Evaluation of Chemichal Content of Desiccated Coconut Using FT-NIR Spectroscopy

Desiccated coconut is one of the leading export products of Indonesia with increasing demand. The quality of desiccated coconut is determined by chemical content of lipids and free fatty acids (FFA). The measurement of the chemical content is mostly performed by chemical methods that leave chemical residues and caused health problems. The aim of this research was to use FT-NIR spectroscopy as a rapid method to estimate chemical content of lipids and FFA in desiccated coconut. The FT-NIR spectrometer with a 1000-2500 nm wavelength range was used to measure spectra by reflectance mode from 48 samples. The reference data was performed using the chemical method. The spectra data were pre-treated using SNV, MSC, second derivative, and normalization. The partial least square regression (PLSR) was used to determine the best calibration model to predict chemical content. The best calibration model for predicting chemical content were obtained using original spectra with 16 PLS factors with the accuracy indicators of r = 0.95, SEC = 0.05 % SEP = 0.55 %, CV = 0.85 %, RPD = 3.21 and consistency 82.81 for lipids content, and r= 0.90, SEC = 0.01 %, SEP = 0.01 %, CV= 5.89 %, RPD = 2.09 and consistency of 93.18 for free fatty acids content.

[1]  Quansheng Chen,et al.  Quantitative detection of fatty acid value during storage of wheat flour based on a portable near-infrared (NIR) spectroscopy system , 2020 .

[2]  A. Gere,et al.  Predicting macronutrients and energy content of snack products using FT-NIR analysis and chemometric techniques , 2020 .

[3]  I. W. Budiastra,et al.  MODEL PENDUGAAN KANDUNGAN AIR, LEMAK DAN ASAM LEMAK BEBAS PADA TIGA PROVENAN BIJI JARAK PAGAR (Jatropha curcas L.) MENGGUNAKAN SPEKTROSKOPI INFRAMERAH DEKAT DENGAN METODE PARTIAL LEAST SQUARE (PLS) , 2020, Jurnal Penelitian Tanaman Industri.

[4]  Beata Walczak,et al.  VSN: Variable sorting for normalization , 2020 .

[5]  Kai Huang,et al.  Evaluation of moisture content in processed apple chips using NIRS and wavelength selection techniques , 2019, Infrared Physics & Technology.

[6]  E. Mohajerani,et al.  Effect of scattering nanoparticles on the curing behavior and conversion gradient of UV-curable turbid systems: two-flux Kubelka-Munk approach , 2018 .

[7]  M. Manley,et al.  Spectroscopic Technique: Near Infrared (NIR) Spectroscopy , 2018 .

[8]  Peiqiang Yu,et al.  Comparison of grating-based near-infrared (NIR) and Fourier transform mid-infrared (ATR-FT/MIR) spectroscopy based on spectral preprocessing and wavelength selection for the determination of crude protein and moisture content in wheat , 2017 .

[9]  Reinhold Carle,et al.  On-line application of near infrared (NIR) spectroscopy in food production , 2015 .

[10]  Serge Kokot,et al.  NIR spectroscopy and chemometrics for the discrimination of pure, powdered, purple sweet potatoes and their samples adulterated with the white sweet potato flour , 2015 .

[11]  David S. Moore,et al.  Handbook of spectroscopy , 2014 .

[12]  Miguel de la Guardia,et al.  Vibrational spectroscopy provides a green tool for multi-component analysis , 2010 .

[13]  Frans van den Berg,et al.  Review of the most common pre-processing techniques for near-infrared spectra , 2009 .

[14]  A. Cannas,et al.  Faecal NIRS to assess the chemical composition and the nutritive value of dairy sheep diets , 2009 .

[15]  J. De Baerdemaeker,et al.  Near Infrared Spectroscopy for Agricultural Materials: An Instrument Comparison , 2005 .

[16]  M. Otsuka,et al.  Comparative particle size determination of phenacetin bulk powder by using Kubelka–Munk theory and principal component regression analysis based on near-infrared spectroscopy , 2004 .