GENETIC AND ENVIRONMENTAL EFFECTS ON ALLOMETRY OF THE MEDICINAL PLANT DENDROBIUM OFFICINALE (ORCHIDACEAE) FROM YUNNAN, SOUTHWEST CHINA
文献类型： 外文期刊
作者： Zhang, Ji 1 ; Li, Tao 2 ; Cai, Yifan 3 ; Wang, Yuanzhong 1 ;
作者机构： 1.Yunnan Acad Agr Sci, Med Plants Res Inst, Kunming 650200, Yunnan, Peoples R China
2.Yuxi Normal Univ, Sci Res Dept, Yuxi 653100, Peoples R China
3.Texas Technol Univ, Biol Dept, Lubbock, TX 79409 USA
关键词： Dendrobium officinale; Allometry; Medicinal plant; Orchidaceae
期刊名称：PAKISTAN JOURNAL OF BOTANY （ 影响因子：0.972； 五年影响因子：0.988 ）
ISSN： 0556-3321
年卷期： 2021 年 53 卷 5 期
页码：
收录情况： SCI
摘要： Medicinal plant (MP) cultivation is taken into consideration for the sustainable use of MPs. The effort in developing effective management of MPs has focused on biomass allocation of to the medicinal parts. Two experiments were designed and carried out to explore genetic and environmental effects on the biomass partitioning patterns of Dendrobium officinale Kimura et Migo in southwest China. We found that there were significant differences in the average of stem biomass (SB), leaf biomass (LB), total biomass (TB), and stem length (SL), respectively, among nine provenances of D. officinale (p<0.01). The allometric relationships differed among provenances, indicating different growth strategies in different provenances of D. officinale. Significant differences in the average of SB, LB, TB, and SL, respectively, were also found among the same provenance of D. officinale cultivated at five different sites (p<0.01). It suggested that environmental factors influenced the biomass accumulation in the plants. These findings show that the biomass allocation of D. officinale was able to respond to both genetic and environmental effects. Therefore, the provenances with high-yield should be selected for commercial cultivation, and a suitable environment for D. officinale growth should be considered.
- 相关文献
作者其他论文 更多>>
-
Rapid determination of geographical authenticity of Gastrodia elata f. glauca using Fourier transform infrared spectroscopy and deep learning
作者：Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词：Gastrodia elata f. glauca; Fourier transform infrared spectroscopy; Deep learning; Data driven version of soft independent; modeling of class analogy
-
ResD-Net: A model for rapid prediction of antioxidant activity in gentian root using FT-IR spectroscopy
作者：Li, Xiaokun;Zeng, Pan;Wu, Xunxun;Yang, Xintong;Liu, Peizhong;Diao, Yong;Lin, Jingcang;Liu, Peizhong;Wang, Yuanzhong
关键词：Antioxidant activity; FT-IR; Gentian; Deep Learning; Chemometrics
-
Development of machine learning models using multi-source data for geographical traceability and content prediction of Eucommia ulmoides leaves
作者：Zhang, Yanying;Zhang, Yanying;Zhu, Xinyan;Wang, Yuanzhong
关键词：Machine learning; Eucommia ulmoides leaves; Geographical traceability; Content prediction; Quality evaluation
-
ATR-FTIR Spectroscopy Preprocessing Technique Selection for Identification of Geographical Origins of Gastrodia elata Blume
作者：Liu, Hong;Li, Jieqing;Liu, Hong;Wang, Yuanzhong;Liu, Honggao
关键词：ATR-FTIR spectroscopy; data preprocessing; DD-SIMCA; Gastrodia elata Blume; GBM; PLS-DA; SVM
-
The method based on ATR-FTIR spectroscopy combined with feature variable selection for the boletus species and origins identification
作者：Ji, Zhiyi;Li, Jieqing;Ji, Zhiyi;Wang, Yuanzhong;Liu, Honggao
关键词：feature variable selection; food safety; mid-infrared spectroscopy; species identification; traceability; wild boletus
-
Effect of drying temperature on composition of edible mushrooms: Characterization and assessment via HS-GC-MS and IR spectral based volatile profiling and chemometrics
作者：Zheng, Chuanmao;Li, Jieqing;Zheng, Chuanmao;Wang, Yuanzhong;Liu, Honggao
关键词：Boletus bainiugan; HS-SPME-GC-MS; VOCs; 2DCOS; Chemometrics; Quality estimation
-
A fast method for predicting adenosine content in porcini mushrooms using Fourier transform near-infrared spectroscopy combined with regression model
作者：Deng, Guangmei;Li, Jieqing;Deng, Guangmei;Wang, Yuanzhong;Liu, Honggao
关键词：Fourier transform near-infrared spectroscopy; Porcini mushrooms; Adenosine; Partial least squares regression
