Independent component analysis (ICA) was integrated with near infrared (NIR) spectroscopy for rapid quantification of sugar content in wax jambu (Syzygium samarangense Merrill & Perry). The JADE algorithm (Joint Approximate Diagonalization of Eigenmatrices) and linear regression with spectral pretreatments were incorporated to analyze the NIR spectra of wax jambu against sucrose solutions. Unlike other multivariate approaches, ICA enabled comprehensive quantification of sugar content in wax jambu. In the present study, ICA was applied as the sole tool to build the NIR calibration model of internal quality of intact wax jambu without any other multivariate analysis methods. The best spectral calibration model of wax jambu (600 to 700 nm and 900 to 1,098 nm) yielded rc = 0.988, SEC = 0.243°Brix, rv = 0.971, SEV = 0.381°Brix, and RPD = 4.15 using the normalized first derivative spectra and 9 independent components (ICs). All ICA results were better than those of partial least squares regression (PLSR). Thus, ICA can quickly identify and effectively quantify the sugar contents in wax jambu with calibration models achieving high predictability.
- Calibration model
- Independent component analysis (ICA)
- Near infrared (NIR) spectroscopy
- Sugar content
- Wax jambu
ASJC Scopus subject areas
- Food Science