Browsing by Subject "Pflanzenkrankheit"

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Biometrical approaches for analysing gene bank evaluation data on barley (Hordeum spec.)
(2007) Hartung, Karin; Piepho, Hans-Peter
This thesis explored methods to statistically analyse phenotypic data of gene banks. Traits of the barley data (Hordeum spp.) of the gene bank of the IPK-Gatersleben were evaluated. The data of years 1948-2002 were available. Within this period the ordinal scale changed from a 0-5 to a 1-9 scale after 1993. At most gene banks reproduction of accessions is currently done without any experimental design. With data of a single year only rarely do accessions have replications and there are only few replications of a single check for winter and summer barley. The data of 2002 were analysed separately for winter and summer barley using geostatistical methods. For the traits analysed four types of variogram model (linear, spherical, exponential and Gaussian) were fitted to the empirical variogram using non-linear regression. The spatial parameters obtained by non-linear regression for every variogram model then were implemented in a mixed model analysis and the four model fits compared using Akaike's Information Criterion (AIC). The approach to estimate the genetical parameter by Kriging can not be recommended. The first points of the empirical variogram should be explained well by the fitted theoretical variogram, as these represent most of the pairwise distances between plots and are most crucial for neighbour adjustments. The most common well-fitting geostatistical models were the spherical and the exponential model. A nugget effect was needed for nearly all traits. The small number of check plots for the available data made it difficult to accurately dissect the genetical effect from environmental effects. The threshold model allows for joint analysis of multi-year data from different rating scales, assuming a common latent scale for the different rating systems. The analysis suggests that a mixed model analysis which treats ordinal scores as metric data will yield meaningful results, but that the gain in efficiency is higher when using a threshold model. The threshold model may also be used when there is a metric scale underlying the observed ratings. The Laplace approximation as a numerical method to integrate the log-likelihood for random effects worked well, but it is recommended to increase the number of quadrature points until the change in parameter estimates becomes negligible. Three rating methods (1%, 5%, 9-point rating) were assessed by persons untrained (A) and experienced (B) in rating. Every person had to rate several pictograms of diseased leaves. The highest accuracy was found with Group B using the 1%-scale and with Group A using the 5%-scale. With a percentage scale Group A tended to use values that are multiples of 5%. For the time needed per leaf assessment the Group B was fastest when using the 5% rating scale. From a statistical point of view both percent ratings performed better than the ordinal rating scale and the possible error made by the rater is calculable and usually smaller than with ratings by rougher methods. So directly rating percentages whenever possible leads to smaller overall estimation errors, and with proper training accuracy and precision can be further improved. For gene banks augmented designs as proposed by Federer and by Lin et al. offer themselves, so an overview is given. The augmented designs proposed by Federer have the advantage of an unbiased error estimate. But the random allocation of checks is a problem. The augmented design by Lin et al. always places checks in the centre plot of every whole plot. But none of the methods is based on an explicit statistical model, so there is no well-founded decision criterion to select between them. Spatial analysis can be used to find an optimal field layout for an augmented design, i.e. a layout that yields small least significant differences. The average variance of a difference and the average squared LSD were used to compare competing designs, using a theoretical approach based on variations of two anisotropic models and different rotations of anisotropy axes towards field reference axes. Based on theoretical calculations, up to five checks per block are recommended. The nearly isotropic combinations led to designs with large quadratic blocks. With strongly anisotropic combinations the optimal design depends on degree of anisotropy and rotation of anisotropy axes: without rotation small elongated blocks are preferred; the closer the rotation is to 45° the more squarish blocks and the more checks are appropriate. The results presented in this thesis may be summarised as follows: Cultivation for regeneration of accessions should be based on a meaningful and statistically analysable experimental field design. The design needs to include checks and a random sample of accessions from the gene pool held at the gene bank. It is advisable to utilise metric or percentage rating scales. It can be expected that using a threshold model increases the quality of multivariate analysis and association mapping studies based on phenotypic gene bank data.
Effects of elevated atmospheric CO2 concentrations on insects and pathogens of spring wheat (Triticum aestivum L. cv. Triso) and oilseed rape(Brassica napus cv. Campino)
(2012) Oehme, Viktoriya; Fangmeier, Andreas
It is suggested that plants, herbivore insects and pathogens will be affected by rising atmospheric CO2. The working hypothesis of this study was that elevated CO2 will affect plant composition and will thus exert influence on plant-insect interactions by changing the nutritive value for insects feeding on phloem sap. To test this hypothesis, experiments were carried out on wheat and oilseed rape in two different systems: controlled environment chambers (climate chamber system) and an open field exposure system with natural climatic and soil conditions (Mini FACE system). The abundance of detrimental insects from different feeding guilds and plant damage by parasitic organisms were examined in a Mini FACE system, while the consequences of elevated CO2 on aphid performance and potential correlations to phloem sap composition of host plants were observed in controlled environment chambers. The concentrations of amino acids and carbohydrates in the phloem of host plants were analysed by high?performance liquid chromatography (HPLC), using a fluorescence detector for amino acids and the evaporative light scattering detector for carbohydrates. In a Mini-FACE system, phenological development of spring wheat and OSR was not significantly changed due to CO2 enrichment. However, elevated CO2 induced changes in plant chemistry (increased carbon:nitrogen ratio and defensive compounds), which resulted in changes in population densities of some pest species. In order to monitor alterations in insect population density, two different methods were applied: direct counts (method 1) and using of yellow sticky traps (method 2). These methods showed both increases and decreases of insect numbers due to elevated CO2, depending on species and on the period of observation. Concerning plant pathogens, leaves of spring wheat were only slightly and not significantly damaged by Erysiphe graminis, Puccinia striiformis, Puccinia recondita and Septoria tritici during the 2006/2008 years in all treatments. Also the OSR was not significantly damaged by Peronospora parasitica. The frequency and severity of disease infestation on spring wheat and OSR was not significantly impacted by elevated CO2. In controlled-environment chambers, the phenology, above ground biomass and RGR of OSR were not significantly impacted due to elevated CO2. And although the phenology of spring wheat was not influenced by raised CO2, significant increases were observed for plant above ground biomass and RGR. The aphid presence significantly reduced the aboveground biomass and RGR of spring wheat, while no effects due to aphids were observed in OSR. High-CO2 treatment differently impacted the performance of aphids. Slight and non-significant increases due to elevated atmospheric CO2 conditions were observed for the aphid relative developmental stages and intrinsic rates of increase, while the weight and RGR were significantly increased for Rhopalosiphum padi and decreased for Myzus persicae. In order to clear CO2-impacts on the insect performance, phloem sap from host plants was analysed for the composition and concentration of amino acids and carbohydrates. In summary, although the phenological development of spring wheat and OSR was not affected due to elevated CO2, significant changes were found for the concentration of carbohydrates in the phloem sap of spring wheat and individual amino acids in both host plants. These alterations in plant chemistry affected the performance and abundance of herbivore insects.
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.