Evaluation of a vat wall-mounted image capture system using image processing techniques to monitor curd moisture during syneresis with temperature treatments

The objective of this study was to evaluate a vat wall-mounted image capture system with a range of image processing techniques (threshold, first order and second order grey level statistics and fractal dimension) to monitor curd moisture content during syneresis with a range of temperature treatments. Milk was renneted using three temperature treatments (32 °C throughout, a cooking step from 32 to 38 °C and 38 °C throughout). Prediction models were evaluated in term of fit to reference measurements on samples of curd at 10 min intervals. The best fitting model was based on the threshold technique giving a standard error of prediction (SEP) = 1.06 g/100 g and correlation coefficient (R) = 0.90. These results demonstrated that the threshold image processing technique was the most useful in this study and showed adequate potential to monitor syneresis and predict curd moisture which influences the final texture of cheese.