Abstract: Polyphenol oxidase (PPO) is the main cause of enzymatic browning of sweet potato. The commonly used method for detecting PPO activity is complicated, so it is of great significance to establish a simple and fast method for the detection of PPO activity. In the present study, the browning process of sweet potato slices were videotaped by a cell phone, and the changes of RGB values in these videos were extracted. The PPO activity prediction model was also be established. The results showed that the change of R value (ΔR) from 0 to 30 s was highly positive correlated with PPO activity (correlation coefficient was 0.946), and the change of G and B value (ΔG and ΔB) was moderately positive correlated with PPO activity (correlation coefficient was 0.799 and 0.620, respectively). Multivariate linear regression model was used to fit the relationship between ΔR, ΔG, ΔB and PPO activity. The coefficient of determination (R2) of the model reached 0.903, the predicted correlation coefficients (rp), root mean square error of prediction (RMSEP) and standard deviation ratio (SDR) of the model were 0.956, 2.079 and 3.459, respectively. The results indicated that the methodology developed here is feasible to predict PPO activity of sweet potato by video and digital image colorimetry.
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