AgEng-LandTechnik 2022 – Pre Conference Certificate Course

From theory to practice – You are a doctoral researcher or just started your career in science? The pre-conference training courses provide you the unique opportunity to learn and gain additional skill sets around data management, acquisition, sensor systems and modelling by highlighting challenges and solutions (new/old) currently in practice. The courses will take place at the Leibniz Institute for Agricultural Engineering and Bioeconomy to strategically allow the maximum engagement and ensure fruitful interactions between you and the experts.

All participants will receive a certificate for the participated training courses.


Target: Doctoral and early career researchers

Pre-Conference Fee: 50 € per registration 

General Pre-requisites:

  1. Pre-registration is necessary. Participants are requested to register for one of the three optional courses that run in parallel sessions during registration
  2. All participants are requested to carry a laptop

Training Courses

Research data management – Weighing practices

Large amounts of data both quantitative and qualitative in nature is collected during the course of research. This data needs to be structured or organised in a proper manner so that it is possible to recover and access relevant information at any given point of time. Therefore, it is vital to ensure good data management practices. This training course aims to put forward the current challenges and provide information on good data management practices for research while conducting practical exercises within the framework of this course. This training course is a compulsory event for all the registered participants attending the pre-conference program.

No. of participants: all registered participants

Optional Training courses:

1. Smart processing systems – Product orientated processes 

Food plays an essential role in maintaining the overall nutrition security. However, the alarming numbers on food loss/waste and nutrition insecurity calls for approaches and methodologies that are process, resource and energy efficient. Traditional food processing techniques are currently inefficient as they are not only labour intensive but also resource and energy intensive. New technologies, sensors and integration of measurement and control systems has led to the shift to smart food processing techniques. This training course will provide a multidisciplinary view on smart food processing techniques that can reliably replace traditional food processing techniques. Specifically, participants will gain an in depth insight within food processing to produce high quality end products.

No. of participants: min 5 and max 20

2. Infield-ag-robotics – Vision to action

To ensure safe, sustainable and resilient food production processes, agriculture robotics plays a significant role in agricultural engineering. In addition to automating mechanical operations, collecting and analyzing data to make informed decisions is an important aspect of this field. For this purpose, novel methods such as optical sensors are increasingly being used to monitor and evaluate the on farm needs for optimum production processes. Therefore, data from stationary sensors and sensors mounted on mobile platforms are merged to provide an in depth understanding of the plant's needs. In this interactive course, participants will have the opportunity to learn about different sensor integrated solutions while also demonstrating their pros and cons. The course will also present the advancement in the field, by showing how robotics can be used to automatically read the data and take action based on the previously obtained information. For this course, it is suggested that participants have at least entry level programming skills, however it is not compulsory.

No. of participants: min 5 and max 20

3. Efficient welfare: Reconciling energy efficiency and animal welfare through model-predictive environmental control

Environmental control of livestock barns is a growing challenge with serious implications for food security and animal welfare. Despite decades of research, versatile predictors that can be used to prevent and alleviate environmental stress effectively and for a reasonably wide range of animal breeds, facilities and climates remain elusive. Mechanistic models of the thermal interaction between livestock and the environment can be powerful tools for identifying conditions of potential stress and optimizing the barn climate for maximum energy efficiency and minimum stress. Nevertheless, the application of such models remains limited. This workshop presents an overview of thermodynamic models for characterizing the highly coupled, multiphysics interaction between livestock and the environment, with a focus on the systematic implementation and application of such models for deriving stress indicators and thresholds and predictive control of the barn climate. A detailed case study of dairy cattle housed in naturally ventilated barns equipped with a smart climate monitoring and control system will be presented as an example. Participants will have an opportunity for hands-on exercises in developing and using sample models.

No. of participants: min 5 and max 20

Special session: Elevator pitches

The elevator pitch session gives the participants the opportunity to explain their research focus in a simple yet concise manner. An elevator pitch that engages the audience and calls for further discussion in the networking session of is the overall aim of this session. As a competitive incentive the best elevator pitch will be awarded chosen by the jury panel. Doctoral researchers are encouraged to participate in this special session.

Participants: max 15 participants.