Saba Naz

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent.

Quick determination of melamine in infant powder and liquid milk by Fourier transform infrared spectroscopy

A simple, cost-effective and environmentally friendly analytical method was developed for the quantification of melamine (MEL) in liquid milk and infant powder by using transmission Fourier transform infrared (FT-IR) spectroscopy. Standards and samples were analyzed in the form of a KBr pellet for recording FT-IR spectra. Partial least squares calibration was established in the FT-IR region, 851.62–798.39 cm−1, with a linear range of 0.001–1%. An excellent coefficient of determination (R2) of 0.9999 was achieved, with minimum errors in the root mean square error of calibration and the root mean square error of prediction, for which the values were 0.17 and 3.49, respectively. The accuracy of the calibration model was also verified using the root mean square error of cross-validation, which was found to be 2.25. The limit of detection and the limit of quantification of the method were 0.0001% (1 ppm) and 0.00035% (3.5 ppm), respectively. The method was successfully applied to liquid and infant powder milk samples and gave good recoveries (98.9–100.2%). The FT-IR method developed here is efficient, accurate and appropriate for MEL detection in the dairy industry, with a reduced cost and a short analysis time.

Chemical Characterization of Canola and Sunflower Oil Deodorizer Distillates

Abstract In the present work deodorizer distillates of canola and sunflower oil were studied for their chemical characterization. Tocopherols, sterols, hydrocarbons and fatty acid composition were determined by Gas chromatography Mass spectrometry (GC-MS). Results indicated that deodorizer distillates of canola oil (DDCLO) studied had higher saponification value in the range of 164.2-175.8 mg/g and all deodorizer distillates of sunfl ower oil (DDSFO) had high iodine value of 126.2-127.1 g/100 g. Peroxide value and free fatty acids were present in the range between 7.0-8.9 mEq/Kg and 35.7-54.4 g/100 g in DDSFO and DDCLO samples, respectively. Contents of oleic acid (49.3-51.1 g/100 g) and linolenic acid (6.2-7.5 g/100 g) were significantly greater in DDCLO samples. Conversely, DDSFO contained concentrated amount of linoleic acid (52.8-53.3 g/100 g). Tocopherols and hydrocarbons were significantly higher in all DDSFO samples while, sterols were dominant in DDCLO samples. GC-MS provided excellent results for simultaneous determination of tocopherols, sterols, hydrocarbons and fatty acid composition of deodorizer distillates of canola and sunflower oil

A green approach for the production of biodiesel from fatty acids of corn deodorizer distillate

A novel alginic acid derived tin catalyst, tin alginate (Sn–Alg), was successfully synthesized, characterized and applied for methyl esterification. Initially, the amount of catalyst, methanol to fatty acid ratio and reaction time were optimized using an oleic acid standard for esterification. The optimal reaction conditions were found to be 4% catalyst, 1 : 12 oleic acid to methanol mole ratio and 2 h reaction time with 98.7% fatty acid methyl ester recovery. The capability of Sn–Alg beads to esterify the fatty acids of corn deodorizer distillate was evaluated. High recovery (97.6%) of esters was obtained after 8 cycles using reprocessed catalyst under the optimized parameters. The results of the present study indicated that based on the environmental pollution, reusability, avoiding the use of potassium or sodium hydroxides or sulphuric or phosphoric acids, and ease of catalyst separation, the solid Sn–Alg catalyst has a great potential for biodiesel production from highly free fatty acid deodorizer distillates.

Synthesis of Highly Stable Cobalt Nanomaterial Using Gallic Acid and Its Application in Catalysis

We report the room temperature (25–30°C) green synthesis of cobalt nanomaterial (CoNM) in an aqueous medium using gallic acid as a reducing and stabilizing agent. pH 9.5 was found to favour the formation of well dispersed flower shaped CoNM. The optimization of various parameters in preparation of nanoscale was studied. The AFM, SEM, EDX, and XRD characterization studies provide detailed information about synthesized CoNM which were of 4–9 nm in dimensions. The highly stable CoNM were used to study their catalytic activity for removal of azo dyes by selecting methyl orange as a model compound. The results revealed that 0.4 mg of CoNM has shown 100% removal of dye from 50 μM aqueous solution of methyl orange. The synthesized CoNM can be easily recovered and recycled several times without decrease in their efficiency.