The Malaysian Journal of Analytical Sciences Vol 17 No 1 (2013): 146 – 152

 

 

 

Penentuan kualiti minyak masak dan lemak komersial menggunakan teknik kimometik

 

(Determination of Commercials Cooking Oils and Fats Using Chemometrics Methods)

 

Azwan Mat Lazim¹*, Mohd Zuli Jaafar², Phang Wei Shong¹, Suzereen Jamil¹

 

¹Pusat Pengajian Sains Kimia & Teknologi Makanan, Fakulti Sains & Teknologi,

Universiti Kebangsaan Malaysia, 43600 Bangi,Selangor, Malaysia

²Universiti Teknologi MARA, 72007 Kuala Pilah, Negeri Sembilan

 

*Corresponding author: azwani79@ukm.my

 

 

Abstrak

Dalam kajian ini, kaedah kimometrik telah digunakan bagi menentukan kualiti beberapa jenis minyak masak komersil daripada dua jenama yang berbeza. Sampel minyak masak yang telah digunakan ialah minyak zaitun, minyak bunga matahari dan mentega dalam dua keadaan yang berbeza, iaitu segar dan digoreng. Kaedah konvensional dilakukan untuk menentukan kualiti minyak, iaitu peratus asid lemak bebas, nilai iodin dan nilai peroksida. Sebanyak 12 sampel minyak telah dianalisis menggunakan spektroskopi inframerah fourier transformasi (FTIR) pada jalur 4000-400 cm^-1. Stimulasi komputer telah dilakukan berdasarkan pencaman corak FTIR dan data pencaman corak dioptimumkan kepada model analisis komponen utama (PCA) dan kuasa dua terkecil separa (PLS). Model PCA digunakan dalam kajian ini bagi membezakan sifat-sifat antara minyak komersial segar dan minyak digoreng. Kemudian model PLS digunakan untuk mendapatkan ujian pengesahan antara kedua-dua minyak. Ujian ini dapat membandingkan hasil yang diramal oleh kaedah PLS dengan nilai yang diperoleh menggunakan kaedah konvensional. Keputusan yang diperoleh menunjukkan ujian pengesahan bagi minyak komersial mempunyai nilai kecerunan graf iaitu 0.90. Ini menunjukkan kaedah kimometik adalah signifikan dengan kaedah konvensional.

 

Kata kunci : Kimometrik; kualiti minyak; PCA; PLS

 

Abstract

In this study, chemometric method has been used in determining the oil quality. The samples used were olive oil, sunflower oil and butter from two different brands. Two different conditions were applied, either it was fresh or fried. Titratio, a conventional method was used to determine free fatty acids content (FFA), iodine value (IV), and peroxide value (PV). Twelve samples were then used for analysis and their FTIR spectra were measured at 4000-400 cm^-1. The computer stimulation was used to process the data based on their pattern recognition which optimized by principal component analysis (PCA) and partial least squares (PLS). PCA model was used to distinguish the properties between fresh and fried oil. The PLS model was used to predict the value for validation test in comparison with conventional results. Results showed the validation value for fresh oil was 0.90. This indicated the chemometric method was in agreement with conventional method.

 

Keywords: Chemometric; Oil quality; PCA; PLS

 

References

1.       Sinclair, R.G., McKay, A.F., Myers, G.S. & Jones, R.N. (1952). The Infrared Absorption Spectra of Unsaturated Fatty Acids and Esters1. Journal of the American Chemical Society, 74 (10): 2578-2585.

2.       Arnold, R.G.  & Hartung, T.E. (1971). Infrared spectroscopic determination of degree of unsaturated of fats and oils. Journal of Food Science, 36 (1): 166-168.

3.       Bernard, J.L.  & Sims, L.G. (1980). IR spectroscopy for determination of total unsaturation.:

4.       Voort, F.R., Ismail, A.A., Sedman, J., Dubois, J. & Nicodemo, T. (1994). The determination of peroxide value by fourier transform infrared spectroscopy. Journal of the American Oil Chemists’ Society, 71 (9): 921-926.

5.       Ho, M.M.  & Sue, T.T., A review on the quantitative analysis of fats and oils using FTIR, M.P.O.B. (MPOB), Editor 1999. p. 30-37.

6.       Moh, M.H., Che Man, Y.B., Badlishah, B.S., Jinap, S., Saad, M.S. & Abdullah, W.J.W. (1999). Quantitative Analysis of Palm Carotene Using Fourier Transform Infrared and Near Infrared Spectroscopy. JAOCS, Journal of the American Oil Chemists Society, 76 (2): 249-254.

7.       Hussein, M.Z., Tarmizi, R.S.H., Zainal, Z., Ibrahim, R. & Badri, R.M. (1996). Preparation and characterization of active carbons from oil palm shells. Carbon, 34 (11): 1447-1453.

8.       Wesolowski, M., Suchacz, B. (2001). Classification of rapeseed and soybean oils by use of unsupervised pattern-recognition methods and neural networks. J.Anal Chem, 3 (30): 323-371.

9.       Brereton, R.G., Chemometrics: Data Analysis for the Laboratory and Chemical Plant. 2003, Chichester, UK: John Wiley & Sons, Ltd.

10.    Riccardo Leardi, A.L.G. (1998). Genetic Algorithms applied to feature selection in PLS Regression : how and when to use them. Chemometrics and Intelligent Laboratory Systems, 41: 195-207.

11.    Guillén, M.D.  & Cabo, N. (1997). Infrared spectroscopy in the study of edible oils and fats. Journal of the Science of Food and Agriculture, 75 (1): 1-11.