Bio: Giorgia Danielato is an academic researcher from University of Avignon. The author has contributed to research in topics: Lycium & Lycium chinense. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.
TL;DR: Optimal analytical methods for metabolic profiling in the fruits of three Solanaceae species, reported here for the first time to the authors' knowledge, revealed compounds discriminating the Lycium species were more abundant in Lycium chinense, whereas Lycium barbarum accumulated more lycibarbarphenylpropanoids A-B, coumaric acid, fructose and glucose.
Abstract: Metabolic profile is a key component of fruit quality, which is a challenge to study due to great compound diversity, especially in species with high nutritional value. This study presents optimized analytical methods for metabolic profiling in the fruits of three Solanaceae species: Lycium barbarum, Lycium chinense and Solanumlycopersicum. It includes the most important chemical classes involved in nutrition and taste, i.e., carotenoids, phenolic compounds and primary compounds. Emphasis has been placed on the systematic achievement of good extraction yields, sample stability, and high response linearity using common LC-ESI-TQ-MS and GC-EI-MS apparatuses. A set of 13 carotenoids, 46 phenolic compounds and 67 primary compounds were profiled in fruit samples. Chemometrics revealed metabolic markers discriminating Lycium and Solanum fruits but also Lycium barbarum and Lycium chinense fruits and the effect of the crop environment. Typical tomato markers were found to be lycopene, carotene, glutamate and GABA, while lycibarbarphenylpropanoids and zeaxanthin esters characterized goji (Lycium spp.) fruits. Among the compounds discriminating the Lycium species, reported here for the first time to our knowledge, chlorogenic acids, asparagine and quinic acid were more abundant in Lycium chinense, whereas Lycium barbarum accumulated more lycibarbarphenylpropanoids A-B, coumaric acid, fructose and glucose.
TL;DR: In this article, the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases is explored.
Abstract: During the past decade metabolomics has emerged as one of the fastest developing branches of "-omics" technologies. Metabolomics involves documentation, identification, and quantification of metabolites through modern analytical platforms in various biological systems. Advanced analytical tools, such as gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectroscopy (LC/MS), and non-destructive nuclear magnetic resonance (NMR) spectroscopy, have facilitated metabolite profiling of complex biological matrices. Metabolomics, along with transcriptomics, has an influential role in discovering connections between genetic regulation, metabolite phenotyping and biomarkers identification. Comprehensive metabolite profiling allows integration of the summarized data towards manipulation of biosynthetic pathways, determination of nutritional quality markers, improvement in crop yield, selection of desired metabolites/genes, and their heritability in modern breeding. Along with that, metabolomics is invaluable in predicting the biological activity of medicinal plants, assisting the bioactivity-guided fractionation process and bioactive leads discovery, as well as serving as a tool for quality control and authentication of commercial plant-derived natural products. Metabolomic analysis of human biofluids is implemented in clinical practice to discriminate between physiological and pathological state in humans, to aid early disease biomarker discovery and predict individual response to drug therapy. Thus, metabolomics could be utilized to preserve human health by improving the nutritional quality of crops and accelerating plant-derived bioactive leads discovery through disease diagnostics, or through increasing the therapeutic efficacy of drugs via more personalized approach. Here, we attempt to explore the potential value of metabolite profiling comprising the above-mentioned applications of metabolomics in crop improvement, medicinal plants utilization, and, in the prognosis, diagnosis and management of complex diseases.
TL;DR: In this article , five solvents were applied to the extraction of pigments from nine brown algae, followed by their determination and quantification by HPLC-DAD, showing a maximal value of 11.9 mg of total pigments per gram of dry alga obtained from the ethanolic extracts of H. elongata and U. pinnatifida.
Abstract: Brown algae are ubiquitously distributed in the NW coastline of the Iberian Peninsula, where they stand as an underexploited resource. In this study, five solvents were applied to the extraction of pigments from nine brown algae, followed by their determination and quantification by HPLC-DAD. A total of 13 compounds were detected: Six were identified as chlorophylls, six were classified as xanthophylls, and one compound was reported as a carotene. Fucoxanthin was reported in all extracts, which is the most prominent pigment of these algae. Among them, L. saccharina and U. pinnatifida present the highest concentration of fucoxanthin (4.5–4.7 mg∙g−1 dry weight). Ethanol and acetone were revealed as the most efficient solvents for the extraction of pigments, showing a maximal value of 11.9 mg of total pigments per gram of dry alga obtained from the ethanolic extracts of H. elongata, followed by the acetonic extracts of L. ochroleuca. Indeed, ethanol was also revealed as the most efficient solvent according to its high extraction yield along all species evaluated. Our results supply insights into the pigment composition of brown algae, opening new perspectives on their commercial exploitation by food, pharmaceutical, and cosmeceutical industries.
TL;DR: A nontargeted metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used to find the differential composition between ZNG and NZNG and showed that two sets of combinative biomarkers to distinguish ZNG from NZNG with good sensitivity and specificity.
••24 Feb 2021
TL;DR: The cultivar Amber Sweet (L. chinense) had fruits of which the similarities between biochemical characteristics of different studies genotypes were the lowest, and a distinctive feature of the other tested genotypes was the yellow colour of the fruit.
Abstract: Fruits of Lycium possess therapeutic properties due to which they are used in traditional and folk medicine and can be used as a kind of functional food. The objective of this study was to evaluate the biochemical characterization of Lycium L. (L. barbarum L., L. chinense Mill. and L. truncatum Y. C. Wang) fruits for 16 cultivars and varieties from the collections in the M. M. Gryshko National Botanical Garden of NAS of Ukraine (Kyiv). This study was aimed at determining the concentration of nutrients in the Lycium fruits. Individual genotypes of three Lycium species: L. barbarum, L.chinense, and L. truncatum, differed in such features as the content of dry matter, sugars, vitamin C, β-carotene, acidity, and tannins in the fruit. Fruits of Lycium spp. are a valuable source of nutrients such as vitamin C (4.38–121.0 mg 100g–1 FW), β-carotene content (1.45–5.52%), and tannin (0.12–1.34%). The sugar content (13.83–20.87%) and acidity of the fruit (0.23–4.62%) meet the consumers' requirements for fresh fruit. The cultivar Amber Sweet (L. chinense) had fruits of which the similarities between biochemical characteristics of different studies genotypes were the lowest. The cv. Amber Sweet was characterized by fruit with high sugar content, very high vitamin C content, average acid content, low tannins and β-carotene content, and the lowest dry matter content. Furthermore, a distinctive feature of the other tested genotypes was the yellow colour of the fruit. The data obtained can be used for further selective work.