantly monitored crop cover. The CSC was then computed out of these resulting images. The image analysis, decision support system and automatic control of harrowing intensity by hydraulic adjustment of the tine angle were installed on a controller which was mounted on the harrow. Eight field experiments were carried out in spring cereals. Mode of harrowing intensity was changed in four experiments by speed, number of passes and tine angle. Each mode was varied in five intensities. In four experiments, only the intensity of harrowing was changed. Modes of intensity were not significantly different among each other. However, intensity had significant effects on WCE and CSC. Cereal plants recovered well from 10% CSC, and selectivity was in the constant range at 10% CSC. Therefore, 10% CSC was the threshold for the decision algorithm. If the actual CSC was below 10% CSC, intensity was increased. If the actual CSC was higher than 10%, intensity was decreased. The new system was tested in an additional field study. Threshold values for CSC were set at 10%, 30% and 60%. Automatic tine angle adjustment precisely realised the three different CSC values with variations of 1.5% to 3%. The next publication discussed and assessed the site-specific field adaptation of the development in cereals. In 2020, three field experiments were conducted in winter wheat and spring oats to investigate the response of the weed control efficacy and the crop to different harrowing intensities, in southwest Germany. In all experiments, six levels of CSC were tested. Each experiment contained an untreated control and an herbicide treatment as a comparison to the harrowing treatments. The results showed an increase in the WCE with an increasing CSC threshold. Difficult-to-control weed species such as Cirsium arvense (L.) and Galium aparine (L.) were best controlled with a CSC threshold of 70%. With a CSC threshold of 20% it was possible to control up to 98% of Thlaspi arvense (L.) The highest crop biomass, grain yield, and selectivity were achieved with an CSC threshold of 20–25% at all trial locations. With this harrowing intensity, grain yields were higher than in the herbicide control plots and a WCE of 68–98% was achieved. The last scientific article compares pairwise a conventional harrow intensity with automatic sensor-based harrowing intensity. Five field experiments in cereals were conducted at three locations in southwestern Germany in 2019 and 2020 to investigate if camera-based harrowing resulted in a more homogenous CSC and higher WCE, biomass, and crop grain yield than a conventional harrow with a constant intensity across the whole plot. For this purpose, pairwise comparisons of three fixed harrowing intensities (10 °, 40 °, and 70 ° tine angle) and three predefined CSC thresholds (CSC of 10%, 20%, and 60%) were realized in randomized complete block designs. Camera-based adjustment of the intensity resulted in 6-16% less standard deviation variation of CSC compared to fixed settings of tine angle. Crop density, WCE, crop biomass and grain yield were significantly higher for camera-based harrowing than for conventional harrowing. WCE and yields of all automatic adjusted harrowing treatments were equal to the herbicide control plots. In this PhD-thesis, a sensor-based harrow was developed and successfully investigated as an alternative to conventional herbicide application in cereals. A permanent, equal replacement of chemical weed control in arable farming systems can only be achieved using modern, sensor-based mechanical weed control approaches. Therefore, the efficacy of the mechanical weed control method can be improved and increased continuously. It has been shown that the precise adjustment of mechanical weed control methods to site-specific weed conditions allows similar WCE results as an herbicide application without causing yield losses. These findings contribute towards modern plant protection strategies to reduce the herbicide use and to establish the acceptance of technical progress in society.
Site-dependent differences in DNA methylation and their impact on plant establishment in Populus trichocarpa
(2016) Schönberger, Brigitte; Ludewig, Uwe
Phosphate (Pi) limits total biomass production in natural tree ecosystems. Due to the low mobility of Pi in soil, higher plants, like trees, require special adaptations for phosphorus (P) acquisition. The genetic and physiological basis of this adaptation has been studied extensively. In addition, phosphorus starvation was recently suggested to affect epigenetic modifications in varying annual plant species. However, the impact of differential DNA methylation and microRNAs (miRNAs) on gene expression as well as site-dependent P-related physiology is largely unknown in perennials. In this study Populus trichocarpa clones, established from stem cuttings from two different locations, were grown in hydroponic culture with different P levels. Morphological and physiological parameters as well as, using bisulfite sequencing, site-specific genome-wide methylomes were determined. Gene and miRNA expression of differentially methylated regions was quantified via qPCR. Site-dependent differences in plant establishment were encountered, together with site-specific differentially methylated chromosomal regions. Methylation differences were nucleotide context-specific and extensively regulated miRNAs and their target genes in an organ-specific way. Though no direct relation between differential methylation in coding regions and their corresponding gene expression was observed, a general site-dependent transcriptional repression by DNA methylation was detected. Nevertheless, differential DNA methylation and gene expression was not affected by P nutrition, although recent studies described P-starvation induced DNA methylation changes, suggesting species-specific epigenetic mechanisms. However, differentially methylated miRNAs, together with their target genes, showed P-dependent expression profiles, indicating miRNA expression changes as a P-related epigenetic modification in poplar. Hence, it was shown that differences in DNA methylation or differentially methylated miRNAs might influence plant establishment and partially correlate with P acquisition, and thus be responsible for a site-dependent adaptation and growth performance, interesting for plant breeding, conservation biology and biodiversity studies of vegetatively propagated perennials.
Use of sensor technologies to estimate and assess the effect of various plant diseases on crop growth and development
(2008) Gröll, Kerstin; Claupein, Wilhelm
The topic of this study was ?Use of sensor technologies to estimate and assess the effect of various plant diseases on crop growth and development?. The background of the investigation can be seen in the challenge of developing a sensor system for the site-specific identification of plant diseases. The most widely used practice in disease control is still to spray fungicides uniformly over fields at different times during the vegetation period. However, most diseases are not distributed uniformly across a field, but occur in patches. During the early stage of epidemics large areas of the field are disease free. Excessive use of fungicides increases costs and can increase fungicides residue levels on agricultural products. As there is an increasing pressure to reduce their use by targeting fungicide spraying only on those places in the field where they are needed, the challenge is to provide farmers the the appropriate technological solutions. A simple and cost-effective optical device, based on the measurement of canopy reflectance in several wavebands, would allow disease patches to be identified and thus controlled. The implementation of these reflectance measurement data into crop growth models would allow for the development of site-specific decision rules whether to spray or not to spray. The specific objectives of the Ph.D. thesis were to: develop and test reflectance measurements as a possible technology to identify reflectance signatures of various plant diseases; develop suitable sets of calibrations that can be used for the identification and quantification of plant diseases; test different sensor systems at different spatial resolutions for their ability to identify plant diseases; develop a strategy to use plant disease information gained from sensor measurements as input dataset for the simulation of wheat growth under disease pressure in CERES-Wheat. In greenhouse experiments at the University of Hohenheim and in field experiments at the experimental station ?Ihinger Hof? of the University of Hohenheim the influence of the diseases powdery mildew, septoria leaf blotch and wheat eyespot on the reflectance of winter wheat was analyzed. To measure the reflectance of the plants three different sensor systems were used. Plant reflectance was measured with a digital camera (LEICA S1 PRO, LEICA Kamera AG, Solms, Germany) at leaf scale (0.5 cm²) and with the spectroradiometer Field Spec® Hand Held (ASD, Inc. Boulder, CO, USA) (0.5 m²) and the Yara N-Sensor in the field-scan modus (12 m²) 2 m above the canopy. The diseases powdery mildew, septoria leaf blotch and wheat eyespot have been analyzed. In a first approach it was tested if it is possible to detect plant diseases using reflectance measurements. The greenhouse studies showed that powdery mildew could be identified especially in the visible wavelength range. Also a correlation between powdery mildew pustules and reflectance changes was possible. Powdery mildew is a leaf disease and changes could directly be detected by a sensor system (Chapter 5). Out of this the second approach was to analyze if a stem disease that cannot directly be detected could be identified using a sensor system. The influence of wheat eyespot was investigated in a field experiment with winter wheat. The results showed that wheat eyespot could not be detected with the digital camera and the spectroradiometer. The problem was the low infection level and the distance between the measuring place and the infection place (Chapter 6). In a next step common vegetation indices were tested for their ability to identify plant diseases. Different vegetation indices were selected out of the literature to detect powdery mildew and septoria leaf blotch in the field using a spectroradiometer. Results indicated that the common vegetation index REIP was able to detect powdery mildew at an infection level of 7 %. With the common vegetation indices septoria leaf blotch could be detected only at a late infection level of 13.7 %. Out of this the new vegetation index DII was developed, which was able to detect septoria leaf blotch at an early infection level of 4 % (Chapter 7). Not only the place of infection but also the spatial resolution seems to play an important role in the identification of plant diseases. In a further approach different sensor systems with different spatial resolutions were tested in a field experiment for the identification of septoria leaf blotch. The results showed in general that septoria leaf blotch could be identified especially in the infrared wavelength range compared to powdery mildew that could especially identified in the visible wavelength range. The results showed further that the lower the spatial resolution , the more difficult it gets to identify plant diseases site-specifically. With a spatial resolution of 0.5 cm² a identification and quantification was possible. With a spatial resolution of 0.5 m² only a identification was possible and with a spatial resolution of 12 m² not identification and quantification was possible. That might be because of the resulting mixture of healthy and diseased plants (Chapter 8). The last step of this work was then to show how reflectance measurements could be implemented into crop growth models to calculate decisions whether to spray or not to spray fungicides on a site-specific level. Summarizing, the overall results of this study indicated that an identification of plant diseases was possible under certain conditions. An identification was possible if the infection place was also the measuring place and if a sensor system was used with a high spatial resolution. The results also showed that it was possible in a certain way to differ between biotroph and necrotroph plant diseases. For a holistic farming concept it is necessary in the future that reflectance measurements are integrated in a crop growth model to give farmers a decision tool that decides whether the infection is critical enough to spray or not.