<![CDATA[Soursop (Annona muricata L.) leaves have been widely used traditionally to overcome health problems, this is related to its total phenolic content. This study was aimed to determine the classification model and total phenolic content of soursop leaf powder of local varieties, in different altitudes using NIR and FTIR spectroscopy with chemometrics. Local variety soursop leaf samples that have been collected from low land (0-200 meter above sea level (masl)), medium land (201-700 masl) and high land (>700 masl) are prepared, then scanned using NIR and FTIR spectroscopy. Furthermore, the NIR spectra data from the samples were used as predictors on the LDA classification model of local and queen varieties soursop leaves to identify sample varieties. Samples identified as local varieties, whose total phenolic content was determined using a comparative method (UV-Vis spectrophotometry). The highest mean of total phenolic content is owned by samples from medium land (Jember) of 5.72% w/w GAE, followed by low land (Bangkalan) 2.95% w/w GAE and high land (Batu) 1, 78% w/w GAE. NIR and FTIR spectra data belonging to the samples were analyzed by chemometrics qualitatively using LDA, SVM and SIMCA, and quantitatively using PLS, PCR and SVR. The best classification and calibration model are formed from the NIR spectra data, that are the LDA model with an accuracy of 100% and the PLS model with an R-square calibration value of 0.998071 and RMSEC of 1.2735631. The LDA and PLS models are applied to the real samples. The results of the sample's total phenolic content determination obtained from the NIR spectroscopy method and UV-Vis spectrophotometry method were then tested with Paired-Samples T Test and it can be concluded that the content obtained from the two methods did not have a significant difference.]]>
