Dr. Paliwal’s research focuses on providing safe and healthy food to humans and livestock. His areas of expertise include development of hardware and software techniques related to machine-vision, vibrational spectroscopy, and data mining methods as they relate to quality assessment of cereal grains, food products, and animal feed.
Near-infrared spectroscopy (NIRS) provides a fast, non-destructive, and accurate assessment of components such as protein, moisture, fat, starch, and ash of cereal grains. Machine vision can quantify visual characteristics of grains to identify various grain types and contaminants present. The team is working on finding ways to integrate the two techniques to develop a comprehensive quality assessment model.
Another project involves using nondestructive sensing devices to rapidly sort high quality fruits, such as strawberries which are prone to spoilage and bruising. NIR hyperspectral imaging techniques can be used for predicting firmness and bruised spots. Once established, the same technology can be used to assess quality of other fruits and vegetables.