Beschreibung des Feuerbrandbefalls am Institut für Obstzüchtung in Dresden-Pillnitz im Jahr 2003

The orchard of the Institute of Fruit Breeding of the German Federal Centre of Breeding Research on Cultivated Plants in Dresden-Pillnitz was highly affected by fire blight in 2003. Infected pomefruit trees were observed over a period of nearly 3 months. The first symptoms on pear trees were found on May 19th. The pathogen Erwinia amylovora was confirmed officially on May 26, and the last infected apple trees were detected the 11th of August. The infected trees had to be grubbed at the decision of the Phytopathological Authority. In total, 1164 apple and 478 pear trees were grubbed, including the entire pear collection of the gene bank. Of 35 wild species of pear, 49 accessions, eight accessions of six species each, showed infections. The apple collection of the gene bank included 33 wild species, with 365 accessions, and 845 cultivars and clones. Ten accessions of nine wild apple species and 81 cultivars/clones of these collections showed fire blight infection. The source of infection was the pear collection, and the distance from that source was important for the occurrence of infection. Field plots close to the pear collection had tree losses of 10–34%, while more distant plots had losses of 0–6%. Around 80% of the lost apple trees were detected and grubbed from 27th May to 11th June. Some of the cultivars bred in Dresden-Pillnitz, e.g. ‘Pilot’ and ‘Rekarda’, were affected by fire blight in most field plots, whereas most others were affected mainly only in plots adjacent to the infection source. A correlation of r=?0.72 could be calculated for rating in artificial shoot inoculations and percentage of trees of resistant cultivars lost. The cultivars ‘Pirol’, ‘Reanda’, ‘Remo’, ‘Rene’, ‘Renora’, ‘Resi’, and ‘Retina’ showed only a very low numbers of infected trees. No tree of ‘Rewena’ showed symptoms of fire blight. Despite a tendency to postblooming, only 8.9% of ‘Pinova’ trees had to be grubbed.     

Computing inbreeding coefficients and the inverse numerator relationship matrix in large populations of honey bees

The inbreeding coefficients are considered in breeding decisions, and the inverse numerator relationship matrix A ^?1 is a prerequisite for breeding value estimation. Polyandry and haploid males are among the specifics of relationships between honey bees. Brascamp and Bijma (2014) averaged out the manifold possible relationships among honey bees that appear to have the same parents in a pedigree and assigned a single entry in A to animals that behave as a unit, for example, the workers of a hive. Their methods of calculation connected full‐sibs in the variance matrix of the Mendelian sampling terms D , via nonzero off‐diagonal elements. This impedes the inversion of A and the closely connected calculation of inbreeding coefficients, because efficient algorithms for this task take D to be a diagonal matrix. Memory limitations necessitate their use for large data sets. We adapted the quickest of them to the block diagonal matrix D , that is postulated for the honey bee. To our knowledge, the presented algorithm is the first one that facilitates the method of Brascamp and Bijma (2014) on large data sets.     

Relation between soil organic matter and yield levels of nonlegume crops in organic and conventional farming systems

The aim of this study was to evaluate the interaction between yield levels of nonleguminous crops and soil organic matter (SOM) under the specific conditions of organic and conventional farming, respectively, and to identify implications for SOM management in arable farming considering the farming system (organic vs. conventional). For that purpose, correlations between yield levels of nonlegume crops and actual SOM level (C_org, N_t, C_hwe, N_hwe) as well as SOM‐level development were examined including primary data from selected treatments of seven long‐term field experiments in Germany and Switzerland. Yield levels of nonlegume crops were positively correlated with SOM levels, but the correlation was significant only under conditions of organic farming, and not with conventional farming treatments. While absolute SOM levels had a positive impact on yield levels of nonlegumes, the yield levels of nonlegumes and SOM‐level development over time correlated negatively. Due to an increased demand of N from SOM mineralization, higher yield levels of nonlegumes obviously indicate an increased demand for OM supply to maintain SOM levels. Since this observation is highly significant for farming without mineral‐N fertilization but not for farming with such fertilization, we conclude that the demand of SOM‐level maintenance or enhancement and thus adequate SOM management is highly relevant for crop production in organic farming both from an agronomical and ecological point of view. Under conventional management, the agronomic relevance of SOM with regard to nutrient supply is much lower than under organic management. However, it has to be considered that we excluded other possible benefits of SOM in our survey that may be highly relevant for conventional farming as well.     

Stir bar sorptive extraction combined with GC-MS analysis and chemometric methods for the classification of South African Wines according to the volatile composition

A simple method for the analysis of major wine volatiles and semivolatiles by stir bar sorptive extraction in combination with thermal desorption and gas chromatography-mass spectrometry (SBSE-TD-GC-MS) was developed. Significant experimental parameters such as extraction time, temperature, salt addition, pH, and thermal desorption parameters were optimized to provide a sensitive and robust analytical method. The method provided good repeatability (%RSD < 10%) for 38 major wine volatile compounds, including alcohols, acids, esters, phenols, aldehydes, ketones, and lactones. Quantitative data for 62 South African red and white wines were used to study the suitability of major volatile data for the differentiation of wine samples according to grape variety or cultivar. Principal component analysis (PCA) and cluster analysis (CA) showed that most of the variation in volatile composition between wine samples could be ascribed to differences in wine age, wood contact, and fermentation practices. Despite the contribution of these factors, discriminant analysis (DA) was successfully applied to the classification of red and white wine samples according to cultivar.     

Combining agent-based and stock-flow modelling approaches in a participative analysis of the integrated land system in Reichraming, Austria

The integrated modelling of coupled socio-ecological systems in land-change science requires innovative model concepts capable of grasping the interrelations between socioeconomic and natural components. Here, we discuss the integrated socio-ecological model SERD (Simulation of Ecological Compatibility of Regional Development) that was developed for the municipality of Reichraming in Upper Austria in a participative 2-year process involving local stakeholders. SERD includes three main components: (1) an agent-based actors module that simulates decisions of farmsteads, the municipal administration and other important actors; (2) a spatially explicit (GIS based) land-use module that simulates land-use change at the level of individual parcels of land and (3) an integrated socio-ecological stock-flow module that simulates carbon and nitrogen flows through both socioeconomic and ecological system compartments. We report on outcomes of a scenario analysis that outlines possible future trajectories depending on both external (e.g. agricultural subsidies and prices) and internal (e.g. innovation, willingness to co-operate) factors. We find that both external and internal factors can affect the behaviour of the integrated system considerably. Local and regional policies are found to be able to counteract adverse global socioeconomic conditions to some extent, but not to reverse the trend altogether. We also find strong interdependencies between socioeconomic and ecological components of the system. Fully evaluating these interdependencies is, however, not possible at the local scale alone and will require explicit consideration of higher-level effects in future research.