The aim of this study was to explore the relationship between mobile phone digital images and β-carotene content in sweet potato. A smart phone was used to collect the image of sweet potato slices. Moreover, the relationship between the RGB information of the images and the content of β-carotene in sweet potato was studied, and predict models were calibrated. The results showed that the content of β-carotene in sweet potato had a strong negative correlation with green (G) value, and a moderate negative correlation with blue (B) value. There was no correlation between β-carotene content and red (R) value of sweet potato slice images. The logarithmic function was used to fit the relationship between G value and β-carotene content. The coefficient of determination (R2) of the model reached 0.947, the predicted correlation coefficients (rp), root mean square error of prediction (RMSEP) and standard deviation ratio (SDR) of the model were 0.983, 0.819 and 5.269, respectively. Overall, digital images of mobile phone can reflect the differences of β -carotene content in sweet potato, and the RGB information of digital image can accurately estimate the β-carotene content of sweet potato, which provides a new idea for rapid detection of sweet potato quality.
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