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IJSTR >> Volume 8 - Issue 8, August 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Predicting Lipid, Caffeine And Chlorogenic Acid Contents Of Arabica Coffee Using NIRS

[Full Text]

 

AUTHOR(S)

Safrizal, Sutrisno, Lilik Pujantoro EN, Usman Ahmad, Samsudin

 

KEYWORDS

Arabica, Coffee, NIRS, Caffeine, Chlorogenic Acid, Lipid, Gayo.

 

ABSTRACT

Coffee is one the most increasingly propular baverage in the world community because it’s very distinctive taste for each region of origin of coffee, which is closely related with the special chemical composition of coffee such as caffeine, lipid and chlorogenic acid components. A Component analysis of coffee in the bean form needs to be done in order to easily classifying the quality of coffee based on its chemical composition. Some studies resulted that NIR able to predict the chemical components in some agricultural materials, such as coffee that can also be predicted its composition using NIRS that should be combined by applying several data treatments on the spectrum including Multiplicative Scatter Correction (MSC), Standard Normal Variate (SNV), Mean Normalization (MN) and the transformation group represented by Orthogonal Signal Correlation (OSC), as well as De-Trending (DT). The purpose of this study was to analyze the correlation between the NIR spectrum and the chemical composition of grinded coffee. Coffee samples were taken from the Indonesian Gayo highland, which 50 samples with 100 grams for each sample were harvested from various height of the planting and species. The samples were then prepared according to the method of Specialty Coffee Association of America (SCAA) protocol. NIRS measurements were done by using a Buchi NIRFlex N-500 spectrophotometer, while chemical components analysis were conducted using a UV-VIS spectrophotometer. The reseach analysis showed that the calibration using Partial Least Square (PLS) that combined with MN and OSC data pretreatment were found to be the best results for predict caffeine content with r value of above 0.7 and the Relative Percent Difference (RPD) value of above 2. The similar results were also found in prediticing of lipid and chlorogenic acid content with RPD values of above 2. The research concluded that NIRS can be used to predict the lipid, caffeine and chlorogenic acid content in the coffee.

 

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