Abstract
Fermented milk (laban) with added date syrup can be an excellent candidate for a nutritious drink. Modeling with quality index (Q(i)) can assist in assessing the quality of the drink's physiochemical properties. The properties of the laban drink fortified with date syrup were measured and modeled with Q(i) during shelf life (7 days), and then analyzed with near-infrared spectra (NIR). The aim of this study was to develop a quality index model for the laban drink properties (objective and sensory assessments) and then to predict Q(i) with a non-destructive measurement of NIR (with partial least-square regression (PLSR) and artificial neural network (ANN) analysis). The results revealed that the developed Q(i) fits well with measured laban drink properties (viscosity, color, total soluble solids, pH, and sensory assessments during the shelf-life period with R-2 = 0.977). The NIR spectrum was efficient to estimate the quality index of the fortified laban drink. It was found that ANN is more appropriate than the PLSR model in estimating the Q(i) of the Laban drink during cold storage. Thus, non-destructive NIR can predict Q(i) and can be utilized with great success in the whole chain of production, processing, transportation, storage, and retail market to check the "quality" and "shelf life" of the product.