Foods

Since different geographical origins of black beans have different nutritional and economic values, their classification is of great significance in the field of agriculture. Therefore, this study aims to develop a classification model for black bean origin identification based on chemometric analysis of near-infrared (NIR) spectral data. Due to the overlap and complex distribution characteristics of raw NIR spectral data, traditional linear discriminant analysis algorithms are unable to extract effective discriminative information from them. To overcome these limitations and improve the performance of the algorithms, fuzzy set theory was incorporated into orthogonal linear discriminant analysis (OLDA), and the fuzzy OLDA (FOLDA) was proposed to extract discriminant features from the NIR absorption spectra of black beans. FOLDA enhances sample diversity and better handles noisy data. Furthermore, by combining FOLDA with a linear kernel function, the kernel FOLDA (KFOLDA) algorithm was proposed to address the challenge of linear algorithms in processing nonlinear data. KFOLDA not only effectively captures and processes nonlinear information within the data but also significantly improves the model’s classification accuracy. The experimental results show that the K-nearest neighbor (KNN) classifier achieved classification accuracies of 86.4% and 95.5% for FOLDA and KFOLDA, respectively. Thus, the proposed model demonstrates satisfactory classification accuracy and performance metrics for distinguishing different geographical origins of black beans.

To elucidate the molecular basis of the functional deterioration of Qula-derived casein, proteomic analysis was conducted, and the protein composition, structural characteristics, and functional properties of imported casein, fresh yak milk casein, and Qula-derived casein were systematically compared. Structural characterization was performed by spectroscopic and microscopic analyses, and physicochemical properties were measured in parallel. Qula-derived casein contained higher proportions of αs1-casein than imported casein and β-casein than both imported and fresh yak milk casein, but a lower proportion of κ-casein than either sample. Relative to fresh yak milk casein, Qula-derived casein showed decreases of 31.8% and 12.3% in α-helix and β-sheet contents, respectively, accompanied by a 22.3% increase in random coil content. Its microstructure also changed from a loose, porous morphology to dense, block-like aggregates. Accordingly, its emulsifying activity index, emulsion stability index, solubility, and surface hydrophobicity decreased to 29.3 m²/g, 23 min, 0.6%, and 199, respectively, representing reductions of 36.7%, 25.8%, 33.3%, and 32.1% compared with fresh yak milk casein. These findings indicate that alterations in casein isoform composition are associated with protein unfolding, aggregation, and the deterioration of functional properties during Qula processing. The new knowledge of this study lies in providing insight into the molecular mechanism by which traditional Qula processing may induce casein subtype changes, unfolding, and aggregation, and in describing a possible association between decreased κ-casein abundance and impaired functionality. These findings support the value-added utilization of Qula-derived casein and the optimization of traditional processing.

Hyperlipidemia is a widespread metabolic disease that triggers abnormal lipid accumulation. Plant polyphenols possess great potential for lipid metabolism regulation. Small-leaved kuding tea (Ligustrum robustum Roxb. Blume, SLKDT) is abundant in polyphenols with proven hypolipidemic activity, whereas its key active constituents and molecular targets remain unclear. This study aimed to identify the key active components and core targets responsible for the lipid-lowering effects of SLKDT polyphenols. Response surface methodology (RSM) was employed to optimize the extraction process of SLKDT polyphenols. In vitro cell experiments were performed to verify the lipid-lowering effect of SLKDT polyphenols, while the obtained polyphenols were further qualitatively characterized via LC-MS/MS. Furthermore, network pharmacology prediction combined with molecular docking was used to screen the key bioactive compounds and their target proteins associated with lipid metabolism regulation. Under the optimal extraction conditions (43% ethanol concentration, ultrasound time of 40 min, solid-to-liquid ratio of 1:56 g/mL, and ultrasonic temperature of 57 °C), the yield of polyphenols from SLKDT was 131.88 mg/g. In vitro experiments confirmed that SLKDT polyphenols significantly reduced intracellular lipid accumulation in HepG2 cells, increased the activities of antioxidant enzymes including GSH-PX, CAT, and T-SOD, and decreased MDA content. Furthermore, SLKDT polyphenols markedly downregulated the expression of lipid synthesis-related genes, including ACC, HMGCR, SREBP-1c, and FASN, while upregulating CYP7A1 expression. A total of 88 compounds were Preliminary identified by LC-MS/MS, mainly including glycosides, flavonoids and phenolic acids. Network pharmacology analysis revealed that chrysin, 6-demethoxytangeretin, bavachinin, isobavachin, and bavachalcone were the core components mediating the lipid-lowering activity of SLKDT polyphenols, with target proteins including TP53, STAT3, AKT1, HSP90AA1, and EGFR. This study elucidates the key components and critical targets underlying the lipid-lowering effects of SLKDT polyphenols, providing experimental evidence and theoretical support for the development of SLKDT-derived products and natural lipid-lowering agents.