Study of Nondestructive Testing of Nanguo Pear Quality Using Vis-NIR Spectroscopy

Abstract

When evaluating fruit, such as the Nanguo pear, ensuring high quality of the product is a top priority. The quality of a Nanguo pear will directly affect its appearance, taste, and commodity value. Currently, most of the quality detection methods of Nanguo pears are destructive. In this work, nondestructive testing methods for the internal and external quality of the Nanguo pear were studied. First, the spectral curves of the Nanguo pear were collected to establish the internal comprehensive quality indicators. Second, the successive projection algorithm was used to extract the spectral characteristics of samples. Based on the gray level co-occurrence matrix, texture features of the sample image were extracted. Finally, the model was established by fusing spectral and image features together, and good modeling results were achieved. The internal and external quality of the Nanguo pear were detected simultaneously. The accuracy of the external quality assessment was 97.14%. For the internal quality prediction model, the correction set R2c and RMSEC are 0.959 and 0.483, respectively, and the prediction set R2P and RMSEP are 0.920 and 0.615, respectively. It provides a theoretical basis for the development of an online nondestructive testing system for fruit.