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.

Background and Aim: Meat is a rich source of many nutrients and plays a vital role in human life however, meat safety is one of the top priorities of great concern for consumers today. More than 90% of human exposure to harmful materials is due to consumption of contaminated meat products. This study was designed to compare four valid analytical methods for the determination of organochlorine pesticides 2,4 D (2,4-dichlorophenoxyacetic acid), dichlorodiphenyldichloroethylene/ dichlorodiphenyltrichloroethane, alachlor, organophosphate, anabolic steroids (progesterone, testosterone, and estrogen), antibiotics (tetracycline, sulfonamides, gentamycin, and cephalexin), antibacterial compounds (Macrolide, β-Lactam, Chloramphenicol, Sulphur drugs, and Gentamicin) residues in 135 beef, buffalo, and sheep meat samples (fresh, frozen meats, minced, and sausage samples) of local, regional, and international brands available in Omani markets. Materials and Methods: Triplicate meat samples from each brand within each species were extracted with acetonitrile and purified with acetonitrile-saturated n-hexane to remove all impurities. To dry the sample after heating, the residue was passed across a Sep-Pak C18 cartridge for sample cleaning before gas chromatography (GC) (Brand GCMS-QP2010 Plus) coupled with different detectors, including a mass spectrometer or GC-electron capture detector (GC-ECD). Liquid chromatography/mass spectrometry (LC-MS) was also employed for the quantification of the residues in meat products. Enzyme-linked immunosorbent assay (ELISA) kits were employed to assess veterinary drug residues, anabolic steroids, and pesticides. The CHARM II instrument was employed to detect chloramphenicol, gentamicin, sulfa-drug, β-lactam, and macrolide residues in meat and meat product samples. Results: A thin-layer chromatographic (TLC) method should be considered as another method of choice to determine concentrations of veterinary drugs and anabolic steroids. The TLC results were validated by LC-MS. The three described methods permit the multi-residue analysis of anabolic steroid residue levels of 0.06-1.89 ppb in meat product samples. There were three violative residues of anabolic steroids in red meat products that were above the maximum residue limits (MRLs). Although, the levels of organochlorine pesticides and antibiotic concentrations in meat products were below the MRLs, the long-term consumption is considered a health hazard and will affect the wellbeing of consumers. Conclusion: The four techniques (GC, high-performance liquid chromatography, ELISA and CHARM II) provided results that were reliable and precise for the detection of chessssmical residues in meat and meat products.