Development of a low-cost modular VIS/NIR spectroscopy for predicting soluble solid content of banana

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Soluble solids content (SSC) is one of the most important parameters of banana associated with taste and consumer acceptance. NIR spectroscopy has been applied for nondestructive determination of SSC, but limited studies were conducted for a low-cost and modular VIS/NIR spectroscopy. This study was conducted to develop a calibration model to predict SSC in bananas using a modular type of VIS/NIR spectroscopy in the range of 350-1000 nm by varying distances of fiber optic probe to samples. Two varieties of bananas, namely Musa acuminata × balbisiana and Musa acuminata ‘Lady Finger’ were used. Partial least square regression (PLSR) was used to build a calibration model and to predict SSC of bananas. Normalization, baseline correction, standard normal variate (SNV), and multiple scattered (MSC) correlation were used for spectra preprocessing. The research showed that using 2 cm probe-sample distance and SNV method resulted in the best model with the coefficient correlation of calibration and prediction of 0.95 and 0.87, respectively. This study proved that probe-sample distances affected the efficiency of the model for VIS/NIR spectroscopy. This work concluded that the low-cost modular VIS/NIR spectroscopy is a promising tool for SSC measurement.