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نتیجه جستجو - Medicinal plants

تعداد مقالات یافته شده: 2
ردیف عنوان نوع
1 The impact of the order of derivative spectra on the performance of pattern recognition methods: Classification ofmedicinal plants according to the phylum
تأثیر ترتیب طیفهای مشتق بر عملکرد روشهای تشخیص الگو: طبقه بندی گیاهان دارویی با توجه به نژاد-2019
Data pre-processing is an important strategy in chemometrics and related fields because inmany cases the transformation of data has a great effect on the performance of the method (model). However, a careful examination of the literature clearly points out that only very few systematic studies are dedicated to the effect of the derivative spectra on the performance of the pattern recognition methods. This comprehensive study compares the impact of the order of derivative spectra and other data pre-processing procedures (normalization and standardization) on the performance of cluster analysis, principal component analysis and discriminant analysis applied for characterization and classification of medicinal plants according to their phylum using UV spectra. The efficiency of the pre-processing methods was estimated by comparing the accuracy of classification and prediction measured by internal cross-validation. Derivatization method (1st order) resulted in the best classification (100%) of medicinal plants according to their phylum (Pteridophyte, Magnoliophyte and Spermatophyte) as compared to other pre-processing methods (normalized spectra-71.4%, standardized spectra-76.2% and original spectra-78.6%).
Keywords: Spectra pre-processing | Derivative-order effect | Pattern recognition methods | Medicinal plants | Phylum
مقاله انگلیسی
2 Predicting climate change impacts on the distribution of the threatened Garcinia indica in the Western Ghats, India
پیش بینی تاثیرات تغییر آب و هوا روی توزیع گاریسینای آستانه ای هندی در گرنه های غربی، هند-2018
In recent years, climate change has become a major threat and has been widely documented in the geographic distribution of many plant species. However, the impacts of climate change on the distribution of ecologically vulnerable medicinal species remain largely unknown. The identification of a suitable habitat for a species under climate change scenario is a significant step towards the mitigation of biodiversity decline. The study, therefore, aims to predict the impact of current, and future climatic scenarios on the distribution of the threatened Garcinia indica across the northern Western Ghats using Maximum Entropy (MaxEnt) modelling. The future projections were made for the year 2050 and 2070 with all Representative Concentration Pathways (RCPs) scenario (2.6, 4.5, 6.0, and 8.5) using 56 species occurrence data, and 19 bioclimatic predictors from the BCC-CSM1.1 model of the Intergovernmental Panel for Climate Change’s (IPCC) 5th assessment. The bioclimatic variables were minimised to a smaller number of variables after a multicollinearity test, and their contributions were assessed using jackknife test. The AUC value of 0.956 ± 0.023 indicates that the model performs with excellent accuracy. The study identified that temperature seasonality (39.5 ± 3.1%), isothermality (19.2 ± 1.6%), and annual precipitation (12.7 ± 1.7%) would be the major influencing variables in the current and future distribution. The model predicted 10.50% (19318.7 sq. km) of the study area as moderately to very highly suitable, while 82.60% (151904 sq. km) of the study area was identified as ‘unsuitable’ or ‘very low suitable’. Our predictions of Climate change impact on habitat suitability suggest that there will be a drastic reduction in the suitability by 5.29% and 5.69% under RCP 8.5 for 2050 and 2070, respectively. Objective and Significance Primary objective of this study is to identify the potential distribution of medicinally and ecologically important but threatened Garcinia indica species in the northern Western Ghats on the basis of species occurrence data and nineteen bioclimatic predictors. Using MaxEnt modelling, current and future species distribution and suitability has been predicted using the BCC-CSM1.1 and four RCP scenarios of 2.6, 4.5, 6.0, and 8.5. The results also signify the bioclimatic variables contribution to the species distribution in northern Western Ghats. Finally, the results signify that the model might be an efficient tool for biodiversity protection, ecosystem management, and species re-habitation planning under future climate change scenarios.
keywords: Garcinia indica |Maximum entropy modelling |Western Ghats |Medicinal plants |Climate change
مقاله انگلیسی
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