Study on the salt-processing technology of Rosa laevigata and its HPLC fingerprints and chromaticity values before and after salt-processing / 中国药房
China Pharmacy
; (12): 861-866, 2022.
Article
in Zh
| WPRIM
| ID: wpr-923194
Responsible library:
WPRO
ABSTRACT
OBJECTIV E To optimize the s alt-processing technology of Rosa laevigata ,and to study high performance liquid chromatography(HPLC)fingerprints and chromaticity values of R. laevigata before and after salt-processing. METHODS The comprehensive scoring method was adopted to optimize the salt-processing technology of R. laevigata using appearance character , moisture and polysaccharide content as index. Fingerprints were established by HPLC method before and after salt-processing ,and chromaticity values (L*,a*,b*)of the powder before and after salt-processing were determined. The multivariate statistical analysis was carried out for raw product and salt-processing product of R. laevigata by using common peak areas and chromaticity values as index. RESULTS The optimal salt-processing technology of R. laevigata was to mix it with appropriate amount of salt water ,place them in the preheated frying wok at 140 ℃,fry them for 25 min,and rotate frying wok 20 times/min. Ten common peaks were calibrated by HPLC fingerprints before and after salt-processing ,and 3 components were identified ,such as gallic acid ,catechin and ellagic acid. The chromaticity values L*,b* and E* changed significantly after salt-processing. The multivariate statistical analysis method could distinguish raw products and salt-processing products into two categories ,in which peaks 1,5,6 and 10 and chromaticity values b* and E* were important characteristic factors. CONCLUSIONS The optimized salt-processing technology is stable and reliable ,and the established fingerprint has good repeatability and stability. Fingerprint and chromaticity values combined with multivariate statistical analysis can provide reference for the identification and quality analysis of R. laevigata before and after salt-processing.
Full text:
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Index:
WPRIM
Type of study:
Prognostic_studies
Language:
Zh
Journal:
China Pharmacy
Year:
2022
Type:
Article