An improvement of far-infrared drying for ginger slices with computer vision and fuzzy logic control

In this study, an intelligent far-infrared drying system was developed whose output power could be adjusted in-line by computer vision and fuzzy logic controller. Ginger slices were first dried at four constant temperatures of 50 degrees C, 60 degrees C, 70 degrees C, and 80 degrees C. The images of ginger slices were captured through the top camera during the drying process. By extracting and analyzing the image features, two fuzzy logic control strategies assisted with computer vision were developed that could suppress color changes and improve product quality, including one-stage and three-stage control. The Delta E (color difference) and BI/BI0 (browning index of drying samples/browning index of fresh samples) signals as the input parameters were fed into the fuzzy logic controller for automatic adjustment of the output temperature. The results of the far-infrared drying with constant temperatures for ginger slices showed that the 60 degrees C drying was the best choice among the four constant temperatures. However, the Delta E and BI/BI0 of the ginger slices dried with the three-stage fuzzy logic control were lower than those of the 60 degrees C drying, resulting in a higher sensory score among them. In addition, the rehydration rate, water activity and total gingerol content of ginger slices dried with the three-stage fuzzy logic control suggested well accepted quality. Therefore, the stepwise fuzzy logic control can be employed for automatic in-line control to optimize the far-infrared drying process.

Automated summary

An intelligent far-infrared drying system with adjustable output power was developed in this study, utilizing computer vision and fuzzy logic controller. Different constant temperature drying conditions for ginger slices were explored, along with two fuzzy logic control strategies assisted by computer vision to improve product quality.