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ORIGINAL RESEARCH article

Front. Plant Sci.

Sec. Plant Nutrition

Volume 16 - 2025 | doi: 10.3389/fpls.2025.1592493

Comprehensive Evaluation of Frost Mulberry Leaves of 21 Mulberry Varieties

Provisionally accepted
Tian  JieTian Jie1Bingxiang  LiuBingxiang Liu1Fan  ZhitongFan Zhitong2Yang  JingyanYang Jingyan1Wu  YiboWu Yibo1Tian  XinyuanTian Xinyuan3Jia  ChenyangJia Chenyang4Wen  HaichaoWen Haichao1Zhang  BingyingZhang Bingying5Li  HongjiaoLi Hongjiao1*
  • 1College of Forestry, Hebei Agricultural University, Baoding, Hebei Province, China
  • 2Yunwuping Forest Farm in Jiangjin District, Chongqing, China
  • 3College of Food Science and Technology,Hebei Agricultural University, Bao Ding, China
  • 4Hebei Academy of Fine Arts, Shijiazhuang, Hebei Province, China
  • 5Hebei Hongya Mountain State- Owned Forest Farm, Baoding, China, Baoding, Hebei Province, China

The final, formatted version of the article will be published soon.

Mulberry, a medicinal and edible plant, exhibits significant pharmacological effects, including immune enhancement, blood lipid and glucose reduction, and tumor inhibition, due to the abundance of nutrients and bioactive components in its leaves. However, traditional mulberry breeding has primarily focused on developing high-yielding, high-quality, stress-resistant, and mechanizable leaf-type mulberry varieties, leading to a relatively uniform product output. With the increasing diversification of mulberry applications, the criteria for variety selection and quality evaluation have become more stringent. In this study, 21 mulberry varieties were selected as experimental materials to evaluate the variations in nutritional quality, functional components, and antioxidant properties of frost mulberry leaves across different varieties. Principal component analysis (PCA) was employed to determine key evaluation indicators. Subsequently, the entropy‐weight method was employed to assign weights to these core indicators, and grey relational analysis (GRA) was applied, to comprehensively assess the overall quality of frost mulberry leaves from the 21 varieties. The results indicate that, in terms of nutritional quality, 'Da 10' exhibited the highest free amino acid content; however, its low soluble sugar content negatively affected leaf texture. In contrast, 'Jiang Mi Guo Sang', 'Lv Shen Zi 2', and 'Ju Shen' demonstrated superior overall performance. Regarding functional components, 'Tang 10', 'Da Yi Bai', 'Da Bai E', and 'Lv Shen Zi 1' excelled across all indicators. Concerning antioxidant capacity, 'Da Bai E', 'Jiang Mi Guo Sang', 'He Lan Sang', and 'Ju Shen' ranked highly, while 'Da 10', 'Da Yi Bai', 'Hong Guo 1', and 'Da Bai E' exhibited higher enzyme activity. PCA identified 10 core indicators related to nutritional quality, functional components, and antioxidant capacity, with a cumulative variance contribution rate of 83.752%. The entropy weight method was then used to assign weights to these indicators, and the final grey relational degree, calculated using grey system theory, ranged from 0.476 to 0.785. This study demonstrates that the varieties 'Da Bai E', 'Da Yi Bai', 'Da 10', 'He Lan Sang', and 'Tang 10' exhibit superior overall quality and high nutritional value, providing theoretical support for the subsequent selection, cultivation, and utilization of mulberry varieties.

Keywords: mulberry, Frost mulberry leaf, nutritional quality, antioxidant capacity, Principal Component Analysis, Entropy weight method, Grey relational analysis

Received: 12 Mar 2025; Accepted: 22 Sep 2025.

Copyright: © 2025 Jie, Liu, Zhitong, Jingyan, Yibo, Xinyuan, Chenyang, Haichao, Bingying and Hongjiao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Li Hongjiao, lihongjiao0103@163.com

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.