PENGEMBANGAN METODE DETEKSI MINYAK KEDELAI DALAM CAMPURAN MINYAK KELAPA MURNI DENGAN SPEKTROSKOPI INFRA MERAH DAN KEMOMETRIKA

• Main Authors: Abdul Rohman, Yakoob B. Che Man
• Format: Article
• Language: English
• Published: Universitas Gadjah Mada 2012-02-01
• Series: Agritech
• Online Access: https://jurnal.ugm.ac.id/agritech/article/view/9619

Analytical Method Development for Analysis of Soybean Oil in the Mixture with Virgin Coconut Oil Using Infrared Spectroscopy and Chemometrics ABSTRAK Spektroskopi Fourier Transform Infra Merah (FTIR) yang digabung dengan kemometrika analisis diskriminan serta analisis multivariat Partial Least Square (PLS) dan Principal Component Regression (PCR) telah digunakan untuk analisis adanya minyak kedelai dalam minyak kelapa murni (Virgin Coconut Oil, VCO). Spektra infra merah yang berhubungan dengan VCO, minyak kedelai, serta campuran keduanya direkam, diinterpretasi, dan diidentifi kasi. Kombinasi daerah bilangan gelombang 1200 – 1000 dan 3025 – 2995 cm-1 digunakan untuk tujuan ini. Analisis diskriminan menunjukkan bahwa VCO murni dapat dibedakan dengan VCO yang telah ditambah dengan minyak kedelai dengan tingkat akurasi 100 %. Sementara itu, model kalibrasi PLS menggunakan spektra normal lebih terpilih untuk kuantifi kasi minyak kedelai dalam VCO dibandingkan dengan PCR dan spektra turunannya. Nilai koefi sien determinasi (R2) yang diperoleh > 0,99 dengan tingkat kesalahan (baik kesalahan kalibrasi atau prediksi) yang dapat diterima. Kata kunci: Minyak kelapa murni, minyak kedelai, kalibrasi multivariat, analisis diskriminan ABSTRACT Fourier Transform Infrared (FTIR) spectroscopy combined with the chemometrics techniques of Discriminant Analysis (DA) as well as multivariate analysis of Partial Least Square (PLS) and Principal Component Regression (PCR) has been developed for analysis of soybean oil (SO) in virgin coconut oil (VCO). The spectral bands correlated with VCO, soybean oil (SO), and their blends were scanned, interpreted, and identifi ed. The combined wavenumber regions of 1200 – 1000 and 3025 – 2995 cm-1 were used during analysis either in classifi cation using DA or in quantifi cation using PLS and PCR. DA can be successfully used for the classifi cation of VCO and that added with SO with the accuracy level of 100 %. Furthermore, PLS using FTIR normal spectra was preferred to be used for the quantifi cation of SO in VCO over PCR and the spectral derivatives. The coeffi cient of determination (R2) value obtained for the relationship between actual and FTIR predicted value of SO is higher than 0.99 with acceptable errors, either in calibration or in validation models. Keywords: Virgin coconut oil, soybean oil, multivariate calibrations, discriminant analysis