The Use of Partial Least Square Regression and Spectral Data in UV-Visible Region for Quantification of Adulteration in Indonesian Palm Civet Coffee

المؤلفون المشاركون

Suhandy, Diding
Yulia, Meinilwita

المصدر

International Journal of Food Science

العدد

المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-7، 7ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2017-08-20

دولة النشر

مصر

عدد الصفحات

7

الملخص EN

Asian palm civet coffee or kopi luwak (Indonesian words for coffee and palm civet) is well known as the world’s priciest and rarest coffee.

To protect the authenticity of luwak coffee and protect consumer from luwak coffee adulteration, it is very important to develop a robust and simple method for determining the adulteration of luwak coffee.

In this research, the use of UV-Visible spectra combined with PLSR was evaluated to establish rapid and simple methods for quantification of adulteration in luwak-arabica coffee blend.

Several preprocessing methods were tested and the results show that most of the preprocessing spectra were effective in improving the quality of calibration models with the best PLS calibration model selected for Savitzky-Golay smoothing spectra which had the lowest RMSECV (0.039) and highest RPDcal value (4.64).

Using this PLS model, a prediction for quantification of luwak content was calculated and resulted in satisfactory prediction performance with high both RPDp and RER values.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Suhandy, Diding& Yulia, Meinilwita. 2017. 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،Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1166925

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Suhandy, Diding& Yulia, Meinilwita. 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 No. 2017 (2017), pp.1-7.
https://search.emarefa.net/detail/BIM-1166925

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Suhandy, Diding& Yulia, Meinilwita. 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. Vol. 2017, no. 2017, pp.1-7.
https://search.emarefa.net/detail/BIM-1166925

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1166925