Uji Keaslian Kopi Bubuk Spesialti Arabika Gayo Aceh Menggunakan Spektroskopi UV dan Kemometrika
Diding Suhandy(1*), Meinilwita Yulia(2)
(1) Laboratorium Rekayasa Bioproses dan Pasca Panen, Jurusan Teknik Pertanian Universitas Lampung, Jl. Soemantri Brojonegoro No. 1 Gedong Meneng Bandar Lampung, Lampung, Indonesia, 35145
(2) Jurusan Teknologi Pertanian, Politeknik Negeri Lampung, Jl. Soekarno Hatta No.10 Rajabasa, Lampung 35141, Indonesia
(*) Corresponding Author
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Aboulwafa, M.M., Youssef, F.S., Gad, H.A., Sarker, S.D., Nahar, L., Al-Azizi, M.M., & Ashour, M.L. (2019). Authentication and discrimination of green tea samples using UV-Visible, FTIR and HPLC techniques coupled with chemometrics analysis. Journal of Pharmaceutical and Biomedical Analysis, 164: 653–658. https://doi.org/10.1016/j.jpba.2018.11.036.
Bansal, S., Singh, A., Mangal, M., Mangal, A.K., & Kumar, S. (2017). Food adulteration: sources, health risks, and detection methods. Critical Reviews in Food Science and Nutrition, 57(6): 1174–1189. https://doi.org/10.1080/10408398.2014.967834.
Briandet, R., Kemsley, E.K., & Wilson, R.H. (1996). Approaches to adulteration detection in instant coffees using infrared spectroscopy and chemometrics. Journal of The Science of Food and Agriculture, 71(3): 359–366.https://doi.org/10.1002/(SICI)1097-0010(199607)71:3%3C359:AID-JSFA593%3E3.0.CO;2-D.
Cunha, C.L., Luna, A.S., Oliveira, R.C.G., Xavier, G.M., Paredes, M.L.L., & Torres, A.R. (2017). Predicting the properties of biodiesel and its blends using mid-FT-IR spectroscopy and first-order multivariate calibration. Fuel, 204: 185–194. https://doi.org/10.1016/j.fuel.2017.05.057.
Dankowska, A., Domagała, A., & Kowalewski, W. (2017). Quantification of coffea arabica and coffea canephora var. robusta concentration in blends by means of synchronous fluorescence and UV-vis spectroscopies. Talanta, 172: 215–220. https://doi.org/10.1016/j.talanta.2017.05.036.
DGIP. (2020). Buku Persyaratan Indikasi Geografis. http://e-book.dgip.go.id/indikasi-geografis/?book=kopi-arabika-gayo. [1 Mei 2020].
dos Santos, C.A.T., Páscoa, R.N., Porto, P.A., Cerdeira, A.L., González-Sáiz, J.M., Pizarro, C., & Lopes, J.A. (2018). Raman spectroscopy for wine analyses: a comparison with near and mid infrared spectroscopy. Talanta, 186: 306–314. https://doi.org/10.1016/j.talanta.2018.04.075.
Ebrahimi-Najafabadi, H., Leardi, R., Oliveri, P., Chiara Casolino, M., Jalali-Heravi, M., & Lanteri, S. (2012). Detection of addition of barley to coffee using near infrared spectroscopy and chemometric techniques. Talanta, 99: 175–179. https://doi.org/10.1016/j.talanta.2012.05.036.
Fearn, T. (2002). Assessing calibrations: SEP, RPD, RER and R2. NIR News, 13(6): 12–13. https://doi:10.1255/nirn.689.
Fujioka, K., & Shibamoto, T. (2008). Chlorogenic acid and caffeine contents in various commercial brewed coffees. Food Chemistry, 106(1): 217–221. https://doi:10.1016/j.foodchem.2007.05.091.
Garcia, L.M.Z., Pauli, E.D., Cristiano, V., Camara, C.A.P., Scarminio, I.S., & Nixdorf, S.L. (2009). Chemometric evaluation of adulteration profile in coffee due to corn and husk by determining carbohydrates using HPAEC-PAD. Journal of Chromatographic Science, 47: 825–832. https://doi.org/10.1093/chromsci/47.9.825.
ICO. (2019). Total Production by All Exporting Countries. http://www.ico.org/historical/1990%20onwards/PDF/1a-total-production.pdf. [1 Mei 2020].
Luksiene, Z., Gudelis, V., Buchovec, I., & Raudeliuniene, J. (2007). Advanced high-power pulsed light device to decontaminate food from pathogens: effects on salmonella typhimurium viability in vitro. Journal of Applied Microbiology, 103(5):1545–1552. https://doi.org/10.1111/j.1365-2672.2007.03403.x.
Moreira, A.S.P., Nunes, F.M., Domingues, M.R., & Coimbra, M.A. (2012). Coffee melanoidins: structures, mechanisms of formation and potential health impacts. Food & Function, 3(9): 903–915. https://doi:10.1039/c2fo30048f.
Nolasco-Perez, I.M., Rocco, L.A.C.M., Cruz-Tirado, J.P., Pollonio, M.A.R., Barbon, S., Barbon, A.P.A.C., & Barbin, D.F. (2019). Comparison of rapid techniques for classification of ground meat. Biosystems Engineering, 183: 151–159. https://doi:10.1016/j.biosystemseng.2019.04.013.
Oliveira, R.C.S., Oliveira, L.S., Franca, A.S., & Augusti, R. (2009). Evaluation of the potential of SPME-GC-MS and chemometrics to detect adulteration of ground roasted coffee with roasted barley. Journal of Food Composition and Analysis, 22: 257–261. https://doi.org/10.1016/j.jfca.2008.10.015.
Pauli, E.D., Barbieri, F., Garcia, P.S., Madeira, T.B., Acquaro, V.R., Scarminio, I.S., Camara, C.A.P., & Nixdorf, S.L. (2014). Detection of ground roasted coffee adulteration with roasted soybean and wheat. Food Research International, 61: 112–119. https://doi.org/10.1016/j.foodres.2014.02.032.
Pizarro, C., Esteban-Díez, I., & González-Sáiz, J.M. (2007). Mixture resolution according to the percentage of robusta variety in order to detect adulteration in roasted coffee by near infrared spectroscopy. Analytica Chimica Acta, 585(2): 266–276. https://doi.org/10.1016/j.aca.2006.12.057.
Reis, N., Botelho, B.G., Franca, A.S., & Oliveira, L.S. (2017). Simultaneous detection of multiple adulterants in ground roasted coffee by ATR-FTIR spectroscopy and data fusion. Food Analytical Methods, 10(8): 2700–2709. https://doi.org/10.1007/s12161-017-0832-3.
Reis, N., Franca, A.S., & Oliveira, L.S. (2013a). Performance of diffuse reflectance infrared Fourier transform spectroscopy and chemometrics for detection of multiple adulterants in roasted and ground coffee. LWT- Food Science and Technology, 53:395–401. https://doi.org/10.1016/j.lwt.2013.04.008.
Reis, N., Franca, A.S., & Oliveira, L.S. (2013b). Quantitative evaluation of multiple adulterants in roasted coffee by diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and chemometrics. Talanta, 115:563–568. https://doi.org/10.1016/j.talanta.2013.06.004.
Ribeiro, M.V.M., Boralle, N., Pezza, H.R., Pezza, L., & Toci, A.T. (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.
Rodríguez, S.D., Gagneten, M., Farroni, A.E., Percibaldi, N.M., & Buera, M.P. (2019). FT-IR and untargeted chemometric analysis for adulterant detection in chia and sesame oils. Food Control, 105: 78–85. https://doi.org/10.1016/j.foodcont.2019.05.025.
Roshan, A-R.A., Gad, H.A., El-Ahmady, S.H., Khanbash, M.S., Abou-Shoer, M.I., & Al-Azizi, M.M. (2013). Authentication of monofloral Yemeni Sidr honey using ultraviolet spectroscopy and chemometric analysis. Journal of Agricultural and Food Chemistry, 61(32): 7722–7729. https://doi.org/10.1021/jf402280y.
Sano, E.E., Assad, E.D., Cunha, S.A.R., Correa, T.B.S., & Rodrigues, H.R. (2003). Quantifying adulteration in roast coffee powders by digital image processing. Journal of Food Quality, 26(2): 123–134. https://doi.org/10.1111/j.1745-4557.2003.tb00232.x.
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., & 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. https://doi.org/10.1016/j.lwt.2015.04.003.
Suhandy, D., Yulia, M., Ogawa, Y., & Kondo, N. (2013). Prediction of l-ascorbic acid using FTIR-ATR terahertz spectroscopy combined with interval partial least squares (iPLS) regression. Engineering in Agriculture, Environment and Food, 6(3): 111–117. https://doi.org/10.1016/S1881-8366(13)80020-1.
Suhandy, D., & Yulia, M. (2017a). The use of partial least square regression and spectral data in uv-visible region for quantification of adulteration in Indonesian palm civet coffee. International Journal of Food Science, 2017:1–7. https://doi.org/10.1155/2017/6274178.
Suhandy, D., & Yulia, M. (2017b). Peaberry coffee discrimination using uv-visible spectroscopy combined with SIMCA and PLS-DA. International Journal of Food Properties, 20(sup1): S331–S339. https://doi.org/10.1080/10942912.2017.1296861.
Suhandy, D., Yulia, M., Ogawa, Y., & Kondo, N. (2017). Diskriminasi kopi lanang menggunakan uv-visible spectroscopy dan metode SIMCA. Agritech, 37(4): 471–476. https://doi.org/10.22146/agritech.12720.
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(17): 9074–9079. https://doi.org/10.1021/jf201918a.
Widaningsih R. 2019. Outlook Kopi. Jakarta: Pusat Data dan Sistem Informasi Pertanian Sekretariat Jenderal - Kementerian Pertanian.
Williams, P. (2007). Grains and seeds. In Near-Infrared Spectroscopy in Food Science and Technology (Ozaki, Y., McClure, W.F. and Christy, A.A), John Wiley & Sons, Inc. Hoboken, N.J: 165–217.
Williams, P. (2010). The RPD statistic: A tutorial note. NIR News, 25(1): 22–26. https://doi:10.1255/nirn.1419.
Winkler-Moser, J.K., Singh, M., Rennick, K.A., Bakota, E.L., Jham, G., Liu, S.X., & Vaughn, S.F. (2015). Detection of corn adulteration in Brazilian coffee (coffea arabica) by tocopherol profiling and near-infrared (NIR) spectroscopy. Journal of Agricultural and Food Chemistry, 63(49): 10662–10668. https://doi.org/10.1021/acs.jafc.5b04777.
DOI: https://doi.org/10.22146/agritech.56451
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