A Novel Method for Quality Evaluation of Gardeniae fructus Praeparatus during Heat Processing Based on Sensory Characteristics and Chemical Compositions

Abstract

The intrinsic chemical components and sensory characteristics of Gardeniae fructus Praeparatus (GFP) directly reflect its quality and subsequently, affect its clinical curative effect. However, there is little research on the correlation between the appearance traits and chemical compositions of GFP during heat processing. In this study, the major components of five typical processed decoction pieces of GFP were determined. With the deepening of processing, the contents of geniposidic acid and 5-HMF gradually increased, while the contents of deacetyl-asperulosidic acid methyl ester, gardenoside, and two pigments declined. Moreover, the electronic eye, electronic tongue, and electronic nose were applied to quantify GFP’s sensory properties. It was found that the chroma values showed a downward trend during the processing of GFP. The results of odor showed that ammonia, alkenes, hydrogen, and aromatic compounds were the material base for aroma characteristics. Complex bitterness in GF was more obvious than that in other GFP processed products. Furthermore, one mathematical model was established to evaluate the correlation between the sensory characteristics and chemical composition of GFP during five different stages. A cluster analysis and neural network analysis contributed to recognizing the processing stage of GFP. This study provided an alternative method for the exterior and interior correlation-based quality evaluation of herbs.

Application of digital-intelligence technology in the processing of Chinese materia medica

“… Xu et al (2015) compared the raw betel nut with its processed products of stir-frying yellow, stir-frying coke and stir-frying charcoal, and found that the contents of 5-HMF and arecoline in the three processed products were significantly different and closely related to the levels obtained by electronic nose and electronic tongue. Zheng et al (2022) used cluster analysis and Artificial neural network analysis (ANN) to better identify gardenia with various processing degrees. For the determination of the end point of processing, the color difference and distribution in the image may be used to determine the degree of stir-frying and cooking of the drug, so that the processing system may determine whether to use partial tumbling, or to end the processing when the decoction pieces reach the optimal efficacy; such processing system may avoid improper or excessive processing ( Lin et al, 2021 ).…”