Aplikasi Volatilomik Berbasis SPME-GC-MS untuk Autentikasi Daging dan Bakso Sapi

Abstract

Kasus pemalsuan daging sapi dengan daging lain yang harganya lebih murah oleh oknum pedagang sering terjadi. Daging babi hutan atau celeng (Sus scrofa) yang diharamkan bagi umat Islam sering dicampurkan dengan daging sapi atau dijual sebagai daging sapi. Selain dalam bentuk daging segar, bentuk olahan daging seperti bakso daging juga tidak lepas dari kasus pemalsuan. Hal ini menyebabkan status kehalalan daging dan olahannya menjadi kritis. Berbagai metode deteksi bahan non-halal pada produk daging dan produk turunannya untuk memastikan status keaslian produk (analisis autentikasi) telah banyak dikembangkan. Hal tersebut dilakukan untuk memberikan informasi tentang kemungkinan kontaminasi oleh bahan non-halal, baik secara sengaja (penipuan) atau tidak sengaja seperti kontaminasi selama transportasi dan penyimpanan. Salah satu metode deteksi bahan non-halal yang berpotensi digunakan untuk mengungkap kasus pemalsuan daging ialah volatilomik. Volatilomik adalah analisis yang terkait deteksi, karakterisasi, dan kuantifikasi senyawa volatil. Volatilomik telah dikembangkan untuk membedakan beberapa jenis produk daging dan beberapa produk turunannya. Penelitian ini bertujuan untuk membedakan daging sapi, daging ayam, dan daging babi hutan serta olahannya berupa bakso berdasarkan profil senyawa volatilnya serta menemukan senyawa penanda dari masing-masing sampel tersebut. Identifikasi senyawa volatil dilakukan dengan SPME-GC-MS (solid phase microextraction – gas chromatography - mass spectrometry). SPME adalah metode ekstraksi senyawa volatil yang praktis, cepat, dan sensitif, yang tidak mengubah komposisi kimia volatil asli. Data yang dihasilkan dari SPME-GC-MS tersebut selanjutnya dianalisis menggunakan metode multivariat PCA (principal component analysis), OPLS-DA (orthogonal partial least square – discriminant analysis) dan PLS-DA (partial least square – discriminant analysis) dengan bantuan perangkat lunak SIMCA v.16. Hasil penelitian menunjukan bahwa daging dan bakso daging sapi, ayam, dan babi hutan dapat dibedakan berdasarkan karakteristik komponen volatilnya melalui PCA. Hasil analisis PCA juga menunjukkan sampel memiliki nilai parameter model yang baik sehingga layak dilanjutkan pada analisis pembedaan lanjut dengan OPLS-DA dan PLS-DA. OPLS-DA digunakan untuk melihat perubahan komposisi senyawa volatil yang penting dalam proses identifikasi sampel pada daging dan baksonya. Perubahan komposisi senyawa volatil teramati melalui perhitungan kurva S-plot dan plot VIP (variable importance in the projection). Senyawa aromatik seperti toluena, o-xilena, m-xilena ditemukan sebagai senyawa penanda daging segar karena berada pada posisi ujung plot bagian kelas yang diamati di S-plot serta memiliki nilai VIP>1. Senyawa-senyawa tersebut menurun intensitasnya pada sampel bakso. Dengan cara serupa, didapatkan golongan senyawa yang menjadi penanda pada bakso ialah senyawa golongan aldehida seperti heksanal dan oktadekanal. Sedangkan dengan PLS-DA didapatkan senyawa penanda atau senyawa yang memiliki koefisien korelasi tertinggi dan memiliki nilai VIP>1 dari masing-masing sampel. Senyawa yang berkorelasi positif dari hasil analisis PLS-DA pada daging sapi yaitu m-xilena, pentanal, 2-propil-1-heptanol, 5-etil dan 2-metil oktana, sedangkan pada bakso sapi yaitu 3-etil-2-metil-1,3-heksadiena, 6-metil-5-hepten-2-ol, dan (E)-2-nonenal. Benzaldehida, 2-sikloheksena-1-ol, dan (E)-2-nonenal adalah senyawa yang berkorelasi tinggi dalam pemisahan kelas sampel daging ayam. Disisi lain, diketahui bahwa 3,8-dimetildekana, 3-metil-3-butenol, dan tridekanal merupakan penanda pada bakso ayam. Senyawa volatil yang ada pada daging babi hutan yang dapat dimanfaatkan sebagai penanda ialah terpinen-4-ol, 3,5-dimetiheptana, dan heksadekana sedangkan pada bakso babi hutan dan campurannya ialah pentanal, naftalena, 11-dodekena-2-on. Model PLS-DA lainnya menunjukan keberadaan senyawa yang sangat kuat pengaruhnya sebagai senyawa pembeda sebagai penciri keberadaan bakso babi hutan murni sekaligus bakso campuran babi hutan yaitu pentanal, 1-okten-3-ol, serta 5-etil-3-(3-metil-5-fenilpirazol-1-il)- 1,2,4-triazol-4-amina.

Some cases of adulteration beef with other meats that are cheaper by unscrupulous traders still often occur. Wild boar meat (Sus scrofa), which is a non-halal product, is often mixed with beef or marketed as beef. Apart from being in the form of fresh meat, processed meat forms such as meat balls also cannot be separated from cases of counterfeiting. Finally, the halal status of meat and processed products becomes critical due to the possibility of this case. Various methods of detecting non-halal ingredients in meat products and their derivatives to ensure product authenticity status (authentication analysis) have been developed. This is done to alert people of the possibility of non-halal products being contaminated, either intentionally (fraud) or inadvertently (contamination during transit and storage). One method of detecting non-halal subtances that has the potential to be used to uncover cases of meat adulteration is volatilomics. Volatilomics is an analysis related to the detection, characterization, and quantification of volatile compounds. Volatilomics began to be developed to differentiate several types of meat products and some of their derivative products. The research was conducted using volatilomic-based SPME-GC-MS (solid phase microextraction–gas chromatography-mass spectrometry) to distinguish beef, chicken, and wild boar meat and it’s meatballs made based on their volatile compound profile and discover marker compounds from each of these samples. Identification of volatile compounds was carried out by SPME-GC-MS. SPME is a simple, sensitive and fast method of extraction of volatile compounds, which does not change the chemical composition of the original volatiles. The data generated from the SPME-GC-MS were then analyzed using the multivariate PCA (principal component analysis), OPLS-DA (orthogonal partial least square–discriminant analysis) and PLS-DA (partial least square–discriminant analysis) methods by SIMCA v.16 software. The results showed that beef, chicken, and wild boar meat and meatballs could be distinguished based on the characteristics of their volatile components through PCA. The results of the PCA analysis also show that the sample has good model parameter values so that it is feasible to continue in further differentiation analysis with OPLS-DA and PLS-DA. OPLS-DA is used to see changes in the composition of volatile compounds that are important in the identification process of samples in meat and meatballs. OPLS-DA is used to see changes in the composition of volatile compounds that are important in the identification process of samples in meat and meatballs. Changes in the composition of volatile compounds were observed through the calculation of the S-plot curve and the VIP plot (variable importance in the projection). Aromatic compounds such as toluene, o-xylene, m-xylene were found as marker compounds for fresh meat because they were located at the end of the plot of the class observed in the S-plot and had a VIP>1 value. These compounds intensity was decreased in the meatball samples. In a similar way, it was found that the group of compounds that became markers on meatballs in meatballs were aldehyde group compounds such as hexanal and octadecanal. Meanwhile, PLS-DA obtained marker compounds or compounds that have the highest correlation coefficient and have a VIP>1 value from each sample. Compounds that were positively correlated from the results of the PLS-DA analysis in beef were m-xylene, pentanal, and 5-ethyl-2-methyloctan, while in beef meatballs namely 3-ethyl-2-methyl-1,3-hexadiene, 6-methyl-5-hepten-2-ol, and (E)-2-nonenal. Benzaldehyde, 2-cyclohexene-1-ol, and (E)-2-nonenal were compounds that were highly correlated in class separation of chicken meat samples. The 3,8-dimethyldecans, 3-methyl-3-butenol, and tridecane were markers in chicken meatballs. In other hand, Terpinen-4-ol, dimethylheptane, and hexadecane were markers for wild boar meat, while pentanal, naphthalene, and 11-dodekene-2-one were markers in wild boar meatballs. and the mixture. Discriminating volatiles derived from a separate PLS-DA model pointed to a consistent 3 compounds, those are pentanal, 5-ethyl-3-(3- methyl-5-phenyl pyrazol-1-yl)-1,2,4-triazol-4-amine and 1-Octene-3-ol. These compounds were identified as significant discriminating compounds in pure wild boar meatballs and mixture meatballs.