Applications of FT-NIRS combined with PLS multivariate methods for the detection & quantification of saccharin adulteration in commercial fruit juices.

Detection of adulteration in carbohydrate-rich foods like fruit juices is particularly difficult because of the variety of the commercial sweeteners available that match the concentration profiles of the major carbohydrates in the foods. In present study, a new sensitive and robust assay using Fourier Transform Near-Infrared Spectroscopy (FT-NIRS) combined with partial least square (PLS) multivariate methods has been developed for detection and quantification of saccharin adulteration in different commercial fruit juice samples. For this investigation, six different commercially available fruit juice samples were intentionally adulterated with saccharin at the following percentage levels: 0%, 0.10%, 0.30%, 0.50%, 0.70%, 0.90%, 1.10%, 1.30%, 1.50%, 1.70% and 2.00% (weight/volume). Altogether, 198 samples were used including 18 pure juice samples (unadulterated) and 180 juice samples adulterated with saccharin. PLS multivariate methods including partial least-squares discriminant analysis (PLS-DA) and partial least-squares regressions (PLSR) were applied to the obtained spectral data to build models. The PLS-DA model was employed to differentiate between pure fruit juice samples and those adulterated with saccharin. The R2 value obtained for the PLS-DA model was 97.90% with an RMSE error of 0.67%. Similarly, a PLS regression model was also developed to quantify the amount of saccharin adulterant in juice samples. The R2 value obtained for the PLSR model was 97.04% with RMSECV error of 0.88%. The employed model was then cross-validated by using a test set which included 30% of the total adulterated juice samples. The excellent performance of the model was proved by the low root mean squared error of prediction value of 0.92% and the high correlation factor of 0.97. This newly developed method is robust, nondestructive, highly sensitive and economical.

New design of experiment combined with UV-Vis spectroscopy for extraction and estimation of polyphenols from Basil seeds, Red seeds, Sesame seeds and Ajwan seeds.

New experimental designs for the extraction of polyphenols from different seeds including Basil seed, Red seed, Sesame seeds and Ajwan seeds were investigated. Four variables the concentration and volume of methanol and NaOH solutions as well as the temperature and time of extraction were varied to see their effect on total phenol extraction. The temperature was varied in the range from 25°C to 200°C while the time in the range from 30 to 200minutes. Response surface methodology was used to optimize the extraction parameters. The estimation of polyphenols was measured through phenols reduction UV-Vis spectroscopic method of phosphotungstic-phosphomolybdic acids (Folin-Ciocalteu's reagent). Calibration curve was made by using tannic acid as a polyphenols standard in the concentration range from 0.1 to 10ppm. The regression line obtained shows the value of correlation coefficient i.e. R=0.930 and Root mean square error of cross validation (RMSEC) value of 0.0654. The Basil seeds were found containing the highest amount of total phenols i.e. 785.76mg/100g. While the Sesame seeds having the least amount i.e. 33.08mg/100g. The Ajwan seeds and the Red seeds are containing the medium amounts i.e. 379mg/100g and 220.54mg/100g respectively.