Abstract:
Flowers are gaining considerable interest among consumers as ingredients in food, beverages, cosmetics, and natural health products. The supply chain trades in multiple forms of botanicals, including fresh whole flowers, which are easier to identify than dried flowers or flowers processed as powdered or liquid extracts. There is a gap in the scientific methods available for the verification of flower species ingredients traded in the supply chains of multiple markets. The objective of this paper is to develop methods for flower species ingredient verification using two orthogonal methods. More specifically, the objectives of this study employed both (1) DNA-based molecular diagnostic methods and (2) NMR metabolite fingerprint methods in the identification of 23 common flower species ingredients. NMR data analysis reveals considerable information on the variation in metabolites present in different flower species, including color variants within species. This study provides a comprehensive comparison of two orthogonal methods for verifying flower species ingredient supply chains to ensure the highest quality products. By thoroughly analyzing the benefits and limitations of each approach, this research offers valuable insights to support quality assurance and improve consumer confidence.
摘要:
鲜花作为食品成分在消费者中引起了相当大的兴趣,饮料,化妆品,和天然保健品。供应链以多种形式的植物药进行交易,包括新鲜的整花,比干花或加工成粉末或液体提取物的花更容易识别。在验证多个市场供应链中交易的花卉成分的科学方法方面存在差距。本文的目的是使用两种正交方法开发花卉品种成分验证的方法。更具体地说,这项研究的目的采用了(1)基于DNA的分子诊断方法和(2)NMR代谢物指纹图谱方法来鉴定23种常见花卉成分。NMR数据分析揭示了有关不同花卉物种中代谢物变化的大量信息,包括物种内的颜色变体。本研究提供了两种正交方法的综合比较,以验证花卉品种成分供应链,以确保最高质量的产品。通过全面分析每种方法的好处和局限性,这项研究为支持质量保证和提高消费者信心提供了有价值的见解。