Journal of Food Processing & Technology

Excellence in grains, seeds, and beans sorting for development of novel foodproducts and for rapid inspection with the QSorter Explorer Robot

3^rd International Conference and Exhibition on Food Processing & Technology

July 21-23, 2014 Hampton Inn Tropicana, Las Vegas, USA

Francesco Dell?Endice

Scientific Tracks Abstracts: J Food Process Technol

Abstract:

The consumer preferences for certain food products strongly depends on the quality ofthe raw materials such as grains and beans, which influence: 1. The sensorial properties of the endproducts 2. The possibility of applying health related claims 3. The overall nutritional value. Today, raw material quality is measured on an average basis and no insight on its variance isavailable: e.g. two lots of wheat grains may have the same average protein content but verydifferent standard deviation. This is due to the fact that there are no high-speed single kernelanalyzers. QualySense team has developed, with the support of the USDA and of Swiss researchlaboratories, the QSorter Explorer robot, a high-speed single kernel analyzer and sorter with amulti-kg-per-hour. The QSorter Explorer transports each kernel at the speed of 50 per second. ANear-Infrared reflectance spectrum between 900 nm and 1700 nm and a color image are takenper each kernel and processed by artificial intelligence algorithms to concurrently measurequality parameters such as biochemical properties (e.g. protein, oil, sugar), physical parameters(e.g. size, shape, color), or defects (e.g. broken, shriveled, infected by diseases). The QSorterExplorer is mainly used to: 4. Develop novel food and drink products sorting kernels based on quality criteria 5. Accelerate manual quality inspection procedures in processing plants To date, some of the successful applications of the QSorter Explorer robot include: ? Identification of other cereals in lots of ?gluten-free? oats. ? Measurement of the ratio between Oleic and Linoleic acids in peanuts. ? Prediction of coffee cup quality from unroasted beans. ? Prediction of baking quality parameters from unprocessed wheat kernels. QualySense is also developing a higher capacity version of the QSorter robot.

Biography :

Francesco Dell?Endice holds a PhD in Spectroscopy from University of Zurich and has abackground in Aerospace Engineering. During his PhD he has been involved in building ahyperspectral camera for the European Space Agency, whose goal was to measure thedistribution of biochemical properties in natural targets such as plants, trees, water and soil froma satellite. In early 2010, he founded QualySense with the mission of bringing biochemicalsorting in the food industry. To date, QualySense has won several prizes and has closed severalprojects with leading food and seed companies worldwide.