Global Journal of Medicinal Plants Research received 497 citations as per Google Scholar report
Andasuryani, Y. A. Purwanto, I. W. Budiastra and K. Syamsu
Catechin, an abundant component within gambir, is the main determinant of gambir quality. The general method to determine catechin is time consuming, costly and produces chemical residual. The objective of this study was to develop NIR calibration model which could be used to predict catechin content of gambir efficiently. Calibration model was established using partial least square (PLS) algorithm by investigating 3 different pre-treatment methods which were normalization between 0 and 1 (n01) first derivative Savitzky-Golay 9 points (dg1) and n01 in combination with dg1 (n01, dg1). Determination of optimum factors number was conducted based on predicted residual error sum square in validation set (V-set PRESS) values and consistency. This study found that pre-treatment n01, dg1 was the best method to produce calibration model. Quality of the best model was shown by (1) high coefficient correlation (r) = 0.91, (2) low standard error of calibration set (SEC) = 2.53% and standard error of validation set (SEP) = 2.44%, (3) slight difference between SEC and SEP. This study demonstrated that FT-NIR spectroscopy could be used as a tool for predicting the catechin content in gambir. It could replace expensiveness and time as well as effort consuming reference method.
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