JOURNAL ARTICLE
Deeper insights into the physiological and metabolic functions of the pigments in plants and their applications: beyond natural colorants.
Published In: Physiologia Plantarum, 2025, v. 177, n. 2. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Mishra, Gayatri; Dash, Sasmita Priyadarsini; Mahapatra, Subrat Kumar; Swain, Dhaneswar; Rout, Gyana Ranjan 3 of 3
Abstract
Plant pigments are the natural source of color perceived by the human senses. They have captivated researchers to explore their structural, physical, and chemical properties, synthesis mode, and physiological significance. They are secondary metabolites in plants metabolism, growth and regulation, photosynthesis, and defense. Chlorophylls, carotenoids, anthocyanins, and betalains are the major classes of natural colors contributing color shades to textiles, foods, and cosmetics. The bioactive properties of these compounds are used to apply the compounds as pharmaceuticals to treat chronic degenerative diseases like hypertension, diabetes, cancer, and cardiovascular disorders. This review discusses classification, biosynthesis, physiological and metabolic activities, commercial applications of plant pigments, and knowledge gaps in pigment identification and application prospects. The review discusses developments in technologies such as non‐encapsulation to preserve the unstable properties of pigment extracts for commercial use and transporter genes involved in synthesizing essential pigments. However, additional research is required to gain insight into the candidate gene for orchestrating stress responses and the potential for engineering stress tolerance in various crops. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Physiologia Plantarum. 2025/03, Vol. 177, Issue 2, p1
- Document Type:Literature Review
- Subject Area:Chemistry
- Publication Date:2025
- ISSN:0031-9317
- DOI:10.1111/ppl.70168
- Accession Number:184713401
- Copyright Statement:Copyright of Physiologia Plantarum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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