Major Research Programs

within the Institute of Food Science and Engineering

On-Line Vision System for Fruit Defect Detection

     A project under the direction of Dr. Yang Tao applied intelligent system techniques using camera vision in conjunction with robotics to inspect and remove defective fruit on packing lines.  This research will not only liberate people from the traditional hand-sorting of fruit but will also improve product quality.

Intelligent system techniques 

use camera vision and robotics 

to detect and remove 

defective fruit 

     One of the persistent problems involved in the technology of automated machine vision defect sorting lies in the discrimination between true defects and the stem-end/calyx of fruit.  A novel method was developed to solve this problem, resulting in a 99% recognition rate for stem-ends and calyxes.  Experimental results showed the effectiveness of the proposed method for large-scale multiple-line processing of massive numbers of fruit such as apples.

     The effect of raw product factors on processing of potatoes into chips and the sensory quality of potato chips was studied by Dr. Luke Howard.  The relationship between physicochemical factors in raw tubers and ultimate potato chip quality was explored.  The results can be used to screen raw tubers for quality, allowing for a more consistent processed product.  Information developed will also be useful in selecting new breeding lines with improved processing traits.