dioscorea deltoidea
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2022 ◽  
Vol 175 ◽  
pp. 114174
Author(s):  
Romaan Nazir ◽  
Suphla Gupta ◽  
Abhijit Dey ◽  
Vijay Kumar ◽  
Ajai Prakash Gupta ◽  
...  

2021 ◽  
Vol 68 (6) ◽  
pp. 1098-1106
Author(s):  
L. A. Volkova ◽  
V. V. Urmantseva ◽  
A. B. Burgutin ◽  
A. M. Nosov

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253617
Author(s):  
Romaan Nazir ◽  
Devendra Kumar Pandey ◽  
Babita Pandey ◽  
Vijay Kumar ◽  
Padmanabh Dwivedi ◽  
...  

Introduction Dioscorea deltoidea var. deltoidea (Dioscoreaceae) is a valuable endangered plant of great medicinal and economic importance due to the presence of the bioactive compound diosgenin. In the present study, response surface methodology (RSM) and artificial neural network (ANN) modelling have been implemented to evaluate the diosgenin content from D. deltoidea. In addition, different extraction parameters have been also optimized and developed. Materials and methods Firstly, Plackett-Burman design (PBD) was applied for screening the significant variables among the selected extraction parameters i.e. solvent composition, solid: solvent ratio, particle size, time, temperature, pH and extraction cycles on diosgenin yield. Among seven tested parameters only four parameters (particle size, solid: solvent ratio, time and temperature) were found to exert significant effect on the diosgenin extraction. Moreover, Box-Behnken design (BBD) was employed to optimize the significant extraction parameters for maximum diosgenin yield. Results The most suitable condition for diosgenin extraction was found to be solid: solvent ratio (1:45), particle size (1.25 mm), time (45 min) and temperature (45°C). The maximum experimental yield of diosgenin (1.204% dry weight) was observed close to the predicted value (1.202% dry weight) on the basis of the chosen optimal extraction factors. The developed mathematical model fitted well with experimental data for diosgenin extraction. Conclusions Experimental validation revealed that a well trained ANN model has superior performance compared to a RSM model.


2021 ◽  
Vol 499 (1) ◽  
pp. 282-288
Author(s):  
JiaYing Wu ◽  
Ying Xiong ◽  
Bin Xu ◽  
ZhenMin Huang ◽  
XiaoFang Cheng

2021 ◽  
Vol 497 (1) ◽  
pp. 144-150
Author(s):  
Ying Jiao ◽  
Ying Xiong ◽  
Lin He ◽  
Zhifeng Yang ◽  
Hong Yuan ◽  
...  

Agronomy ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 394
Author(s):  
Maria V. Titova ◽  
Elena V. Popova ◽  
Svetlana V. Konstantinova ◽  
Dmitry V. Kochkin ◽  
Igor M. Ivanov ◽  
...  

Dioscorea deltoidea is a medicinal plant valued for its high content of steroidal glycosides (SG)—bioactive compounds with cardioprotective and immunomodulation actions, also used to treat reproductive system disorders. To overcome the limitations of natural resources of this species, a suspension cell culture of D. deltoidea was developed as a renewable and ecologically sustainable source of raw biomass and SG. Cell culture demonstrated stable and intensive growth in the laboratory (20 L) and industrial (630 L) bioreactors operated under a semi-continuous regime (specific growth rate 0.11–1.12 day−1, growth index 3.5–3.7). Maximum dry weight accumulation (8.5–8.8 g/L) and SG content (47–57 mg/g DW) were recorded during the stationary phase. Bioreactor-produced cell biomass contained inorganic macro (K, Ca, Mg, Na) and micro (Zn, Mn, Fe, B, Al, Cu, Cr, Se, Co, Ni) elements in concentrations within the safe range of dietary recommendations. Acute toxicity test showed no or insignificant changes in organ weight, hematological panel and blood biochemistry of laboratory animals fed with 2000 and 5000 mg/kg dry biomass. The results suggest that cell culture of D. deltoidea grown in bioreactors has great potential to be used as functional foods and a component of specialized dietary supplements in complex therapy of reproductive system disorders and mineral deficiency.


2021 ◽  
pp. 769-777
Author(s):  
Nirmala Joshi ◽  
Hassan Sher ◽  
Ikram Ur Rahman ◽  
Rainer W. Bussmann ◽  
Narel Y. Paniagua-Zambrana

2021 ◽  
Vol 68 (6) ◽  
pp. 612-621
Author(s):  
Л. А. Волкова ◽  
В. В. Урманцева ◽  
А. Б. Бургутин ◽  
А. М. Носов
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