Diskriminasi Kopi Lanang Menggunakan UV-Visible Spectroscopy dan Metode SIMCA

https://doi.org/10.22146/agritech.12720

Diding Suhandy(1*), Meinilwita Yulia(2), Yuichi Ogawa(3), Naoshi Kondo(4)

(1) Laboratorium Rekayasa Bioproses dan Pasca Panen, Jurusan Teknik Pertanian, Universitas Lampung, Jl. Soemantri Brojonegoro No. 1 Gedong Meneng Bandar Lampung, Lampung 35145
(2) Jurusan Teknologi Pertanian, Politeknik Negeri Lampung, Jl. Soekarno Hatta No. 10, Rajabasa Bandar Lampung, Lampung
(3) Laboratorium Bio-Sensing Engineering, Graduate School of Agriculture, Kyoto University, Sakyo ku, Kyoto 606-8502
(4) Laboratorium Bio-Sensing Engineering, Graduate School of Agriculture, Kyoto University, Sakyo ku, Kyoto 606-8502
(*) Corresponding Author

Abstract


In this research, the use of ultraviolet-visible (UV-VIS) spectral information of coffee solution in the range of 190-700 nm to classify the type of coffee into lanang and regular. The spectral data of lanang and regular coffee were acquired using UV-Vis/NIR spectrometer (JASCO Corp., Tokyo, Japan). The multivariate data analysis method, SIMCA, was used to construct the classification models which worked with the individual PCA model for each class of coffee samples. SIMCA provided the classification of the samples into one or more classes. The performance of the developed SIMCA model for each class was then evaluated in terms of its sensitivity, specificity, and accuracy. The SIMCA classification method showed that it was possible to discriminate and separate the samples into two different classes (lanang and regular coffee) satisfactory value of accuracy, sensitivity and specificity. This result could open a development of a rapid and reliable method based on UV-Vis spectra for the authentication of lanang coffee in the near future.

ABSTRAK

Pada penelitian ini kami menggunakan informasi yang terdapat dalam spektra ultraviolet-visible dari sampel larutan kopi pada panjang gelombang 190-700 nm untuk mengklasifikasi dua jenis kopi yaitu kopi lanang dan kopi biasa (kopi bukan lanang). Spektra kedua jenis kopi tersebut diambil menggunakan alat UV-Vis/NIR spektrometer (JASCO Corp., Tokyo, Jepang). Metode analisis data berpeubah banyak bernama SIMCA digunakan untuk membangun model klasifikasi jenis kopi dengan cara membangun model PCA pada setiap kelas yaitu kelas kopi lanang dan kelas kopi biasa. Model SIMCA yang dibangun kemudian digunakan untuk mengevaluasi apakah sebuah sampel termasuk ke dalam kelas tertentu atau termasuk ke dalam lebih dari satu kelas. Kualitas model klasifikasi kemudian dievaluasi menggunakan parameter accuracy, sensitivity dan specificity. Pada penelitian ini, hasil klasifikasi menggunakan model SIMCA menunjukkan bahwa proses diskriminasi kopi lanang dan kopi biasa menghasilkan nilai accuracy, sensitivity dan specificity yang sangat memuaskan. Hasil riset ini telah membuka kemungkinan pengembangan metode yang mudah dan cepat berbasis spektra UV-visible untuk proses uji keaslian kopi lanang.



Keywords


Classification model; discrimination; peaberry coffee; SIMCA; UV-Visible spectroscopy

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References

Ebrahimi-Najafabadi, H., Leardi, R., Oliveri, P., Casolino, M.C., Jalali-Heravi, M. dan Lanteri, S. (2012). Detection of addition of barley to coffee using near infrared spectroscop yand chemometric techniques. Talanta 99: 175–179.

Franca, A.S. dan Oliveira, L.S. (2008). Chemistry of defective coffee beans. Dalam: Koeffer, E.N. (ed.). Food Chemistry Research Developments, hal 105–138. Nova Science Publishers, Inc.

International Coffee Organization (2016). Total production by all exporting countries. http://www.ico.org/prices/po-production.pdf. [22 Agustus 2016].

Kumar, S., Panchariya, P.C., Prasad, P.B. dan Sharma, A.L. (2015). Non-destructive classification of Assam black tea using ultra-fast gas chromatography (UFGC) coupled with soft independent modeling of class analogy (SIMCA). Sensors and Transducers 186(3): 104–111.

Lavine, B.K. (2009). Validation of classifiers. Dalam: Walczak, B., Tauler, R. dan Brown, S. (ed.). Comprehensive chemometrics, hal 587–599. Elsevier, Oxford.

Souto, U.T.C.P., Barbosa, M.F., Dantas, H.V., Pontes, A.S., Lyra, W.S., Diniz, P.H.G.D., Araújo, M.C.U. dan Silva, E.C. (2015). Identification of adulteration in ground roasted coffees using UV–Vis spectroscopy and SPA-LDA. LWT - Food Science and Technology 63(2): 1037–1041.

Suhandy, D., Waluyo, S., Sugianti, C., Yulia, M., Iriani, R., Handayani, F.N. dan Apratiwi, N. (2016a). The feasibility of using ultraviolet-visible spectroscopy and soft independent modelling of class analogies (SIMCA) for classification of Indonesian palm civet coffee (kopi luwak). Prosiding Seminar Nasional Tempe. 28 Mei 2016. Bandar Lampung.

Suhandy, D., Waluyo, S., Sugianti, C., Yulia, M., Iriani, R., Handayani, F.N. dan Apratiwi, N. (2016b). The use of UV-Vis-NIR spectroscopy and chemometrics for identification of adulteration in ground roasted arabica coffees -investigation on the influence of particle size on spectral analysis-. Prosiding Seminar Nasional Tempe. 28 Mei 2016. Bandar Lampung.

Sundaram, J., Park, B., Kwon, Y. dan Lawrence, K.C. (2013). Surface enhanced Raman scattering (SERS) with biopolymer encapsulated silver nanosubstrates for rapid detection of foodborne pathogens. International Journal of Food Microbiology 167: 67–73.

Wahono, B. (2016). Effects of peaberry coffee on the sexual behavior and the blood testosterone levels of the male mouse (mus musculus). Proceeding of 3rd International Conference on Research, Implementation and Education of Mathematics and Science. 16–17 May 2016. Yogyakarta. Hal. B21–B25.

Wang, J., Jun, S., Bittenbender, H.C., Gautz, L. dan Li, Q.X. (2009). Fourier transform infrared spectroscopy for Kona coffee authentication. Journal of Food Science 74(5): C385–C391.





DOI: https://doi.org/10.22146/agritech.12720

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