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Comparison of variable liming strategies in organic farming systems using online pH-measurements
(2011)
In organic farming, soil pH is one of the most important soil characteristics affecting nutrient availability, soil microbial activity and plant growth. Using the soil pH mapping sensor system Veris MSP, detailed information on in-field variability of soil pH can be obtained enabling spatial variable lime application. Scenario calculations for an organically managed field in Germany reveal that compared with the standard farm practice (i.e. uniform liming rate) variable lime application does not lead to higher costs while soil pH is optimized in different field zones resulting in increased crop productivity. Using two different lime qualities increases liming costs moderately but gives farmers the chance to increase pH quickly in extreme low pH areas.
Transition road maps – an investigative approach to map the daily life consumption of individuals
(2014)
The present paper aims at investigating an innovative approach to guide consumers’ daily life choices in Germany towards a more sustainable way of acting. This should be achieved by introducing a new concept: transition road maps. Transition road maps bear the capability of illustrating courses of consumption behaviour without being prohibitive. These schemes foster self-determined behaviour and encourage the consumer to rethink and restructure his or her habits of consumption, with a focus on sustainability. The innovative thought is, not to simply stick to the usual triad of spheres of activity, consisting of nutrition, mobility and housing. Instead further aspects of consumers’ daily routines are considered, such as leisure activities, time usage or financial activities. Moreover the transition road maps are based on a new ideology of combining and connecting the qualitative algorithm of time use, financial spending and resource impact of social practices in the area of private consumption. In the long-term, the transition road maps could e.g. be used in sustainability communication or consumer counselling.
Between Ekaterinburg and Nowosibirsk, in the Western Siberian grain belt, spring wheat is grown on fertileChernozem soils. Field and farm sizes are large but the land-use intensity per area is low compared to CentralEurope. Fertilizers and pesticides are applied only in low to moderate quantities and yields range between 10and 20 dt ha-1 . We studied the arable weed flora in the northern forest steppe zone of Tyumen region using arandomized sampling design. Surprisingly, the species richness was only moderate, on average 9.8 ± 3.8species per 100 m². Compared to weed communities of Bashkiria (Southern Ural) and less intensively usedarable land of Central Europe these numbers are rather low. Moreover, most of the recorded species werecosmopolitans or widely distributed throughout the temperate zone. We suggest that the land use intensitywas high enough to reduce the density of a number of weed species in a way that they were not registered byour random sampling design. The limited conservational value of the weed vegetation of large grain fields inTyumen leads to the conclusion that if intensification of land use is unavoidable, it should be directed to arableland and not to ex-arable land or ancient grassland, which is of higher conservation value.
This study identifies and evaluates factors for success in innovation work in the Bavarian dairy farming industry. The research is based on an analysis of innovation system theories and a comparison with innovation work in the Dutch dairy sector. Dutch dairy farming is characterized by high productivity and technical efficiency at the farm level. Moreover, important developments in dairy farming have originated in the Netherlands. Therefore, this study delves into the systemic background of the successful innovation work in the Netherlands and makes a comparison with Bavaria. The main result of this study is that innovation work in the Bavarian dairy farming sector is lacking in two respects: end-user (farmer) integration and within-sector cooperation.
German farmers are required by law to regularly self-assess the welfare of their animals. The project Q Check is aiming at developing a system that will assist farmers to objectively assess animal health and welfare in dairy cows. For this reason, a quarterly report will be compiled from animal-based key indicators to give an overview of the on-farm situation. The anonymised and aggregated reports can also be used for national animal welfare monitoring: Continuous collection of these key indicators enables the summary and publication of figures reflecting the current animal health and welfare status and progressions at federal state and at national level. Q Check is based on four data recording and analysis systems, which are already established in Germany and implemented on a national level. Out of these systems, the most suitable indicators to describe herd health have been selected by 215 experts within a twostage Delphi study. In addition, over 50 face-to-face interviews with stakeholders related to the German dairy sector have been performed in order to take into account the socio-scientific point of view. To complete the process, the selected indicators are currently being checked against mass data and hence tested for suitability regarding monitoring purposes. An automatic farm-specific evaluation of animal health, based on verified indicators, will provide support to farmers in fulfilling their legal requirements and in identifying weak points on the individual farms. A benchmarking system will be set up which will allow tracking the individual herd health indicators in the same farm in their course over time and compared with similar farms. These routinely provided horizontal and vertical statistics will facilitate targeted intervention and support objectified management decisions, implying that dairy farmers can benefit in several respects. In the course of the project, new tools for determining the risk of ketosis in the scope of milk recording will also be validated and implemented at national level to enhance monitoring of this major disease complex. The results of these nationwide, systematic investigations will contribute substantially to objectifying the discussion about the health and welfare situation of dairy cows.
In this paper, we evaluate the application of Bayesian Optimization (BO) to discrete event simulation (DES) models. In a first step, we create a simple model, for which we know the optimal set of parameter values in advance. We implement the model in SimPy, a framework for DES written in Python. We then interpret the simulation model as a black box function subject to optimization. We show that it is possible to find the optimal set of parameter values using the open source library GPyOpt. To enhance our evaluation, we create a second and more complex model. To better handle the complexity of the model, and to add a visual component, we build the second model in Simio, a commercial off-the-shelf simulation modeling tool. To apply BO to a model in Simio, we use the Simio API to write an extension for optimization plug-ins. This extension encapsulates the logic of the BO algorithm, which we deployed as a web service in the cloud.
The fact that simulation models are black box functions with regard to their behavior and the influence of their input parameters makes them an apparent candidate for Bayesian Optimization (BO). Simulation models are multivariable and stochastic, and their behavior is to a large extent unpredictable. In particular, we do not know for sure which input parameters to adjust to maximize (or minimize) the model’s outcome. In addition, the complex models can take a substantial amount of time to run.
Bayesian Optimization is a sequential and self-learning algorithm to optimize black box functions similar to as we find them in simulation models: they contain a set of parameters for which we want to identify the optimal set, they are expensive to evaluate, and they exhibit stochastic noise. BO has proven to efficiently optimize black box functions from varius disciplines. Among those, and most notably, it is successfully applied in machine learning algorithms to optimize hyperparameters.
Studies on nutrition have historically concentrated on food-shortages and over-nutrition. The physiological states of feeling hungry or being satiated and its dynamics in food choices, dietary patterns, and nutritional behavior, have not been the focus of many studies. Currently, visual analytic using easy-to-use tooling offers applicability in a wide-range of disciplines. In this interdisciplinary pilot-study we tested a novel visual analytic software to assess dietary patterns and food choices for greater understanding of nutritional behavior when hungry and when satiated. We developed software toolchain and tested the hypotheses that there is no difference between visual search patterns of dishes 1) when hungry and when satiated and 2) in being vegetarian and non-vegetarian. Results indicate that food choices can be deviant from dietary patterns but correlate slightly with dish-gazing. Further, scene perception probably could vary between being hungry and satiated. Understanding t he complicated relationship between scene perception and nutritional behavioral patterns and scaling up this pilot-study to a full-study using our introduced software approaches is indispensable.
To assess the effect of intercropping on malting quality a field trial with spring barley (Hordeum vulgare) and legume (pea) as well as non-legume (camelina and linseed) intercrops in two additive seeding ratios as well as sole cops was established in 2017 at the organic experimental station of University of Applied Sciences Osnabrück in North-Western Germany. Two tested malting barley cultivars (cv. Marthe and cv. Odilia) showed different performance, but all variants achieved brewing quality. Results after two years indicate that linseed and camelina were able to limit protein content. For best land-use efficiency of malting barley production intercropping with linseed showed best results. Mixed intercropping can help to promote internal efficiency loops and is therefore a promising sustainable intensification strategy for more resilient future crop production under changing climate conditions.
Nitrogen (N) pollution of groundwater bodies is often a result of high livestock densities combined with use of mineral N fertilisers in Northwest Germany, specifically in combination with sandy soils and high amounts of precipitation. Organic agriculture is discussed as an alternative management practice reducing nitrogen losses due to area-based livestock densities and waiving of mineral N fertilisers. A field trial with integrated ceramic suction cups over three years showed potential for reduced N loads under conventional management specifically with organic fertilisation. Now, the field trial is under transition into organic farming with promising additional benefits for drinking water quality and the great potential to develop optimised N management strategies.
Animal husbandry methods also play an important role in public discussion, as animal welfare is often valued in society by visual perceptions. In this context, there is often an idealized idea of livestock husbandry and nutrition, which is staged by ideal-typical images. In the minds of many citizens, nature-loving images trigger a positive imagination that results from the longings of urban living conditions. Media and stakeholder analyses indicate that the use of straw in livestock husbandry and nutrition also has a positive impact on the welfare of livestock. According to this, straw is preferred by the public for more animal welfare. But what is not considered is the fact that the straw must be of impeccable hygienic quality
Animal husbandry methods also play an important role in public discussion, as animal welfare is often valued in society by visual perceptions. In this context, there is often an idealized idea of livestock husbandry and nutrition, which is staged by ideal-typical images. In the minds of many citizens, nature-loving images trigger a positive imagination that results from the longings of urban living conditions. Media and stakeholder analyses indicate that the use of straw in livestock husbandry and nutrition also has a positive impact on the welfare of livestock. According to this, straw is preferred by the public for more animal welfare.
But what is not considered is the fact that the straw must be of impeccable hygienic quality. Fungal infestation and the formation of mycotoxins in straw can cause diseases in livestock with consequences for animal welfare.
The first evaluation of a perfect straw quality also takes place in science through sensory tests, i.e. through smell, grip, colour and impurities. Only in the case of abnormalities in the sensory tests are further examinations indicated, such as microbiological examination procedures.
The hygienic properties of straw were examined on the basis of these assessment criteria. In addition to the microbiological-hygienic tests, the sensors of the straw were also tested.
The results show that there are no abnormalities in the sensory examination of the hygiene status. This was to observe an impeccable hygiene status.
However, the microbiological-hygienic investigations showed that the straw had microbiological as well as mycotoxin loads above the orientation values. This can have negative health effects, such as diseases for farm animals.
The scientific results led to the conclusion: The public discussion about animal welfare, which is often conducted primarily on the basis of visual impressions, could gain in scientific resilience if it includes objective results such as microbiological analyses in addition to images in order to evaluate animal welfare in livestock farming