Klasifikasi Kopi Bubuk Spesialti Kalosi dan Toraja Menggunakan UV-Visible Spectroscopy dan Metode PLS-DA

  • Diding Suhandy Jurusan Teknik Pertanian, Fakultas Pertanian, Universitas Lampung, Jl. Prof. Dr. Soemantri Brojonegoro No. 1, Bandar Lampung 35145
  • Meinilwita Yulia Jurusan Teknologi Pertanian, Politeknik Negeri Lampung, Jl. Soekarno Hatta No. 10 Rajabasa, Bandar Lampung 35141
Keywords: authentication, Kalosi coffee, PLS-DA, Toraja coffee, UV-Visible spectroscopy

Abstract

 

Specialty coffee is sold in a very expensive price. Specialty coffee is usually consumed as a single origin (without mixed with other coffee). For this reason, the detection of impurities (authentication) in specialty coffee is a very important process to be performed. In this study, UV-visible spectroscopy combined with PLS-DA method were used to discriminate between two specialty coffees from South Sulawesi (Kalosi and Toraja). A number of 100 ground roasted coffee samples were used for Kalosi and Toraja, respectively (1 gram each sample). A standard aqueous extraction procedure of the coffee samples using distilled water was performed and the spectral data of aqueous samples of Kalosi and Toraja coffee were acquired in transmittance mode using a UV-Visible spectrometer (Genesys™ 10S UV-Vis, Thermo Scientific, USA). The result showed that using PLS-DA method, all prediction samples were correctly classified into their corresponding classes with 100% rate for sensitivity, specificity, and accuracy, respectively.

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References

Assis C, Oliveira LS, Sena MM. 2018. Variable selection applied to the development of a robust method for the quantification of coffee blends using mid infrared spectroscopy. Food Analytical Methods. 11: 578-588. https://doi.org/10.1007/ s12161-017-1027-7

Bertone E, Venturello A, Giraudo A, Pellegrino G, Geobaldo F. 2016. Simultaneous determination by NIR spectroscopy of the roasting degree and Arabica/Robusta ratio in roasted and ground coffee. Food Control. 59: 683-689. https://doi.org/10.1016/ j.foodcont.2015.06.055

Botelho BG, Oliveira LS, Franca AS. 2017. Fluorescence spectroscopy as tool for the geographical discrimination of coffees produced in different regions of Minas Gerais State in Brazil. Food Control. 77: 25-31. https://doi.org/10.1016/ j.foodcont.2017.01.020

Cai T, Ting H, Jin-lan Z. 2016. Novel identification strategy for ground coffee adulteration based on UPLC–HRMS oligosaccharide profiling. Food Chemistry. 190: 1046-1049. https://doi.org/10. 1016/j.foodchem.2015.06.084

Cortésa V, Cubero S, Aleixos N, Blasco J, Talens P. 2017. Sweet and nonsweet taste discrimination of nectarines using visible and near-infrared spectroscopy. Postharvest Biology and Technology. 133 :113-120. https://doi.org/10.1016/j.postharvbio. 2017.07.015

Craig AP, Botelho BG, Oliveira LS, Franca AS. 2018. Mid infrared spectroscopy and chemometrics as tools for the classification of roasted coffees by cup quality. Food Chemistry. 245: 1052-1061. https:// doi.org/10.1016/j.foodchem.2017.11.066

Daniel D, Lopes FS, dos Santos VB, do Lago CL. 2018. Detection of coffee adulteration with soybean and corn by capillary electrophoresis-tandem mass spectrometry. Food Chemistry. 243: 305-310. https://doi.org/10.1016/j.foodchem.2017.09.140

de Santana FB, Mazivila SJ, Gontijo LC, Neto WB, Poppi RJ. 2018. Rapid discrimination between authentic and adulterated andiroba oil using FTIR-HATR spectroscopy and random forest. Food Analytical Methods. 11: 1927-1935. https://doi.org/ 10.1007/s12161-017-1142-5

DJHKI (Direktorat Jenderal Hak Kekayaan Intelektual) Kementrian Hukum dan HAM Republik Indonesia. 2018. Indikasi Geografis [internet]. [diunduh tanggal 13 Mei 2018]. Tersedia pada: http://www.dgip.go.id.

Giovenzana V, Beghi R, Tugnolo A, Brancadoro L, Guidetti R. 2018. Comparison of two immersion probes coupled with visible/near infrared spectroscopy to assess the must infection at the grape receiving area. Computers and Electronics in Agriculture. 146: 86-92. https://doi.org/10.1016/ j.compag.2018.01.017

Grasel FS, Ferrao MF. 2016. A rapid and non-invasive method for the classification of natural tannin extracts by near infrared spectroscopy and PLS-DA. Analytical Methods. 8: 644-649. https://doi.org/ 10.1039/C5AY02526E

Marquetti I, Link JV, Lemes ALG, Scholz MBS, Valderrama P, Bona E. 2016. Partial least square with discriminant analysis and near infrared spectroscopy for evaluation of geographic and genotypic origin of arabica coffee. Computers and Electronics in Agriculture. 121: 313-319. https:// doi.org/10.1016/j.compag.2015.12.018

Ozdestan O, van Ruth SM, Alewijn M, Koot A, Romano A, Cappelin L, Biasioli F. 2013. Differentiation of specialty coffees by proton transfer reaction-mass spectrometry. Food Research International. 53: 433-439. https://doi.org/10.1016/j.foodres.2013. 05.013

Pascu E. 2013. The authenticity and traceability of food-consumers protection form. Annals of Faculty of Economics. 1(1): 658-662.

Ribeiro MVM, Boralle N, Pezza HR, Pezza L, Toci AT. 2017. Authenticity of roasted coffee using 1H NMR spectroscopy. Journal of Food Composition and Analysis. 57: 24-30. https://doi.org/10.1016/ j.jfca.2016.12.004

Sanchez PM, Pauli ED, Scheel GL,Rakocevic M,Bruns RE, Scarminio IS. 2018. Irrigation and light access effects on coffea arabica l. leaves by FTIR‑chemometric analysis. Journal of The Brazilian Chemical Society. 29(1): 168-176.

Sirisomboon P, Posom, J. 2019. Online measurement of activation energy of ground bamboo using near infrared spectroscopy. Renewable Energy. 133: 480-488. https://doi.org/10.1016/j.renene.2018. 10.051

Suhandy D, Yulia M. 2017. Peaberry coffee discrimination using uv-visible spectroscopy combined with SIMCA and PLS-DA. International Journal of Food Properties. 20: S331-S339. https://doi.org/10.1080/10942912.2017.1296861

Suhandy D, Yulia M, Ogawa Y, Kondo N. 2017. Discrimination of peaberry coffee using uv-visible spectroscopy and simca method. Agritech. 37(4): 471-476. https://doi.org/10.22146/agritech.12720

Suhandy D, Waluyo S, Sugianti C, Yulia M, Iriani R, Handayani FN, Apratiwi N. 2016. 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-. Dalam: Prosiding Seminar Nasional Tempe 2016. Bandar Lampung, 28 Mei 2016. Hal:198-204.

Suhandy D, Yulia M, Ogawa Y, Kondo N. 2012. L-Ascorbic Acid Prediction in Aqueous Solution Based on FTIR-ATR Terahertz spectroscopy. Engineering in Agriculture, Environment, and Food. 5: 152-158.

Wermelinger T, D’Ambrosio L, Klopprogge B, Yeretzian C. 2011. Quantification of the robusta fraction in a coffee blend via raman spectroscopy: proof of principle. Journal of Agricultural and Food Chemistry. 59: 9074-9079. https://doi.org/ 10.1021/jf201918a

Yulia M, Suhandy D. 2017. Indonesian palm civet coffee discrimination using UV-visible spectroscopy and several chemometrics methods. Journal of Physics: Conference Series. 835: 1-6. https:// doi.org/10.1088/1742-6596/835/1/012010

Published
2019-02-13
How to Cite
SuhandyD., & YuliaM. (2019). Klasifikasi Kopi Bubuk Spesialti Kalosi dan Toraja Menggunakan UV-Visible Spectroscopy dan Metode PLS-DA. Jurnal Ilmu Pertanian Indonesia, 24(1), 73-81. https://doi.org/10.18343/jipi.24.1.73