1
|
Miguel MDG. Chemical and Biological Properties of Three Poorly Studied Species of Lycium Genus-Short Review. Metabolites 2022; 12:1265. [PMID: 36557303 PMCID: PMC9788301 DOI: 10.3390/metabo12121265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/08/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022] Open
Abstract
The genus Lycium belongs to the Solanaceae family and comprises more than 90 species distributed by diverse continents. Lycium barbarum is by far the most studied and has been advertised as a “superfood” with healthy properties. In contrast, there are some Lycium species which have been poorly studied, although used by native populations. L. europaeum, L. intricatum and L. schweinfurthii, found particularly in the Mediterranean region, are examples of scarcely investigated species. The chemical composition and the biological properties of these species were reviewed. The biological properties of L. barbarum fruits are mainly attributed to polysaccharides, particularly complex glycoproteins with different compositions. Studies regarding these metabolites are practically absent in L. europaeum, L. intricatum and L. schweinfurthii. The metabolites isolated and identified belong mainly to polyphenols, fatty acids, polysaccharides, carotenoids, sterols, terpenoids, tocopherols, and alkaloids (L. europaeum); phenolic acids, lignans, flavonoids, polyketides, glycosides, terpenoids, tyramine derivatives among other few compounds (L. schweinfurthii), and esters of phenolic acids, glycosides, fatty acids, terpenoids/phytosterols, among other few compounds (L. intricatum). The biological properties (antioxidant, anti-inflammatory and cytotoxic against some cancer cell lines) found for these species were attributed to some metabolites belonging to those compound groups. Results of the study concluded that investigations concerning L. europaeum, L. intricatum and L. schweinfurthii are scarce, in contrast to L. barbarum.
Collapse
Affiliation(s)
- Maria da Graça Miguel
- Departamento de Química e Farmácia, Mediterranean Institute for Agriculture, Environment and Development, Faculdade de Ciências e Tecnologia, Universidade do Algarve, Campus de Gambelas, 8005-139 Faro, Portugal
| |
Collapse
|
2
|
Li C, Wang Y. Non-Targeted Analytical Technology in Herbal Medicines: Applications, Challenges, and Perspectives. Crit Rev Anal Chem 2022; 54:1951-1970. [PMID: 36409298 DOI: 10.1080/10408347.2022.2148204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Herbal medicines (HMs) have been utilized to prevent and treat human ailments for thousands of years. Especially, HMs have recently played a crucial role in the treatment of COVID-19 in China. However, HMs are susceptible to various factors during harvesting, processing, and marketing, affecting their clinical efficacy. Therefore, it is necessary to conclude a rapid and effective method to study HMs so that they can be used in the clinical setting with maximum medicinal value. Non-targeted analytical technology is a reliable analytical method for studying HMs because of its unique advantages in analyzing unknown components. Based on the extensive literature, the paper summarizes the benefits, limitations, and applicability of non-targeted analytical technology. Moreover, the article describes the application of non-targeted analytical technology in HMs from four aspects: structure analysis, authentication, real-time monitoring, and quality assessment. Finally, the review has prospected the development trend and challenges of non-targeted analytical technology. It can assist HMs industry researchers and engineers select non-targeted analytical technology to analyze HMs' quality and authenticity.
Collapse
Affiliation(s)
- Chaoping Li
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
- College of Traditional Chinese Medicine, Yunnan University of Chinese Medicine, Kunming, China
| | - Yuanzhong Wang
- Medicinal Plants Research Institute, Yunnan Academy of Agricultural Sciences, Kunming, China
| |
Collapse
|
3
|
Fusion of electronic nose and hyperspectral imaging for mutton freshness detection using input-modified convolution neural network. Food Chem 2022; 385:132651. [DOI: 10.1016/j.foodchem.2022.132651] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 02/01/2022] [Accepted: 03/04/2022] [Indexed: 01/19/2023]
|
4
|
Aparecida Plastina Cardoso M, Windson Isidoro Haminiuk C, Pedro AC, de Andrade Arruda Fernandes Fernandes I, Akemi Casagrande Yamato M, Maciel GM, Do Prado IN. Biological Effects of Goji Berry and the Association with New Industrial Applications: A Review. FOOD REVIEWS INTERNATIONAL 2021. [DOI: 10.1080/87559129.2021.2007261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
| | | | - Alessandra Cristina Pedro
- Programa de Pós-Graduação Em Engenharia de Alimentos (Ppgeal), Cep (81531–980), Universidade Federal Do Paraná (UFPR), Curitiba, Brasil
| | | | | | - Giselle Maria Maciel
- Laboratório de Biotecnologia, Universidade Tecnológica Federal Do Paraná (UTFPR), Cep (81280–340), Curitiba, Brasil
| | - Ivanor Nunes Do Prado
- Programa de Pós-Graduação Em Ciência de Alimentos (Ppc), Cep (87020–900), Universidade Estadual de Maringá (UEM), Maringá, Brasil
| |
Collapse
|
5
|
Salo HM, Nguyen N, Alakärppä E, Klavins L, Hykkerud AL, Karppinen K, Jaakola L, Klavins M, Häggman H. Authentication of berries and berry-based food products. Compr Rev Food Sci Food Saf 2021; 20:5197-5225. [PMID: 34337851 DOI: 10.1111/1541-4337.12811] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 06/16/2021] [Accepted: 06/30/2021] [Indexed: 12/15/2022]
Abstract
Berries represent one of the most important and high-valued group of modern-day health-beneficial "superfoods" whose dietary consumption has been recognized to be beneficial for human health for a long time. In addition to being delicious, berries are rich in nutrients, vitamins, and several bioactive compounds, including carotenoids, flavonoids, phenolic acids, and hydrolysable tannins. However, due to their high value, berries and berry-based products are often subject to fraudulent adulteration, commonly for economical gain, but also unintentionally due to misidentification of species. Deliberate adulteration often comprises the substitution of high-value berries with lower value counterparts and mislabeling of product contents. As adulteration is deceptive toward customers and presents a risk for public health, food authentication through different methods is applied as a countermeasure. Although many authentication methods have been developed in terms of fast, sensitive, reliable, and low-cost analysis and have been applied in the authentication of a myriad of food products and species, their application on berries and berry-based products is still limited. The present review provides an overview of the development and application of analytical chemistry methods, such as isotope ratio analysis, liquid and gas chromatography, spectroscopy, as well as DNA-based methods and electronic sensors, for the authentication of berries and berry-based food products. We provide an overview of the earlier use and recent advances of these methods, as well as discuss the advances and drawbacks related to their application.
Collapse
Affiliation(s)
- Heikki M Salo
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
| | - Nga Nguyen
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
| | - Emmi Alakärppä
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
| | - Linards Klavins
- The Natural Resource Research Centre, University of Latvia, Riga, Latvia
| | - Anne Linn Hykkerud
- Department of Horticulture, Norwegian Institute of Bioeconomy Research (NIBIO), Ås, Norway
| | - Katja Karppinen
- Department of Horticulture, Norwegian Institute of Bioeconomy Research (NIBIO), Ås, Norway.,Department of Arctic and Marine Biology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Laura Jaakola
- Department of Horticulture, Norwegian Institute of Bioeconomy Research (NIBIO), Ås, Norway.,Department of Arctic and Marine Biology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Maris Klavins
- The Natural Resource Research Centre, University of Latvia, Riga, Latvia
| | - Hely Häggman
- Ecology and Genetics Research Unit, University of Oulu, Oulu, Finland
| |
Collapse
|
6
|
Mu Q, Kang Z, Guo Y, Chen L, Wang S, Zhao Y. Hyperspectral image classification of wolfberry with different geographical origins based on three-dimensional convolutional neural network. INTERNATIONAL JOURNAL OF FOOD PROPERTIES 2021. [DOI: 10.1080/10942912.2021.1987457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Qingshuang Mu
- School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China
| | - Zhilong Kang
- School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China
| | - Yanju Guo
- School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China
| | - Lei Chen
- School of Information Engineering, Tianjin University of Commerce, Tianjin, China
| | - Shenyi Wang
- School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China
| | - Yuchen Zhao
- School of Electronic Information Engineering, Hebei University of Technology, Tianjin, China
| |
Collapse
|