Feature Wavelength Selection of Three-Dimensional Fluorescence Data of Tomato Storage Room Gas Based on Wavelet Packet Decomposition for Early Warning of Its Spoilage

doi:10.7506/spkx1002-6630-20211103-026

Abstract

Abstract: In order to realize quality monitoring and spoilage early warning of tomatoes during storage based on three-dimensional (3D) fluorescence information of the storage room gas, a strategy for selecting feature wavelengths based on wavelet packet decomposition was proposed. Firstly, Rayleigh scattering removal and Savitzky-Golay (SG) smoothing were carried out on the original data to eliminate the noise interference and the background emission spectrum without fluorescence information. Secondly, the emission spectrum corresponding to each excitation wavelength was decomposed by the wavelet packet method and the feature excitation wavelengths were selected by the energy of the lowest frequency band combined with its proportion in the total energy. Thirdly, the emission spectrum corresponding to each selected feature excitation wavelength was divided into different bands, each band was decomposed by the wavelet packet method, and the feature emission wavelengths were selected by the lowest wavelet packet frequency band energy. Fourthly, considering the different fluorescence information of tomatoes before and after spoilage, the benchmark of tomato spoilage could be determined by the total energy change of the feature excitation wavelengths; at the same time, the same benchmark was obtained by cluster analysis of spectral vectors at the feature emission wavelengths. Fifthly, the feature emission wavelengths were optimized according to the spoilage benchmark to reduce the number of the feature wavelengths and simplify the analysis. Finally, the feature emission wavelengths of the spoilage benchmark date were taken as the benchmark vector to calculate the Mahalanobis distance between it and fluorescence feature vectors before the benchmark date. The results showed that with the advance of storage, the Mahalanobis distance decreased, effectively describing the quality change of tomatoes during storage and ultimately realizing spoilage early warning.

Key words: tomato; three-dimensional fluorescence; wavelet packet energy; cluster analysis; spoilage benchmark; Mahalanobis distance

CLC Number:

TS205.9

LI Jianmeng, YIN Yong, YU Huichun, YUAN Yunxia, LI Ying. Feature Wavelength Selection of Three-Dimensional Fluorescence Data of Tomato Storage Room Gas Based on Wavelet Packet Decomposition for Early Warning of Its Spoilage[J]. FOOD SCIENCE, 2022, 43(21): 63-69.

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Feature Wavelength Selection of Three-Dimensional Fluorescence Data of Tomato Storage Room Gas Based on Wavelet Packet Decomposition for Early Warning of Its Spoilage

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