Nondestructive Testing of Pear Based on Fourier Near-Infrared Spectroscopy.

Abstract

Fourier transform near-infrared (FT-NIR) spectroscopy is a nondestructive, rapid, real-time analysis of technical detection methods with an important reference value for producers and consumers. In this study, the feasibility of using FT-NIR spectroscopy for the rapid quantitative analysis and qualitative analysis of 'Zaosu' and 'Dangshansuli' pears is explored. The quantitative model was established by partial least squares (PLS) regression combined with cross-validation based on the spectral data of 340 pear fresh fruits and synchronized with the reference values determined by conventional assays. Furthermore, NIR spectroscopy combined with cluster analysis was used to identify varieties of 'Zaosu' and 'Dangshansuli'. As a result, the model developed using FT-NIR spectroscopy gave the best results for the prediction models of soluble solid content (SSC) and titratable acidity (TA) of 'Dangshansuli' (residual prediction deviation, RPD: 3.272 and 2.239), which were better than those developed for 'Zaosu' SSC and TA modeling (RPD: 1.407 and 1.471). The results also showed that the variety identification of 'Zaosu' and 'Dangshansuli' could be carried out based on FT-NIR spectroscopy, and the discrimination accuracy was 100%. Overall, FT-NIR spectroscopy is a good tool for rapid and nondestructive analysis of the internal quality and variety identification of fresh pears.

Plant phenotyping relevance

FT-NIR分光法を用いて生果実の可溶性固形分・滴定酸度を非破壊推定し、交差検証と精度評価を行っており、植物器官の品質形質取得法が研究の中心である。

Code and data availability

The paper reports FT-NIR spectroscopy of pears with PLS and cluster analysis, but the Data Availability Statement explicitly says no new data were created or shared, and no public dataset, spectral data, code, or model repository is provided. Analysis was done in proprietary OPUS 5.5 software with no author code URL.

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