Displaying all 13 publications

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  1. Rohman, A., Che Man, Y.B.
    MyJurnal
    Two functional food oils, namely extra virgin olive oil (EVOO) and virgin coconut oil (VCO) have been analyzed simultaneously using Fourier transform infrared (FTIR) spectroscopy. The performance of multivariate calibration of principle component regression (PCR) and partial least square regression (PLSR) was evaluated in order to give the best prediction model for such determination. FTIR spectra were treated with several treatments including mean centering (MC), derivatization, and standard normal variate (SNV) at the combined frequency regions of 3050 – 3000, 1660 – 1650, and 1200 – 900 cm-1. Based on its capability to give the highest values of coefficient of correlation (R) for the relationship between actual value of EVOO/VCO and FTIR predicted value together with the lowest values of root mean square error of calibration (RMSEC), PLSR with mean centered-first derivative spectra was chosen for simultaneous determination of EVOO and VCO. It can be concluded that FTIR spectroscopy combined with multivariate calibration of PLSR was successfully applied to simultaneously quantify EVOO and VCO with acceptable parameters.
  2. Rohman, A., Sugeng, R., Che Man, Y.B.
    MyJurnal
    The present study was carried out to characterize red fruit (Pandanus conoideus Lam) oil (RFO) in term of FTIR spectra, fatty acid composition, and volatile compounds. FTIR spectrum of RFO was slightly
    different from other common vegetable oils and animal fats, in which in the frequency range of 1750 – 1700 cm-1, RFO appear two bands. The main fatty acid composition of RFO is oleic acid accounting for 68.80% followed by linoleic acid with the concentration of 8.49%. The main volatile compounds of RFO as determined using gas chromatography coupled with mass spectrometry (GC-MS) and headspace analyser are 1,3-dimethylbenzene (27.46%), N-glycyl- L-alanine (17.36%), trichloromethane (15.22%), and ethane (11.43%).
  3. Rohman, A., Che Man, Y.B., Ismail, A., Puziah, H.
    MyJurnal
    FTIR spectroscopy in combination with multivariate calibrations, i.e. partial least square (PLS) and principle component regression (PCR) was developed for quantitative analysis of cod liver oil (CLO) in binary mixture with corn oil (CO). The spectra of CLO, CO and their blends with certain concentrations were scanned using horizontal attenuated total reflectance (HATR) accessory at mid infrared (MIR) region of 4,000 – 650 cm-1. The optimal spectral treatments selected for calibration models were based on its ability to provide the highest values of coefficient of determination (R2) and the lowest values of root mean error of calibration (RMSEC). PLS was slightly well suited for quantitative analysis of CLO compared to PCR. FTIR spectroscopy in combination with multivariate calibration offers rapid, no excessive chemical reagent, and easy in operational to be applied for determination of CLO in binary mixture with other oils.
  4. Rohman A, Man YC, Sismindari
    Pak J Pharm Sci, 2009 Oct;22(4):415-20.
    PMID: 19783522
    Today, virgin coconut oil (VCO) is becoming valuable oil and is receiving an attractive topic for researchers because of its several biological activities. In cosmetics industry, VCO is excellent material which functions as a skin moisturizer and softener. Therefore, it is important to develop a quantitative analytical method offering a fast and reliable technique. Fourier transform infrared (FTIR) spectroscopy with sample handling technique of attenuated total reflectance (ATR) can be successfully used to analyze VCO quantitatively in cream cosmetic preparations. A multivariate analysis using calibration of partial least square (PLS) model revealed the good relationship between actual value and FTIR-predicted value of VCO with coefficient of determination (R2) of 0.998.
  5. Nurrulhidayah, A.F., Che Man, Y.B., Shuhaimi, M., Rohman, A., Khatib, A., Amin, I.
    MyJurnal
    The use of Fourier transform infrared (FTIR) spectroscopy coupled with chemometric techniques to differentiate butter from beef fat (BF) was investigated. The spectral bands associated with butter, BF, and their mixtures were scanned, interpreted, and identified by relating them to those spectroscopically representative to pure butter and BF. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the selected fingerprint regions of 1500-1000 cm-1, with the values of coefficient of determination (R2) and root mean square error of calibration (RMSEC) are 0.999 and 0.89% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with BF. Using 6 principal components, root mean square error of prediction (RMSEP) is 2.42% (v/v). These results proved that FTIR spectroscopy in combination with multivariate calibration can be used for the detection and quantification of BF in butter formulation for authentication use.
  6. Nurrulhidayah, A.F., Arieff, S.R., Rohman, A., Amin, I., Shuhaimi, M., Khatib, A.
    MyJurnal
    Differential scanning calorimetry (DSC) is developed and used for detection of butter adulteration with lard. Butter has the similar characteristics to lard makes lard a desirable adulterant in butter. DSC provides unique thermal profiling for lard and butter. In the heating thermogram of the mixture, there was one major endothermic peak (peak A) with a smaller shoulder peak embedded in the major peak that gradually smoothed out to the major peak as the lard percent increased. In the cooling thermogram, there were one minor peak (peak B) and two major exothermic peaks, peak C which increased as lard percent increased and peak D which decreased in size as the lard percent increased. From Stepwise Multiple Linear Regression (SMLR) analysis, two independent variables were found to be able to predict lard percent adulteration in butter with R2 (adjusted) of 95.82. The SMLR equation of lard percent adulteration in butter is 293.1 - 11.36 (Te A) - 2.17 (Tr D); where Te A is the endset of peak A and Tr D is the range of thermal transition for peak D. These parameters can serve as a good measurement parameter in detecting lard adulteration in butter. DSC is a very useful means for halal screening technique to enhance the authenticity of Halal process.
  7. Rohman A, Ariani R
    ScientificWorldJournal, 2013;2013:740142.
    PMID: 24319381 DOI: 10.1155/2013/740142
    Fourier transform infrared spectroscopy (FTIR) combined with multivariate calibration of partial least square (PLS) was developed and optimized for the analysis of Nigella seed oil (NSO) in binary and ternary mixtures with corn oil (CO) and soybean oil (SO). Based on PLS modeling performed, quantitative analysis of NSO in binary mixtures with CO carried out using the second derivative FTIR spectra at combined frequencies of 2977-3028, 1666-1739, and 740-1446 cm(-1) revealed the highest value of coefficient of determination (R (2), 0.9984) and the lowest value of root mean square error of calibration (RMSEC, 1.34% v/v). NSO in binary mixtures with SO is successfully determined at the combined frequencies of 2985-3024 and 752-1755 cm(-1) using the first derivative FTIR spectra with R (2) and RMSEC values of 0.9970 and 0.47% v/v, respectively. Meanwhile, the second derivative FTIR spectra at the combined frequencies of 2977-3028 cm(-1), 1666-1739 cm(-1), and 740-1446 cm(-1) were selected for quantitative analysis of NSO in ternary mixture with CO and SO with R (2) and RMSEC values of 0.9993 and 0.86% v/v, respectively. The results showed that FTIR spectrophotometry is an accurate technique for the quantitative analysis of NSO in binary and ternary mixtures with CO and SO.
  8. Rohman A, Che Man YB
    Food Chem, 2011 Nov 15;129(2):583-588.
    PMID: 30634271 DOI: 10.1016/j.foodchem.2011.04.070
    Currently, the authentication of virgin coconut oil (VCO) has become very important due to the possible adulteration of VCO with cheaper plant oils such as corn (CO) and sunflower (SFO) oils. Methods involving Fourier transform mid infrared (FT-MIR) spectroscopy combined with chemometrics techniques (partial least square (PLS) and discriminant analysis (DA)) were developed for quantification and classification of CO and SFO in VCO. MIR spectra of oil samples were recorded at frequency regions of 4000-650cm-1 on horizontal attenuated total reflectance (HATR) attachment of FTIR. DA can successfully classify VCO and that adulterated with CO and SFO using 10 principal components. Furthermore, PLS model correlates the actual and FTIR estimated values of oil adulterants (CO and SFO) with coefficient of determination (R2) of 0.999.
  9. Rohman A, Man YB, Riyanto S
    Phytochem Anal, 2011 Sep-Oct;22(5):462-7.
    PMID: 22033916 DOI: 10.1002/pca.1304
    Red fruit (Pandanus conoideus Lam) is endemic plant of Papua, Indonesia and Papua New Guinea. The price of its oil (red fruit oil, RFO) is 10-15 times higher than that of common vegetable oils; consequently, RFO is subjected to adulteration with lower price oils. Among common vegetable oils, canola oil (CaO) and rice bran oil (RBO) have similar fatty acid profiles to RFO as indicated by the score plot of principal component analysis; therefore, CaO and RBO are potential adulterants in RFO.
  10. Fadzlillah NA, Rohman A, Ismail A, Mustafa S, Khatib A
    J Oleo Sci, 2013;62(8):555-62.
    PMID: 23985484
    In dairy product sector, butter is one of the potential sources of fat soluble vitamins, namely vitamin A, D, E, K; consequently, butter is taken into account as high valuable price from other dairy products. This fact has attracted unscrupulous market players to blind butter with other animal fats to gain economic profit. Animal fats like mutton fat (MF) are potential to be mixed with butter due to the similarity in terms of fatty acid composition. This study focused on the application of FTIR-ATR spectroscopy in conjunction with chemometrics for classification and quantification of MF as adulterant in butter. The FTIR spectral region of 3910-710 cm⁻¹ was used for classification between butter and butter blended with MF at various concentrations with the aid of discriminant analysis (DA). DA is able to classify butter and adulterated butter without any mistakenly grouped. For quantitative analysis, partial least square (PLS) regression was used to develop a calibration model at the frequency regions of 3910-710 cm⁻¹. The equation obtained for the relationship between actual value of MF and FTIR predicted values of MF in PLS calibration model was y = 0.998x + 1.033, with the values of coefficient of determination (R²) and root mean square error of calibration are 0.998 and 0.046% (v/v), respectively. The PLS calibration model was subsequently used for the prediction of independent samples containing butter in the binary mixtures with MF. Using 9 principal components, root mean square error of prediction (RMSEP) is 1.68% (v/v). The results showed that FTIR spectroscopy can be used for the classification and quantification of MF in butter formulation for verification purposes.
  11. Fadzillah NA, Man Yb, Rohman A, Rosman AS, Ismail A, Mustafa S, et al.
    J Oleo Sci, 2015;64(7):697-703.
    PMID: 25994556 DOI: 10.5650/jos.ess14255
    The authentication of food products from the presence of non-allowed components for certain religion like lard is very important. In this study, we used proton Nuclear Magnetic Resonance ((1)H-NMR) spectroscopy for the analysis of butter adulterated with lard by simultaneously quantification of all proton bearing compounds, and consequently all relevant sample classes. Since the spectra obtained were too complex to be analyzed visually by the naked eyes, the classification of spectra was carried out.The multivariate calibration of partial least square (PLS) regression was used for modelling the relationship between actual value of lard and predicted value. The model yielded a highest regression coefficient (R(2)) of 0.998 and the lowest root mean square error calibration (RMSEC) of 0.0091% and root mean square error prediction (RMSEP) of 0.0090, respectively. Cross validation testing evaluates the predictive power of the model. PLS model was shown as good models as the intercept of R(2)Y and Q(2)Y were 0.0853 and -0.309, respectively.
  12. Aina GQ, Erwanto Y, Hossain M, Johan MR, Ali ME, Rohman A
    J Adv Vet Anim Res, 2019 Sep;6(3):300-307.
    PMID: 31583226 DOI: 10.5455/javar.2019.f348
    Objective: The objective of this study was to employ real-time or quantitative polymerase chain reaction (q-PCR) using novel species specific primer (SSP) targeting on mitochondrial cytochrome-b of wild boar species (CYTBWB2-wb) gene for the identification of non-halal meat of wild boar meat (WBM) in meatball products.

    Materials and Methods: The novel SSP of CYTBWB2-wb was designed by our group using PRIMERQUEST and NCBI software. DNA was extracted using propanol-chloroform-isoamyl alcohol method. The designed SSP was further subjected for validation protocols using DNA isolated from fresh meat and from meatball, which include specificity test, determination of efficiency, limit of detection and repeatability, and application of developed method for analysis of commercially meatball samples.

    Results: The results showed that CYTBWB2-wb was specific to wild boar species against other animal species with optimized annealing temperature of 59°C. The efficiency of q-PCR obtained was 91.9% which is acceptable according to the Codex Allimentarius Commission (2010). DNA, with as low as 5 pg/μl, could be detected using q-PCR with primer of CYTBWB2-wb. The developed method was also used for DNA analysis extracted from meatball samples commercially available.

    Conclusion: q-PCR using CYTBWB2-wb primers targeting on mitochondrial cytochrome-b gene (forward: CGG TTC CCT CTT AGG CAT TT; Reverse: GGA TGA ACA GGC AGA TGA AGA) can be fruitfully used for the analysis of WBM in commercial meatball samples.

  13. Hossain MAM, Uddin SMK, Chowdhury ZZ, Sultana S, Johan MR, Rohman A, et al.
    PMID: 30865559 DOI: 10.1080/19440049.2019.1580389
    Mislabelling in fish products is a highly significant emerging issue in world fish trade in terms of health and economic concerns. DNA barcoding is an efficient sequencing-based tool for detecting fish species substitution but due to DNA degradation, it is in many cases difficult to amplify PCR products of the full-length barcode marker (~650 bp), especially in severely processed products. In the present study, a pair of universal primers targeting a 198 bp sequence of the mitochondrial 16s rRNA gene was designed for identification of fish species in the processed fish products commonly consumed in Malaysia. The specificity of the universal primers was tested by both in-silico studies using bioinformatics software and through cross-reaction assessment by practical PCR experiments against the DNA from 38 fish species and 22 other non-target species (animals and plants) and found to be specific for all the tested fish species. To eliminate the possibility of any false-negative detection, eukaryotic endogenous control was used during specificity evaluation. The developed primer set was validated with various heat-treated (boiled, autoclaved and microwaved) fish samples and was found to show high stability under all processing conditions. The newly developed marker successfully identified 92% of the tested commercial fish products with 96-100% sequence similarities. This study reveals a considerable degree of species mislabelling (20.8%); 5 out of 24 fish products were found to be mislabelled. The new marker developed in this work is a reliable tool to identify fish species even in highly processed products and might be useful in detecting fish species substitution thus protecting consumers' health and economic interests.
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