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Outline
Objective: The study aimed to systematically profile the functional components of non-centrifugal cane sugar of sugarcane (NCS) using a chemomics-based strategy, and to establish a near-infrared (NIR) rapid detection technique for comprehensive quality grading of NCS. Methods: The potential functional components in NCS were identified and analyzed by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS). The total phenolic acid content was determined by ultraviolet-visible spectrophotometry. Key quality indicators, including sucrose, reducing sugar, total sugar, and loss on drying, were quantified according to industry and national standards. A comprehensive evaluation index (Fq) was introduced, in which weight coefficients for each indicator were optimally assigned based on their deviation from the mean of a large sample set, enabling integrated quality assessment of NCS. Results: A total of 21 major chemical components were identified in NCS, among which 16 were phenolic acids, primarily including citric acid, vanillic acid, syringic acid, p-hydroxybenzoic acid, and chlorogenic acid. Key indicators of 76 batches of samples were determined, and calibration models between these indicators and corresponding near-infrared spectral data were established. The determination coefficients (R2cal) of the prediction models for sucrose, reducing sugars, total phenolic acids, and loss on drying were 0.867, 0.900, 0.938, and 0.981, respectively, all exceeding 0.85. The root mean square errors of cross-validation (RMSECV) were 1.06, 1.01, 0.0245, and 0.342, respectively, indicating satisfactory model fitting. Quality classification of the samples was performed based on the normal distribution of the Fq value. Experimental validation demonstrated that high-quality samples exhibited superior antioxidant activity compared to low-quality samples, confirming the rationality of the established quality evaluation system. Conclusion: The proposed method incorporates functional component analysis into the current regulatory framework and achieves comprehensive quality evaluation through NIR rapid detection, providing a practical approach for rapid efficacy assessment of NCS.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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