Profil Metabolit Kopi Arabika Puntang Berbasis GC-MS Berdasarkan Metode Pascapanen yang Berbeda

Abstract

Indonesia memiliki berbagai kopi single origin dengan rasa dan aroma yang khas karena perbedaan profil metabolitnya. Penelitian ini bertujuan mengetahui profil metabolit dan komponen aroma kopi arabika Puntang berdasarkan perbedaan proses pascapanen menggunakan instrumen GC-MS. Data hasil analisis GC-MS diolah menggunakan MS-DIAL dan analisis kemometrik berupa analisis komponen utama (PCA) untuk melihat pengelompokkan proses pascapanennya. Hasilnya menunjukkan bahwa sejumlah 28 senyawa teridentifikasi, di antaranya 25% hidrokarbon, 18% ester, 14% alkohol, 11% asam karboksilat, 7% keton, 7% eter, 7% terpenoid, 4% alkaloid, 4% pirolina, dan 3% aldehida. PCA menunjukkan bahwa kafeina dan asam heksadekanoat sebagai metabolit penciri yang membedakan sampel menjadi tiga kelompok, yaitu kopi arabika Puntang proses natural, proses madu, dan proses cuci. Penelitian ini berhasil mengidentifikasi profil metabolit kopi arabika Puntang yang dikelompokkan berdasarkan tiga proses pascapanen berbeda menggunakan PCA.

Indonesia has various single-origin coffees with unique flavors and aromas based to the differences in metabolite profiles. This study uses GC-MS instruments to determine the metabolite profile and aroma components of Puntang Arabica coffee based on differences in post-harvest processes. The GC-MS analysis data were processed using MS-DIAL and chemometric analysis, like principal component analysis(PCA), to observe the grouping of the post-harvest processes. The results showed that 28 compounds were identified, encompassing several classes of compounds, including 25% hydrocarbons, 14% esters, 14% alcohols, 14% carboxylic acids, 7% ketones, 7% ethers, 7% terpenoids, 4% alkaloids, 4% pyrolines, and 4% aldehydes. The PCA indicated that caffeine and hexadecanoic acid are marker metabolites that differentiate the samples into three groups: natural process, honey process, and washed process Puntang Arabica coffee. The research successfully identified the metabolite profiles of Puntang Arabica coffee which was grouped based on three different post-harvest processes using PCA.