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Optimization of processing technology for Sophora Japonica based on correlation analysis between multi-component control and color correlation analysis
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Chinese Traditional and Herbal Drugs | 2026, 57(15) : 5859 - 5873
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Chinese Traditional and Herbal Drugs | 2026, 57(15): 5859-5873
Optimization of processing technology for Sophora Japonica based on correlation analysis between multi-component control and color correlation analysis
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MENG Fanmiao, LI Ning, ZHANG Zezhao, WANG Xinguo, NIU Liying
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doi: 10.7501/j.issn.0253-2670.2026.15.008
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Objective To optimize the optimal processing methods for two different preparations of Huaimi (Sophorae Japonicae, SJ) and establish a method for determining the content of marker components and analyzing their correlation with color values using UPLC. Methods UPLC was employed to determine nine components in SJ (5-hydroxymethylfurfural, protocatechuic acid, rutin, isoquercitrin, quercetin, kaempferol-3-O-rutinoside, narcissin, kaempferol, and isorhamnetin) and alcohol-soluble extract content as evaluation indicators. A single-factor experiment combined with Box-Behnken design-response surface methodology (BBD-RSM) was employed to investigate three factors: roasting power, roasting time, and feedstock quantity. The weighting coefficient of the 10 indicators was calculated using the criteria importance through inter-criteria correlation (CRITIC) method. Both approaches were integrated to analyze and optimize the processing techniques for the two prepared forms of SJ. The IRIS electronic eye was employed to measure color changes in SJ at different processing levels. SPSS 20.0 and Origin 2024 software were used to analyze the correlation between color and indicator components. Results The optimal processing conditions for stir-fried SJ were determined as frying power 900 W, 5 min processing time, and 115 g batch size. For charred SJ, the optimal conditions were frying power 1 600 W, 3 min processing time, and 100 g batch size. Three batches of samples were prepared for validation, yielding average composite scores of 67.33 and 78.98 with RSD of 2.29% and 0.70%, respectively. These values closely matched predicted values, indicating process stability. Correlation analysis between color values and nine components revealed that both L* and b* values showed significant positive correlations with rutin, kaempferol 3-O-rutinoside, and narcissin, while exhibiting significant negative correlations with kaempferol, quercetin, and isorhamnetin. The a* value demonstrated significant positive correlations with protocatechuic acid, isoquercitrin, quercetin, kaempferol, and isorhamnetin, indicating a correlation between color and changes in internal components of SJ. Conclusion The processing methods for stir-fried SJ and charred SJ optimized through BBD-RSM and CRITIC weighting are stable and feasible. Changes in intrinsic components during processing showed significant correlation with color values, providing a simple and intuitive basis for assessing the degree of processing and the relationship between intrinsic component changes in stir-fried SJ and charred SJ, and offering reference for their quality evaluation and clinical application.
Sophorae Japonicae  /  processing techniques  /  Box-Behnken design-response surface methodology  /  CRITIC weighting method  /  intelligent sensory technology  /  electronic eye  /  colorimetric values  /  5-hydroxymethylfurfural  /  protocatechuic acid  /  rutin  /  isoquercitrin  /  quercetin  /  kaempferol-3-O-rutinoside  /  narcissin  /  kaempferide  /  isorhamnetin  /  correlation analysis
MENG Fanmiao, LI Ning, ZHANG Zezhao, WANG Xinguo, NIU Liying. Optimization of processing technology for Sophora Japonica based on correlation analysis between multi-component control and color correlation analysis[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (15) : 5859 -5873 . DOI: 10.7501/j.issn.0253-2670.2026.15.008
Year 2026 volume 57 Issue 15
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doi: 10.7501/j.issn.0253-2670.2026.15.008
  • Receive Date:2026-02-16
  • Online Date:2026-09-09
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  • Received:2026-02-16
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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