ANALISIS DAGING TIKUS DALAM BAKSO SAPI MENGGUNAKAN METODE SPEKTROSKOPI INFRAMERAH YANG DIKOMBINASIKAN DENGAN KEMOMETRIKA

For Indonesian community, meatball or known as bakso is one of the favorite meat based foods. In order to gain economical benefits, the substitution of beef meat with rat�s meat can happen due to the different price between rat�s meat and beef. In this present research, the feasibility of FTIR s...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: , HALIDA RAHMANIA, , Dr. Abdul Rohman, M.Si., Ap.
التنسيق: Theses and Dissertations NonPeerReviewed
منشور في: [Yogyakarta] : Universitas Gadjah Mada 2014
الموضوعات:
ETD
الوصول للمادة أونلاين:https://repository.ugm.ac.id/130360/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=70781
الوسوم: إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
المؤسسة: Universitas Gadjah Mada
الوصف
الملخص:For Indonesian community, meatball or known as bakso is one of the favorite meat based foods. In order to gain economical benefits, the substitution of beef meat with ratâ��s meat can happen due to the different price between ratâ��s meat and beef. In this present research, the feasibility of FTIR spectroscopy in combination with chemometrics of multivariate calibration based on partial least square (PLS) was used for quantitative analysis of ratâ��s meat in the binary mixture of beef in meatball formulation. Meanwhile principal component analysis (PCA) was used for classification between ratâ��s meat and beef meatballs. Rat's fat and beef fat extracted from meatball according to traditional Soxhlet method were subjected to FTIR measurements and analyzed with chemometrics PLS and PCA. Some frequency regions in mid infrared region were optimized, and finally, the frequency region 750 â�� 1000 cm-1 was selected during PLS and PCA modelling. For quantitative analysis, the relationship between actual values (x-axis) and FTIR predicted values (y-axis) is described by equation of y = 0.9417 x + 2.8410 with coefficient of determination (R2) of 0.993 and root mean square error of calibration (RMSEC) of 1.79%. Furthermore, PCA was succesfully used for classification of ratâ��s meat meatball and beef meatball.