Insights into the quality profile and potential quality markers of Lycium barbarum (goji) berries after Tribolium castaneum infestation

Abstract

This study innovatively integrated multidimensional quality evaluation with UPLC-MS metabolomics to comprehensively elucidate the molecular mechanisms underlying insect-induced quality deterioration and to identify diagnostic markers. The results demonstrated that insect infestation altered color, reduced the content of total flavonoids, total phenolics, six active compounds, and markedly decreased antioxidant capacity (P < 0.05), leading to the quality deterioration. Metabolomic analysis identified 91 differential metabolites (DMs). KEGG pathway enrichment analysis revealed that these DMs were primarily involved in core biological pathways such as amino acid metabolism, carbohydrate metabolism, and energy metabolism. These metabolic disturbances were closely associated with nutrient depletion during insect growth and development, providing molecular-level insights into infestation-induced quality decline. ROC curve analysis further identified 6 Q-markers (uric acid, montanol, sucrose, aesculetin, malic acid, and tryptophan). This study not only systematically elucidated the material basis of infestation-induced quality deterioration, but discovered a panel of specific metabolic markers with early-warning potential.

Keywords: Goji berry; Insect infestation; Metabolomics; Q-marker; Quality.

Fig. 1

Appearance of normal goji samples (N-1 and N-2) and T. castaneums-infested goji samples (TC-1 and TC-2). 1 and 2 represent goji samples collected from Yinchuan, Ningxia, China and Jinghe, Xinjiang, China, respectively.

Fig. 2

Changes of active indicators between normal goji (N-1 and N-2) and T. castaneums-infested goji (TC-1 and TC-2) samples. Total falvonoids (A), total phenolics (B), 6 active compounds (C–H), and antioxidant activities (I–K). ^⁎, P < 0.05; ^⁎⁎, P < 0.01; ^⁎⁎⁎, P < 0.001; ^⁎⁎⁎⁎, P < 0.0001.

Fig. 3

UPLC-MS analysis of goji samples. PCA scores (A, B), volcano plots (C, D), HMDB classifications (E, F), along with the accumulation histograms of the top three metabolite types for goji-1 and goji-2 groups (G, H). KEGG pathway analysis (I, J) for goji-1 and goji-2 groups, respectively. Venn diagram (K) between goji-1 and goji-2 groups. ROC analysis (L) for goji-1 group.

Fig. 3

UPLC-MS analysis of goji samples. PCA scores (A, B), volcano plots (C, D), HMDB classifications (E, F), along with the accumulation histograms of the top three metabolite types for goji-1 and goji-2 groups (G, H). KEGG pathway analysis (I, J) for goji-1 and goji-2 groups, respectively. Venn diagram (K) between goji-1 and goji-2 groups. ROC analysis (L) for goji-1 group.

Fig. 3

UPLC-MS analysis of goji samples. PCA scores (A, B), volcano plots (C, D), HMDB classifications (E, F), along with the accumulation histograms of the top three metabolite types for goji-1 and goji-2 groups (G, H). KEGG pathway analysis (I, J) for goji-1 and goji-2 groups, respectively. Venn diagram (K) between goji-1 and goji-2 groups. ROC analysis (L) for goji-1 group.

Fig. 4

Correlation heat-maps illustrating the relationships among quality indicators (A and B) and between quality indicators and key differential metabolites (C and D) for goji-1 and goji-2 groups. ^⁎, P < 0.05; ^⁎⁎, P < 0.01.