Determination of Classification Model and Phytochemical Content of Methanol Extract of Andrographis paniculata Leaves from Different Altitude Regions using Near Infrared Spectroscopy and Chemometric

Abstract

Context: Andrographis paniculata is one of the plants from Acanthaceae family that usually used as a traditional medicine in Indonesia. Aims: This research aims to explore the capability of Near Infrared (NIR) spectroscopy and chemometrics to classify the A. paniculata leaves extracts which were planted in different altitude regions and determine phytochemical content of the leaves extracts. Settings and Design: A model for determining calssification of plant extracts was formed using NIR spectra and chemometric then the model was applied on real samples. Phytochemical content of the leaves extracts were determined by partial least square model. Methods and Material: Samples were extracted by methanol then scanning the extract with NIR spectrophotometer at (780 to 2 500) nm. NIR spectra was analyzed with The Unscrambler software to formed classification model. Statistical analysis used: The samples was classified using LDA (Linear Discriminant Analysis), SIMCA (Soft Independent Modelling of Class Analogies), SVM (Support Vector Machines) and CA (Cluster Analysis). Results: LDA, SIMCA and SVM has formed an accuracy value of 100 % while the CA classification model produces two clusters, cluster A consist of extracts from Malang and Madura region, Indonesia, and cluster B consist of extracts from Jember region, Indonesia. A. paniculata from Malang region, Indonesia has the highest concentration of phenolic, flavonoid and alkaloid that were 164.3 mg GAE g . Conclusions: This study showed that NIR spectroscopy coupled with chemometric could be used for classified the A. paniculata which is planted in different altitude regions.