Mango and mangosteen are commercially important tropical fruits with a short shelf life. Fruit processing is one of the alternatives to extend the shelf life of these fruits. Purée is one of the processed products of fresh fruit. In this research, the quality of mango and mangosteen purée was analyzed. Titratable acidity (TA) and total soluble solids (TSS) were predicted using non-destructive near-infrared (NIR) spectroscopy. A partial least squares regression (PLSR) model was developed based on the NIR spectra with a wavelength ranging from 800 to 2500 nm. The PLSR model returned a coefficient of determination (r²) and a ratio of prediction to deviation (RPD) of 0.955 and 4.7 for TSS, and 0.784 and 2.2 for TA, in the mango purée. Similarly, the best model was selected for the TSS prediction in the mangosteen purée through PLSR, with an r², a root mean square error of cross-validation (RMSECV), and RPD of 0.799, 0.3% malic acid, and 2.2, respectively. The results show the possible application of NIR spectroscopy in the product processing line, although a larger number of samples with wide variation in future studies are needed as an input to update the model, in order to obtain a more robust model.

This research comparatively investigates different mangosteen pericarp processing schemes. The experimental pericarp processing schemes were hot air drying (HAD; control), quick freezing/HAD (QF + HAD), slow freezing/HAD (SF + HAD), and slow freezing/freeze-drying (SF + FD). For freezing, the QF temperature was −38 °C for 2 h and that of SF was −25 °C for 2 weeks. For drying, the HAD temperature was 60 °C for 7 h. In the FD process, the primary and secondary temperatures were −20 °C and 50 °C for 48 h. The experimental results showed that the freezing method (i.e., QF and SF) affected the physical properties (moisture content, water activity, and color) of dried mangosteen pericarp. The antioxidant activities (DPPH and ABTS) of the SF + HAD scheme (28.20 and 26.86 mg Trolox/g DW of mangosteen pericarp) were lower than the SF + FD scheme (40.68 and 41.20 mg Trolox/g DW of mangosteen pericarp). The α-mangostin contents were 82.3 and 78.9 mg/g DW of mangosteen pericarp for FD and HAD, respectively; and the corresponding TPC were 1065.57 and 783.24 mg GAE/g DW of mangosteen pericarp. The results of this study suggest that the drying process had a negligible effect on bioactive compounds. Essentially, the SF + HAD technology is the most operationally and economically viable scheme to process mangosteen pericarp.

To date, different approaches have been applied to measure the internal parameters of mangoes by destructive and non-destructive techniques. Recently, real-time evaluation of the internal parameters has become important assessment for fruits in high demand. This research aims to develop an online prototype system to measure the total soluble solids (TSS) in mangoes using a fiber optic diode array Visible-Near Infrared (VisNIR) spectrometer on a conveyor belt. Spectra were acquired in a wavelength range from 400-1000 nm. The diffuse reflectance spectra of mangoes were subjected to several preprocessing techniques such as moving average smoothing (MAS), standard normal variate (SNV), multiplicative scatter correction (MSC), baseline offset and normalization before model development. The spectral information and corresponding TSS values were used to establish a linear relationship by partial least squares (PLS) regression. Spectra in three wavelength ranges of 400-1000 nm, 600-1000 nm, and 700-1000 nm were used for the model development. Baseline offset combined with MAS showed effective transformation of spectra at a wavelength of 6001000 nm. The optimum model was obtained by an external validation technique with a correlation coefficient of calibration set and a prediction set of 0.80 and 0.74, respectively. The root mean square error of the calibration (RMSEC), root mean square error of prediction (RMSEP) and bias were 0.690%, 0.765%, and 0.061%, respectively. The statistical results from PLS regression indicated the feasibility of using the online conveyor system for grading the fruit according to the TSS.