RESUMEN
Lettuce storage time is an important factor affecting the lettuce freshness. To realize the non-destructive, rapid and effective discrimination of lettuce storage time, generalized fuzzy K-harmonic means (GFKHM) clustering was proposed by introducing the pth power of Euclidean distance into fuzzy K-harmonic means (FKHM) clustering to replace the square of Euclidean distance in FKHM, and furthermore GFKHM was applied in the discrimination of lettuce storage time. Sixty fresh lettuce samples were prepared as the research object, and the near infrared reflectance (NIR) spectra of lettuces were collected by Antaris â ¡ near infrared spectrometer with a spectral range of 10 000ï½4 000 cm-1 for three 12-hour detections. Firstly, the 1 557-dimensional NIR spectra were reduced by principal component analysis (PCA) to decrease redundant information. After the first 20 principal components were selected, PCA translated the 1 557-dimensional NIR spectra into the 20-dimensional data. Secondly, linear discriminant analysis (LDA) was used to extract the discriminant information from the 20-dimensional data to improve the clustering accuracy. With the first two discriminant vectors, LDA translated the 20-dimensional data into the two-dimensional data. Finally, the cluster centers from fuzzy C-means clustering (FCM) were set as the initial cluster centers for FKHM and GFKHM and fuzzy membership values of FKHM and GFKHM were calculated to identify lettuce storage time. The experimental results showed that the discrimination accuracy of GFKHM has achieved 92.5% which was higher than that of FKHM. The cluster centers of GFKHM were much closer to the true cluster centers in comparison with FKHM. Furthermore, the convergence of the GFKHM was significantly faster than FKHM. Near infrared spectroscopy coupled with GFKHM, PCA and LDA could cluster NIR spectra of lettuce quickly and correctly, and this provided a fast and nondestructive method for identifying lettuce storage time.
