Development of a novel approach to determine heating pattern using computer vision and chemical marker (M-2) yield

In this study, a novel approach to determine heating patterns using chemical marker (M-2) yield and computer vision was developed for packaged foods after microwave sterilization. Due to various constraints of temperature measurement devices such as fiber-optic temperature sensors, thermocouples, and infrared sensors, there is a need to develop an accurate and rapid method to determine heating patterns in packaged food trays after microwave sterilization. Yield of a heat sensitive chemical marker (M-2) was used as a coloring agent and digital images of the processed trays were analyzed using a computer vision system. A script in IMAQ vision builder software was written to obtain a 3-D heating pattern for the sterilized trays. Relationship between chemical marker (M-2) yield and cumulative thermal lethality (F0) was also studied. Validation of the locations of cold and hot spots determined by computer vision were performed by fiber-optics temperature measurement sensor. Results show that computer vision in combination with chemical marker M-2 and other accessories can be used as a rapid, accurate and cost efficient tool to specify the location of cold and hot spots after microwave sterilization.