Medicinal Plants: Towards Optimization and Prediction of Drug Yield
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Herbal drugs are in use as medicines world over for centuries. The recent surge in demand for herbal drugs in global market, however, cannot be met due to constraints that need to be addressed immediately for their effective commercialization. A viable long-term alternative to overcome the inherent problems, therefore, is to opt for intensively monitored domestic cultivation. The immediate imperative however is to study the effect of environmental and biotic factors that affect quality and yield of phytochemicals under natural conditions. This review summarizes a list of drugs derived from dif...
Herbal drugs are in use as medicines world over for centuries. The recent surge in demand for herbal drugs in global market, however, cannot be met due to constraints that need to be addressed immediately for their effective commercialization. A viable long-term alternative to overcome the inherent problems, therefore, is to opt for intensively monitored domestic cultivation. The immediate imperative however is to study the effect of environmental and biotic factors that affect quality and yield of phytochemicals under natural conditions. This review summarizes a list of drugs derived from different plant sources, the role of different factors influencing their production with relevant examples. We have also analyzed critically about few such factors that can be controlled under greenhouse condition for production of plants with consistently high levels of desired phytochemicals. Further, the review also emphasizes the significance of developing models like artificial neural network (ANN) and multiple linear regression (MLR) for optimization and prediction of drug yield under any situation, either natural field condition or controlled greenhouse condition.
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