Detection of lard mixed with body fats of chicken, lamb and cow by fourier transform infrared spectroscopy

Fourier transform infrared (FTIR) spectroscopy provides a simple and rapid means of detecting lard blended with chicken, lamb, and cow body fats. The spectral bands associated with chicken, lamb, and cow body fats and their lard blends were recorded, interpreted, and identified. Qualitative differences between the spectra are proposed as a basis for differentiating between the pure animal fats and their blends. A semiquantitative approach is proposed to measure the percent of lard in blends with lamb body fat (LBF) on the basis of the frequency shift of the band in the region 3009–3000 cm−1, using the equation y = 0.1616x + 3002.10. The coefficient of determination (R2) was 0.9457 with a standard error (SE) of 1.23. The percentage of lard in lard/LBF blends was also correlated to the absorbance at 1417.89 and 966.39 cm−1 by the equations y = 0.0061x + 0.1404 (R2 = 0.9388, SE = 0.018) and y = 0.004x + 0.1117 (R2 = 0.9715, SE = 0.009), respectively. For the qualitative determination of lard blended with chicken body fat (CF), the FTIR spectral bands in the frequency ranges of 3008–3000, 1418–1417, 1385–1370, and 1126–1085 cm−1 were employed. Semiquantitative determination by measurement of the absorbance at 3005.6 cm−1 is proposed, using the equation y = 0.0071x + 0.1301 (R2 = 0.983, SE = 0.012). The percentage of lard in lard/GF blends was also correlated to the absorbance at 1417.85 cm−1 (y = 0.0053x + 0.0821, with R2 = 0.9233, SE = 0.019) and at 1377.58 cm−1 (y = 0.0069x + 0.1327, with R2 = 0.9426, SE = 0.022). For blends of lard with cow body fat (CBF) bands in the range 3008–3006 cm−1 and at 1417.8 and 966 cm−1 were used for qualitative detection. The equation y = –0.005x + 0.3188 with R2 = 0.9831 and SE = 0.0086 was obtained for semiquantitative determination at 966.22 cm−1

Rapid determinations of moisture content in crude palm oil by fourier transform infrared spectroscopy

A simple, rapid, and direct Fourier transform infrared (FTIR) spectroscopic method was developed for the determination of moisture content of crude palm oil (CPO). The calibration set was prepared by adding double-distilled water to dried CPO in ratios (w/w) between 0 and 13% moisture. A partial least squares (PLS) regression technique was employed to construct a calibration model followed by cross-validation step. The accuracy of this method was comparable to the accuracy of the American Oil Chemists’ Society’s vacuum oven method, which is used for determination of moisture and volatile matter, with mean difference (MDa) of 0.0105, a coefficient of determination (R2) and a standard error of calibration (SEC) of 0.9781 and 0.91, respectively. It is also comparable to the accuracy of the International Union of Pure and Applied Chemistry’s distillation method with MDa, R2, and SEC of 0.0695, 0.9701, and 0.65, respectively. The study showed that midband FTIR spectroscopy combined with the PLS regression calibration technique is rapid and accurate for determination of moisture content of CPO samples with a total analysis time of less than 2 min and less than 2 mL of sample

A new method for determining of gossypol in cottonseed oil by FTIR spectroscop

A new method was developed to determine the gossypol content in cottonseed oil using FTIR spectroscopy with a NaCl transmission cell. The wavelengths used were selected by spiking clean cottonseed oil to gossypol concentrations of 0–5% and noting the regions of maximal absorbance. Transmittance values from the wavelength regions 3600–2520 and 1900–800 cm−1 and a partial least squares (PLS) method were used to derive FTIR spectroscopic calibration models for crude cottonseed, semirefined cottonseed, and gossypol-spiked cottonseed oils. The coefficients of determination (R2) for the models were computed by comparing the results from the FTIR spectroscopy against those obtained by AOCS method Ba 8-78. The R2 were 0.9511, 0.9116, and 0.9363 for crude cottonseed, semirefined cottonseed, and gossypol-spiked cottonseed oils, respectively. The SE of calibration were 0.042, 0.009, and 0.060, respectively. The calibration models were cross-validated within the same set of oil samples. The SD of the difference for repeatability and accuracy of the FTIR method were better than those for the chemical method. With its speed (ca. 2 min) and ease of data manipulation, FTIR spectroscopy is a useful alternative to standard wet chemical methods for rapid and routine determination of gossypol in process and/or quality control for cottonseed oil

Determining α-tocopherol in refined bleached and deodorized palm olein using fourier transform infrared spectroscopy

Fourier transform infrared (FTIR) spectroscopy was developed for the determination of a-tocopherol in refined bleached and deodorized (RBD) palm olein. The calibration and validation samples were prepared by spiking known amount of a-tocopherol to produce a wide range of a-tocopherol up to 2000 ppm. The method was based on the sodium chloride (NaCl) windows, and the transmission path was fixed at 50 lm at room temperature. The partial least squares (PLS) calibration models for predicting a-tocopherol were developed by using the FTIR spectral region at 3100–2750 cm�1. The accuracy of the method was comparable to that of the high-performance liquid chromatography (HPLC), with coefficients of determination (R2) from calibration samples of 0.9922. The models were validated and the R2 of validation and the standard errors of prediction (SEP) computed. The standard deviation of difference for repeatability (SDDr) for the method was comparable to that for HPLC. With its speed and ease of data manipulation by the computer software, FTIR spectroscopy is advantageous as a simple and rapid quantitative determining analytical tool for a-tocopherol in RBD palm olein

Pengembangan Metode Deteksi Minyak Kedelai dalam Campuran Minyak Kelapa Murni dengan Spektroskopi Infra Merah dan Kemometrika

Fourier Transform Infrared (FTIR) spectroscopy combined with the chemometrics techniques of Discriminant Analysis (DA) as well as multivariate analysis of Partial Least Square (PLS) and Principal Component Regression (PCR) has been developed for analysis of soybean oil (SO) in virgin coconut oil (VCO). The spectral bands correlated with VCO, soybean oil (SO), and their blends were scanned, interpreted, and identifi ed. The combined wavenumber regions of 1200 – 1000 and 3025 – 2995 cm-1 were used during analysis either in classifi cation using DA or in quantifi cation using PLS and PCR. DA can be successfully used for the classifi cation of VCO and that added with SO with the accuracy level of 100 %. Furthermore, PLS using FTIR normal spectra was preferred to be used for the quantifi cation of SO in VCO over PCR and the spectral derivatives. The coeffi cient of determination (R2) value obtained for the relationship between actual and FTIR predicted value of SO is higher than 0.99 with acceptable errors, either in calibration or in validation models.ABSTRAKSpektroskopi Fourier Transform Infra Merah (FTIR) yang digabung dengan kemometrika analisis diskriminan serta analisis multivariat Partial Least Square (PLS) dan Principal Component Regression (PCR) telah digunakan untuk analisis adanya minyak kedelai dalam minyak kelapa murni (Virgin Coconut Oil, VCO). Spektra infra merah yang berhubungan dengan VCO, minyak kedelai, serta campuran keduanya direkam, diinterpretasi, dan diidentifi kasi. Kombinasi daerah bilangan gelombang 1200 – 1000 dan 3025 – 2995 cm-1 digunakan untuk tujuan ini. Analisis diskriminan menunjukkan bahwa VCO murni dapat dibedakan dengan VCO yang telah ditambah dengan minyak kedelai dengan tingkat akurasi 100 %. Sementara itu, model kalibrasi PLS menggunakan spektra normal lebih terpilih untuk kuantifi kasi minyak kedelai dalam VCO dibandingkan dengan PCR dan spektra turunannya. Nilai koefi sien determinasi (R2) yang diperoleh > 0,99 dengan tingkat kesalahan (baik kesalahan kalibrasi atau prediksi) yang dapat diterima

A new method for determining aflatoxins in groundnut and groundnut cake using FTIR spectroscopy with attenuated total reflectance technique

A new analytical method was developed for the determination of aflatoxins in groundnut and groundnut cakes by Fourier transform infrared (FTIR) spectroscopy using horizontal attenuated total reflectance technique. Groundnut and groundnut cake samples were used in this study. The wavelengths were selected for the four types of aflatoxins—B1, B2, G1, and G2—and the standards prepared for each by spiking some clean sample with the aflatoxins in concentrations of 0–1200 parts per billion. A partial least square regression was used to derive the calibration models for each toxin. The coefficients of determination (R2) of the calibration model were computed for the FTIR spectroscopy predicted values vs. actual values of aflatoxins in parts per billion. The R2 was found to be 0.9911, 0.9859, 0.9986, and 0.9789 for aflatoxins B1, B2, G1, and G2, respectively. Standard errors of calibration for groundnut samples were found to be 1.80, 2.03, 1.42, and 2.05 for aflatoxins B1, B2, G1, and G2, respectively. Calibration models were validated with an independent set of samples. The R2 of validation models were computed. The SD of the difference for repeatability of the FTIR method was found to be better than that of the chemical method. Based on the results obtained, FTIR spectroscopy can be a useful instrumental method for determining aflatoxins in oilseeds and oilseed cakes. With its speed and ease of data manipulation by computer software, it is a possible alternative to the standard wet chemical methods for a rapid and accurate routine determination of aflatoxin levels in food and feed

Application of FTIR spectroscopy in determining sesamol in sesame seed oil

A new analytical method was developed for determining sesamol in sesame seed oil by FTIR spectroscopy. Sesamol was also spiked at 0 to 1000 mg/kg in freshly refined, bleached, and deodorized palm olein (RBDPOo) and groundnut (peanut) oil. FTIR spectra were recorded using a transmission (NaCl) cell accessory at room temperature, and the partial least squares regression statistical method was used to derive calibration models for each oil. The standard errors of calibration were 6.07, 5.88, and 4.24 mg/100 g for sesame, RBDPOo, and groundnut oils, with coefficients of determination (R2) of 0.9947, 0.9940, and 0.9662, respectively. The calibration models were validated by the “leave-one-out” cross-validation method, and the R2 of validation, the standard errors of prediction, and SD of the differences for repeatability and accuracy were computed. Our results support the premise that FTIR spectroscopy is an efficient and accurate method for determining minor components such as sesamol in edible oils. Paper no. J10132 in JAOCS 80, 1–4 (January 2003)

Fourier Transform Infrared (FTIR) spectroscopic determination of soap residues in the refined vegetable oils

A new analytical method was developed for the determination of soap in palm and groundnut oils by FTIR spectroscopy. Soap from 0 to 80 mg/kg oil was produced in situ in the oils by adding sodium hydroxide. The FTIR spectroscopy was with a sodium chloride transmission cell, and the partial least-squares statistical method was used to calibrate a model for each oil. The accuracy of the method was comparable to that of AOCS Method Cc17-95, with coefficients of determination (R2) of 0.98 and 0.98 for both palm and groundnut oils. The standard errors of calibration were 1.84 and 1.36 for the two oils, respectively. The calibration models were cross-validated, and the R2 of cross-validation and standard errors of cross validation were computed. The standard deviation of the difference for repeatability of the FTIR method was better than that for the chemical method used for determining soap in palm and groundnut oils. With its speed and ease of data manipulation by computer software, FTIR spectroscopy is a possible alternative to the standard wet chemical methods for rapid (2 min) and accurate routine determination of soap in chemically refined vegetable oil

Multivarate calibration of fourier transform spectra in determining the malonaldehyde as a TBA reactive substance (TBARS) in palm olein

Fourier transform infrared (FTIR) spectra of palm oil samples between 2900 and 2800 cm–1 and 1800 and 1600 cm–1 were used to compare different multivariate calibration techniques for quantitative determination of their thiobarbituric acid-reactive substance (TBARS) content. Fifty spectra (in duplicate) of palm oil with TBARS values between 0 and 0.25 were used to calibrate models based on partial least squares (PLS) and principal components regression (PCR) analyses with different baselines. The methods were compared for the number of factors, coefficients of determination (R2), and accuracy of estimation. The standard errors of prediction (SEP) were calculated to compare their predictive ability. The calibrated models generated three to eight factors, R2 of 0.9414 to 0.9803, standard error of estimation (SEE) of 0.0063 to 0.0680, and SEP of 1.20 to 6.67

Analysis of potential lard adulteration in chocolate and chocolate products using fourier transform infrared spectroscopy

Fourier transform infrared (FTIR) spectroscopy, in combination with attenuated total reflectance (ATR) and partial least square (PLS) regression, was used to detect the presence of lard in chocolate formulation. The spectral bands associated with lard, cocoa butter and their blends (ranging from 0% to 15% of lard in cocoa butter) were recorded, interpreted and identified. A semi-quantitative approach is proposed to measure the percent of lard in blends on the basis of spectral data at the frequency region 4000–650 cm−1, using the equation y = 0.9225x + 0.5539. The coefficient of determination (R2) was 0.9872 with a standard error (SE) of 1.305. In this paper, the potential of FTIR spectroscopy as a rapid analytical tool for the quantitative determination of adulterants especially lard, in chocolate, is demonstrated