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. 2025 Apr 21;14(8):1434.
doi: 10.3390/foods14081434.

Research on Quality Evaluation of the Seeds of Cichorium glandulosum Boiss. et Huet

Xu Chen  1   2 , Jianshuang Jiang  3 , Fengling Li  2 , Wen Lei  2 , Juan Li  2 , Xiaoting Wang  2 , Ayiben Wenhua  2 , Jingjing Xia  2 , Jiang He  1
Affiliations

Research on Quality Evaluation of the Seeds of Cichorium glandulosum Boiss. et Huet

Xu Chen et al. Foods. .

Abstract

The seeds of Cichorium glandulosum Boiss. et Huet. (CS) are known for various effects. However, the research on the establishment of quality evaluation standards for CS is currently limited. Therefore, this study employed Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS) to analyze the components of CS. Forty-nine compounds were identified through manual analysis and database comparison. The components were then verified using HPLC and standards. Additionally, 19 batches were collected to establish the fingerprint chromatogram. Five major chemical components were selected for subsequent analysis. MIR, combined with three variable selection algorithms and three preprocessing methods, was used to build prediction models. For the three indexes of Chlorogenic Acid, 1,4-Dicaffeoylquinic Acid, and 1,5-Dicaffeoylquinic Acid, the R2 values for both the training set and test set were above 0.9, the RPD values were all greater than 2.5, and the RER values were greater than 10. This indicated that the combination of mid-infrared spectroscopy and chemometrics had excellent model applicability and prediction performance for these three indexes. A quality evaluation system has been initially established, laying a foundation for research on quality evaluation of CS.

Keywords: Cichorium glandulosum Boiss. et Huet.; UHPLC-MS/MS; chemometrics; infrared spectroscopy; quality evaluation.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
26 compounds were identified based on UPLC-MS/MS analysis.
Figure 2
Figure 2
Comparison of HPLC spectra between the CS sample and the standard sample. S1 refers to the first batch of CS, and CK is composed of a mixture of standardized compounds.
Figure 3
Figure 3
The HPLC fingerprint profiles of 19 batches of CS. S1–S19 refers to the batch of CS, and R is composed of a mixture of standardized compounds.
Figure 4
Figure 4
(A) The mid-infrared spectra. (B) The structures of five chemical components.
Figure 5
Figure 5
Mid-infrared model results of chlorogenic acid. (A) R2 result. (B) RPD results. (C) RER results. (D) Optimal model results.
Figure 6
Figure 6
Mid-infrared model results of Aesculin. (A) R2 result. (B) RPD result. (C) RER results. (D) Optimal model results.
Figure 7
Figure 7
Mid-infrared model results of 1,4-dicaffeoylquinic acid. (A) R2 result. (B) RPD result. (C) RER results. (D) Optimal model results.
Figure 8
Figure 8
Mid-infrared model results of Isochlorogenic Acid A. (A) R2 result. (B) RPD result. (C) RER results. (D) Optimal model results.
Figure 9
Figure 9
Mid-infrared model results of 1,5-Dicaffeoylquinic acid. (A) R2 result. (B) RPD result. (C) RER results. (D) Optimal model results.
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