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A portable microNIR instrument as a screening tool in discriminating fruit based beverages prepared with cow ricotta cheese whey by-products.

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INTRODUCTION
Ricotta cheese whey (RCW)-fruit based beverages are a novel type of healthy drinks, in which the nutritional components of fruit are combined with proteins and minerals of the dairy RCW by-product. Varying the fruit component as well as the type of technological process to obtain ricotta cheese from whey, different functional properties can be achieved. This work aimed at verifying the ability of a diode array microNIR to discriminate RCW-fruit based beverages prepared from four types of clear juices (pear, strawberry, blueberry, apple) and two RCWs, considering various technological factors such as the proportion of RCW to fruit juice, the influence of the pasteurization step and of storage time on open shelf.
EXPERIMENTAL
Beverages were prepared from concentrated clear juices diluted with tap water to 16.6 % soluble solids content and RCW in different proportions (80:20, 70:30, 60:40) in order to obtain beverages standardized at 14% of soluble solids content. After bottling in 125-mL glass bottles, beverages were pasteurized and put in shelf life on open shelf up to 5 months. NIR spectra were recorded by a diode array microNIR (MicroNIR1700, Diessechem instrument, Italy) over the range 900-1280 nm in transmittance mode, using a 1-cm light path cuvette. Measurements were carried out on beverages soon after mixing (TQ), and after pasteurization. On one lot of apple and blueberry based beverages measurements were performed after 5 month storage on open shelf at ambient temperatures. NIR spectra were transformed in absorbance, and then processed using PLS_Toolbox (Eigenvector Research, Inc., USA) software. PCA was performed on spectra; scores of Principal components were submitted to analysis of variance and means were compared by Tukey’s test.
RESULTS AND DISCUSSION
Using PCA analysis on absorbance spectra from 900 to 1280 nm three principal components (PC) were obtained. PC-1, explaining 96.88% of total variance, distinguished blueberry and strawberry-20% RCW based beverages from pear and apple-based ones; PC-1 value was higher in 40% RCW based beverages than in 20% and 30% RCW ones and in pasteurized beverages than in TQ ones. PC-2 explained 2.57% of total variance, had negative scores for pear and apple-20% RCW based beverages and positive for blueberry and strawberry-based ones, with the latter drink having the highest score; PC-2 was higher in 20% RCW based beverages than 40% RCW ones. PC-3 (0.21% of total variance explained) distinguished the 20% RCW beverage based on apple and blueberry juices mixed in a 50+50 ratio (MIX) from pear, apple, blueberry and strawberry-based ones, had a lower value in pasteurized beverage and in 40% RCW based ones. Furthermore all PCs were able to distinguish 30% RCW apple-based and MIX-based beverages prepared from each type of RCW.
Our results indicate that chemometric analysis applied to the NIR spectra was able to discriminate RCW-based beverages according to their formulation (type of juice used, type of RCW, RCW to juice proportion) as well as the processing step (TQ and after pasteurization).