Profile Website : https://farmworx.nl
Suresh Neethirajan is an Associate Professor in the Animal Sciences department, Wageningen University & Research, The Netherlands. His technical background is in bioengineering with sensor technologies expertise, and he is focused on bringing solutions to improving animal health and welfare through enabling digital technologies and Artificial Intelligence.
Suresh obtained his PhD cum laude at the University of Manitoba, Canada. From 2011 to 2018, Suresh was an Associate Professor in the Biological Engineering program of the University of Guelph, Canada.
Non-Invasive Rapid Sex Detection of Incubated Chicken Eggs
(PhD student - Lennard van den Tweel)
Commercially produced chickens serve essentially two purposes: “broilers” for meat and “layers” for table eggs. Layer chickens, bred to mature more slowly, can lay commercial eggs within 16 to 21 weeks after hatching. Male layer chicks do not lay eggs upon reaching maturity and their use is commercially limited. Male chicks - billions a year - are macerated usually within a day of hatching. Besides obvious animal welfare and ethical/societal considerations, (shredded) chick carcasses have limited commercial value. Overall goal of this proposed project is to develop a method for non-invasive determination of the sex of an embryo of chicken egg, using spectroscopy imaging and Artificial Intelligence technologies.
Multiplexed Biomarker Detection in Whole Blood Using Biosensing Platform (Postdoctoral Fellow - Ali Youssef)
As part of the Next Level Animal Sciences (NLAS) program, we are currently developing wearable non-invasive biosensors for livestock applications. Disease prevention and enabling actionable feedback are the drivers for developing wearable sensors and Internet of Things technologies in livestock. Minimally invasive implantable biochip composed of multiplexed sensor arrays for determining various biomarkers in blood along with optical nano photodetectors has the potential to measure the biosensing signals in an integrated wearable device approach.
Measuring Emotions in Farm Animals
Understanding animal emotions is a key to unlocking methods for improving animal welfare. Currently there are no ‘benchmarks’ or any scientific assessments available for measuring and quantifying the emotional responses of farm animals. The overall goal is to combine various imaging (3D, Depth, thermal) and sensor technologies through sensor fusion into efficient systems for monitoring and measuring the animals’ compound expression of emotions, as well as positive & negative indicators of welfare. Through combining affective computing, Artificial Intelligence, bioengineering and applied ethology we aim to address the practical obstacles in the realization of the automatizing emotion recognition in production animals.
Upscaling Real-Time Sensor Data for Monitoring of Production Animals
The goal of this project is to develop innovative approaches to use in-situ data collected via sensors in the livestock farming as input to the application of data technologies.