PhD in IOT in Agriculture: Development of Novel Sensors for Online Milk Quality and Cow Health Monitoring KU Leuven Geel Biosystems TC, Geel Campus Belgium

Iot In Agriculture: Development Of Novel Sensors For Online Milk Quality And Cow Health Monitoring (Phd)

 

Last modification : Saturday, May 4, 2019

 

 

Optimization and intensification of livestock production is widely encouraged to meet the increasing demands for livestock products and to contribute to improving the livelihoods of rural households. To this end, sustainable animal production which guarantees welfare for both the animal and the farmer requires automation of the production process in combination with thorough health monitoring of the individual animals. The research team “Livestock Technology”, under the lead of Prof. Ben Aernouts, develops, implements and validates innovative sensor technology and data processing algorithms to support the animal management in livestock production. Our research lab is hosted by the KU Leuven Technology campus in Geel, located in a green and rural environment, in close collaboration with the industry and the livestock sector.

Project

 

In Flanders, dairy production is an important segment of the agricultural production, representing about 15% of the total market value. Over the last 50 years, the average milk production per cow and per lactation has increased drastically as a result of genetic selection and improved feed and management practices in dairy farming. However, due to the intense focus on high milk production, modern dairy cows are prone to production-related disorders. As the production of milk is a dominant factor in the metabolism of dairy cows, involving a very intense interaction with the blood circulation, the extracted milk contains valuable information on the metabolic status of the cow. Therefore, regular analysis of the produced milk is considered the most efficient way to monitor cow health.

 

Today, online measurements of the milk production, conductivity and color is already common practice in dairy farming. Nevertheless, these milk parameters are influenced by many factors next to the health status of the cow. For this reason, there is a need for monitoring parameters which have a more direct link with the cow’s health. The formation of milk components, such as milk fat, protein and lactose, is the immediate result of the cow’s feed uptake and metabolic status, as well as the health of the milk producing cells in the udder. As a result, regular analysis of the basic milk components for each individual cow can give valuable information on its udder health and metabolic and nutritional status.

 

In this project, online milk analyzer prototypes will be designed and built based on miniature spectrometers (MEMS technology). These sensors will be implemented in automatic milking systems to monitor the milk quality at the level of udder quarters. This will allow for the elimination of systemic effects of the animals through inter-quarter comparison, supporting a high performance warning system for identifying mastitis. Furthermore, the robustness of these sensors will be evaluated and improved by applying different calibration strategies. Finally, the variation of the sensor measurements will be studied in relation to the cow’s health and combined with advanced data-processing techniques to obtain a robust early-warning system.

Profile

 

To perform this practice-oriented research, the Livestock Technology group of KU Leuven is looking for a highly motivated PhD candidate.

 

 

If you:

 

    hold a MSc degree (with minimal distinction and obtained in the last 3 years at a university in the EEA) in biosciences, bioscience-engineering, engineering (technology) or equivalent

    are an hands-on engineer with a creative, critical, analytical and innovative mindset

    have excellent oral and written communication skills in English

    are eager to work in a multidisciplinary team of national and international researchers and learn and explore innovative technologies

    have strong interest in dairy farming, sensor technology, data processing and scientific research

    are interested in building a career in IoT and data science

 

 

Then you are THE candidate we are looking for and we would like you to apply for this interesting PhD position.

 

Experience with scientific data-processing software (such as Matlab, Python, R, C, Labview or equal) is a plus.

Offer

 

We offer a fulltime PhD position for 4 years, starting on the 1st September 2019 or sooner. Our young, dynamic and multidisciplinary team will support you in all aspects to successfully obtain a PhD degree and a proper scientific training at a top-ranked university. You will work closely together with the research center for dairy production “Hooibeekhoeve” and the milking technology industry. You will have opportunities to participate at national and international meetings, establish your own network and gain experience in transferal skills.

Interested?

For more information please contact Prof. dr. ir. Ben Aernouts, tel.: +32 14 72 13 64, mail: ben.aernouts@kuleuven.be.

You can apply for this job no later than July 31, 2019 via the online application tool

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.


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