Evaluation of Suitable Cultivation Regions in China for Siraitia grosvenorii Using a MaxEnt Model and Inductively Coupled Plasma Mass Spectrometry

Global climate change is reshaping the habitat suitability of medicinal plants, potentially compromising their phytochemical integrity and therapeutic efficacy. Siraitia grosvenorii, an edible medicinal plant in China, has expanded its cultivation area into non-native habitats. Therefore, this study analyzed the suitable cultivation region under different periods in China based on the MaxEnt model, and 59 samples were investigated to explore the interrelationships between chemical constituents and climatic variables through multivariate statistical analysis, which will contribute to meeting the sustainable supply of high-quality S. grosvenorii. We discovered that appropriate habitats cover an area of 58.76 × 104 km2, mainly in the southern parts of China. Under future climate conditions, suitable habitats decrease and shift to the northeast along the current habitats. The precipitation levels of the driest month, precipitation seasonality, and temperature seasonality were crucial for its distribution. Furthermore, 11 elements were identified to distinguish samples from different suitable areas through orthogonal partial least squares discriminant analysis. Correlation analysis revealed a strong association between chemical constituents and various climatic factors. This study offers valuable insights into potential S. grosvenorii cultivation areas in China and provides reference indicators for quality evaluation.

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Publication Details

Journal
Agronomy
Published
2025-06-17
DOI
https://doi.org/10.3390/agronomy15061474
Primary Topic
Biochemical Analysis and Sensing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation of Suitable Cultivation Regions in China for Siraitia grosvenorii Using a MaxEnt Model and Inductively Coupled Plasma Mass Spectrometry

Dianpeng Li, Fu ChuanMing, Xiaojie Yan, Jingru Song et al.
Agronomy
Biochemical Analysis and Sensing Techniques
article

Evaluation of Suitable Cultivation Regions in China for Siraitia grosvenorii Using a MaxEnt Model and Inductively Coupled Plasma Mass Spectrometry

Dianpeng Li, Fu ChuanMing, Xiaojie Yan, Jingru Song, Fei Dong, Fenglai Lu, Xiyang Huang
article en

Abstract

Global climate change is reshaping the habitat suitability of medicinal plants, potentially compromising their phytochemical integrity and therapeutic efficacy. Siraitia grosvenorii, an edible medicinal plant in China, has expanded its cultivation area into non-native habitats. Therefore, this study analyzed the suitable cultivation region under different periods in China based on the MaxEnt model, and 59 samples were investigated to explore the interrelationships between chemical constituents and climatic variables through multivariate statistical analysis, which will contribute to meeting the sustainable supply of high-quality S. grosvenorii. We discovered that appropriate habitats cover an area of 58.76 × 104 km2, mainly in the southern parts of China. Under future climate conditions, suitable habitats decrease and shift to the northeast along the current habitats. The precipitation levels of the driest month, precipitation seasonality, and temperature seasonality were crucial for its distribution. Furthermore, 11 elements were identified to distinguish samples from different suitable areas through orthogonal partial least squares discriminant analysis. Correlation analysis revealed a strong association between chemical constituents and various climatic factors. This study offers valuable insights into potential S. grosvenorii cultivation areas in China and provides reference indicators for quality evaluation.

AgronomyVol. 15(6)
Guangxi University (CN), Chinese Academy of Sciences (CN), Guangxi Institute of Botany (CN), Guangxi University of Chinese Medicine (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 83%
Biochemical Analysis and Sensing Techniques
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