pH Prediction of Perlis Sunshine Mango Using NIR Spectrometer

Abstract

Abstract To evaluate the various internal quality attributes of fruits, NIR spectroscopy techniques are undoubtedly quick and non-destructive tools. Acidity (pH) is one of the main quality attributes in mango fruits. Generally, it is being predicted in destructive way. The aim of this research was to develop calibration model and prediction of pH in Perlis Sunshine mangoes using NIR spectrometer. The transmission spectra of Sunshine mangoes were acquired in the wavelength range from 300 to 1000 nm. The effects of different types of pre-processing methods and spectra treatments, such as baseline correction, multiplicative scatter correction (MSC), Savitzky-Golay (SG) smoothing, second order derivative (SG) and normalisation were analyzed. The prediction models were developed by partial least squares (PLS) regression. The coefficient of determination (R2) of pH was 0.928 and the standard error of cross-validation (SECV) was 0.153. The results indicated that by using the NIR measurement system, in the suitable spectral range, it is possible to predict the pH of mango fruits by non-destructively.