Research activities in the first two cycles of European Biosystems engineering university studies - Situation in the Netherlands

Wageningen University has implemented the bachelor – master model by 2003. The biosystems related programmes of Wageningen University are the BSc Agrotechnology and the MSc Agricultural and Bioresource Engineering. The bachelor programme has a size of 180 credits and the master programme a size of 120 credits. Both 1st and 2nd cycle programmes have a strong focus on research. A thesis is part of both programmes; the size is 12 credits for the bachelor thesis (to be increased to 24 by 2010) and 36 for the master thesis. An important difference between the bachelor and the master thesis is the level of independence. The bachelor thesis work is more structured than the master thesis work. Most of the thesis work is related to ongoing research projects. In the bachelor programme there are several courses that confront students with research and in which they learn research and academic skills. In this way the students gradually learn what research is and how to do it. In the master programme there are only a few courses related to the research skills; the students that start with the master are supposed to posses these skills. The BSc degree is not considered as an end point but is a pivot point for choosing a master. Therefore there are no research positions for persons having only BSc degree. Research positions in industry require at least a MSc degree but the trend is that more and more a PhD is required. Senior research positions within the research organizations require in most cased a PhD and within the university it is a basic requirement

Enhancing the attractiveness of european study programmes in biosystems engineering - the Netherlands

Wageningen University and all study programmes are very internationally oriented. First, most of the master programmes have a mandatory internship of 24 credits and the students are stimulated to go abroad. Second, the new structure of the programmes by September 2010 make it for especially the bachelor students more easy to go a certain period abroad to follow courses at an other university. Third, all master programmes are fully taught in the English language, making it possible for foreign students to come to Wageningen University for a master programme. Much effort is put in promoting Wageningen University. The websites play a very important role in informing prospective students on the possibilities offered by Wageningen University. In addition there are paper brochures available with information on all master programmes. Wageningen University is also present on several educational fairs to promote the study programmes

Testing an Online Spread Pattern Determination Sensor on a Broadcast Fertilizer Spreader

An alternative method for fertilizer spread pattern determination was developed based on predicting where individual fertilizer particles land on the ground, in contrast to the traditional method of collecting the particles in bins (ASAE Standard S341.2). A small broadcast granular fertilizer spreader (Lowery 300) was equipped with an optical sensor designed to measure the velocity and diameter of individual fertilizer particles shortly after they leave the impeller disc. The measured velocity and diameter of individual particles were input into a ballistic model that predicted where particles land on the ground. A total of over 1000 landing spots revealed the spread pattern. The results have shown that the optical sensor is capable of automatically determining the spread pattern of a fertilizer spreader on the fly. The sensor could be a key component in the development of uniformity-controlled fertilizer application systems

Structural and Functional Microcirculatory Aspects of Patients with (Suspected) Connective Tissue Disease and Pulmonary Arterial Hypertension

Smulders, Y.M. [Promotor]Vonk Noordegraaf, A. [Promotor]Serné, E.H. [Copromotor]Voskuijl, A.E. [Copromotor

Adaptive detection of volunteer potato plants in sugar beet fields

Volunteer potato is an increasing problem in crop rotations where winter temperatures are often not cold enough to kill tubers leftover from harvest. Poor control, as a result of high labor demands, causes diseases like Phytophthora infestans to spread to neighboring fields. Therefore, automatic detection and removal of volunteer plants is required. In this research, an adaptive Bayesian classification method has been developed for classification of volunteer potato plants within a sugar beet crop. With use of ground truth images, the classification accuracy of the plants was determined. In the non-adaptive scheme, the classification accuracy was 84.6 and 34.9% for the constant and changing natural light conditions, respectively. In the adaptive scheme, the classification accuracy increased to 89.8 and 67.7% for the constant and changing natural light conditions, respectively. Crop row information was successfully used to train the adaptive classifier, without having to choose training data in advanc