Quality Evaluation of Thirteen Geographical Populations of Lycium chinense Using Quantitative Analysis of Nutrients and Bioactive Components

Abstract

Lycium chinense Mill. is an important medicinal and edible perennial plant that has been developed as a popular vegetable and healthcare tea in southern China in recent years. In this study, we evaluated the nutritional quality of 13 different geographical L. chinense populations through a common-garden experiment. There were significant differences (P<0.05) in active components and nutrient elements among the populations. Principal component and clustering analyses showed that populations in the central China showed better integrated quality than the other populations; populations in southern China also showed good prospects for further development, having special characteristics such as high contents of amino acids, total flavonoids, and chlorogenic acid. Moreover, all the populations had much higher contents than most vegetables of flavonoids and of the mineral elements Fe, Se, Mn, and K. These results provide important information required for the development of L. chinense germplasm resources and to ensure the sustainable utilization of L. chinense.

Transcriptome analysis reveals genes related to the synthesis and metabolism of cell wall polysaccharides in goji berry (Lycium barbarum L.) from various regions

“…The total sugar content was determined using a titration method, 22 with a few modifications. For this, 2.0 g of goji berries samples and 200 mL water were placed into a 250‐mL volumetric flask and extracted for 30 min at 80 °C.…”

Phenotype correlation analysis and excellent germplasm screening of herb Bletilla Rchb. f. based on comprehensive evaluation from thirty-three geographic populations

“…The phenol–sulphuric acid method was used to analyze polysaccharide content as described previously with minor modifications [ 23 ]. Approximately 2 g of dried pseudobulb powder was treated with 50 mL H 2 O for 120 min at 100 °C twice using the conventional heating reflux extraction method.…”

“…Common garden experiments retaining the same cultural environment can be used to analyze phenotypic variation among different populations to eliminate phenotypic variation induced by environmental factors and have become an important means of resource evaluation [ 20 – 22 ]. Through the collection of wild resources for common garden cultivation, quality evaluation was performed to determine the high-quality resources in the tested varieties and has been widely used in many medicinal plants, such as Epimedium sagittatum and Lycium chinense [ 22 , 23 ]. Gray relation analysis (GRA) is a multifactor statistical analysis method that includes dimensionless processing, correlation coefficient calculation, correlation degree and relative correlation degree calculation and is widely used in the comprehensive evaluation of the quality of medicinal materials [ 24 ].…”

Phenotype - Chemotype Correlation of the Herb Bletilla Rchb. f. Based on a Comprehensive Evaluation of Thirty- Three Geographic Populations

“…The phenol-sulphuric acid method was used to analyze polysaccharide content as described previously with minor modi cations [23]. Approximately 2 g of dried pseudobulb powder was treated with 50 mL H 2 O for 120 min at 100 o C twice using the conventional heating re ux extraction method.…”

“…Common garden experiments retaining the same cultural environment can be used to analyze phenotypic variation among different populations to eliminate phenotypic variation induced by environmental factors and have become an important means of resource evaluation [20][21][22]. Through the collection of wild resources for common garden cultivation, quality evaluation was performed to determine the high-quality resources in the tested varieties and has been widely used in many medicinal plants, such as Epimedium sagittatum and Lycium chinense [22,23]. Gray relation analysis (GRA) is a multifactor statistical analysis method that includes dimensionless processing, correlation coe cient calculation, correlation degree and relative correlation degree calculation and is widely used in the comprehensive evaluation of the quality of medicinal materials [24].…”