Application of Near-Infrared Spectroscopy to Rapidly Classify the Chinese Quince Fruits from Different Habitats

Author:

Diao Songfeng12ORCID,Tang Xiaoqian3,Huang Lin1,Li Yanjie2,Fan Xiongfei1,Shao Wenhao2ORCID

Affiliation:

1. Research Institute of Non-Timber Forestry, Chinese Academy of Forestry, Key Laboratory of Non-Timber Forest Germplasm Enhancement & Utilization of National Forestry and Grassland Administration, Zhengzhou 450003, Henan, China

2. Institute of Subtropical Forestry Research of Chinese Academy of Forestry, Key Laboratory of Subtropical Tree Breeding and Cultivation of State Forestry and Grassland Administration, Key Laboratory of Tree Breeding of Zhejiang Province, Hangzhou 311400, Zhejiang, China

3. Science and Technology Management Department, Chinese Academy of Forestry, Beijing 100091, China

Abstract

The ecological habitats of Chinese quince (Chaenomeles speciosa Nakai) fruits affect their phenotype. Currently, limited or no rapid method exists for classifying Chinese quince fruit from different ecosystems. This study developed a partial least squares discriminant analysis (PLS-DA) classification model to effectively and nondestructively classify 663 Chinese quince fruit samples from six environments in 2020. PLS-DA models and other variable selection approaches were used in this study. The near-infrared spectroscopy (NIRs) absorption spectra of raw Chinese quince fruit samples from six habitats showed a similar shape. The spectra of each environment showed little variance. The raw fruit spectra varied significantly among habitat categories after the first derivative preprocessing phase. The uninformative variable elimination (UVE) variable selection approach had greater calibration and validation set specificity of 0.93 and 0.98. This study found the best classification specificity using the UVE variable selection approach compared to other methods including the PLS-DA model without variable selection. The UVE approach improved Yunnan habitat categorization specificity from 86% to 88% when integrated with PLS-DA. Additionally, the validation set for quinces originating from Anhui, Chongqing, Hubei, Shandong, and Zhejiang achieved an ideal classification score of 100%. The findings of the study indicated that PLS-DA can serve as an alternative approach for classifying the habitats of Chinese quince fruits. When used in conjunction with other methods, this technique can assist researchers, scientists, and industry professionals in identifying the main factors responsible for significant variations in the habitats, composition, and quality of Chinese quince fruits.

Funder

National Science and Technology Basic Resources Survey Program of China

Publisher

Hindawi Limited

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