Analysis and detection of decayed blueberry by low field nuclear magnetic resonance and imaging
Qiao Shicheng, Tian Youwen, Song Ping, He Kuan and Song Shiyuan
Postharvest Biology and Technology, Volume 156, October 2019, 110951
2019
บทคัดย่อ
Decay is a major cause of quality loss and food safety concerns for blueberry fruit. Low-field nuclear magnetic resonance (LF-NMR) has been used to analyze and detect decayed blueberry fruit. According to NMR relaxation analysis, transverse relaxation time (T21, T22, T23) of decayed fruit increased to different degrees, while signal amplitude (A21, A22, A23) decreased to different degrees. Six relaxation features were input into BPNN model to identify the decay classes of fruit. The identification accuracy of training set was 86.7%, and that of the validation set was 90%. According to magnetic resonance imaging (MRI), twice threshold segmentation algorithm was proposed to segment the decayed region with dark color. A total of 15 features were extracted from gray histogram, gray level co-occurrence matrix (GLCM) and gray level-gradient co-occurrence matrix (GGCM) of the image for correlation analysis. Five features were then input into a back propagation neural network (BPNN) model. The identification accuracy of training set was 92.2%, and that of the validation set was 83.3%. Finally, 11 variables, including transverse relaxation features and image features, were input into the BPNN model. The identification accuracy of training set was 98.8%, and that of the validation set was 94.2%, which showed the highest identification accuracy. The results showed that LF-NMR and MRI are suitable for analyzing and detecting the decay disease of fruit, which provides a theoretical basis for nondestructive detection of fruit disease.