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Development of Prediction Model for Total Dietary Fiber Content in Brown Rice by Fourier Transform-Near Infrared Spectroscopy  

Lee, Jin-Cheol (Biotechnology Industrialization Center, Dongshin University)
Yoon, Yeon-Hee (Biotechnology Industrialization Center, Dongshin University)
Kim, Sun-Min (Biotechnology Industrialization Center, Dongshin University)
Pyo, Byeong-Sik (Biotechnology Industrialization Center, Dongshin University)
Eun, Jong-Bang (Department of Food Science and Technology and Biotechnology Research Institute, Chonnam National University)
Publication Information
Korean Journal of Food Science and Technology / v.38, no.2, 2006 , pp. 165-168 More about this Journal
Abstract
Fourier transform-near infrared spectroscopy (FT-NIRS) was evaluated for determination of total dietary fiber (TDF) content of brown rice. Enzymatic-gravimetric method was suitable to obtain reference values for calibration of NIR at 1,000-2,500 nm range. Standard error of laboratory procedure ranged 0.17 to 0.72%. Partial least square (PLS) regression was used to develop the calibration equations. Regression was performed automatically using NIRCal chemometric software. Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP), showing 0.9780, 0.0636, and 0.0642, respectively. This prediction model can be used for determination of TDF in brown rice and would be useful for real-time analysis in food industry.
Keywords
FT-NIRS; TDF; brown rice; PLS; prediction model;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Chung HI, Kim HJ. Near-infrared spectroscopy: principles. Anal. Sci. Technol. 13: 1A-14A (2000)
2 Lee KO. Rice consumption and market trends of instant rice. The Monthly Food World 6: 76-82 (2005)
3 Sung CJ. Utilization and physiological activities of dietary fiber. Food Sci. Ind. 28: 2-23 (1995)
4 Williams PC, Norris KH. Qualitative applications on near-infrared reflectance spectroscopy. Vol. 15, pp 241-243. In: Near-Infrared Technology in the Agricultural and Food Industries. Williams P, Norris K (eds), AACC, St. Paul, MN, USA (1990)
5 Sato T. Application of principal-component analysis On near-infrared spectroscopic data of vegetable oils for their classification. J. Am. Oil Chem. Soc. 71: 293-298 (1994)   DOI
6 Fredstrom SB, Jung HG, Halgerson JL, Eyden CA, Slavin JL. Trial of near-infrared reflectance spectroscopy in a human fiber digestibility study. J. Agric. Food Chem. 42: 735-738 (1994)   DOI   ScienceOn
7 Moon SS, Lee KH, Cho RK. Application of near-infrared reflectance spectroscopy in quality evaluation of domestic rice. Korean J. Food Sci. Technol. 26: 718-725 (1994)
8 Cho SY, Choi, SG, Rhee C. Determination of degree of retrogradation of cooked rice by near-infrared reflectance spectroscopy. Korean J. Food Sci. Technol. 26: 579-584 (1994)   과학기술학회마을
9 Sohn MR, Cho RK. Possibility of nondestructive evaluation of pectin in apple fruit using near-infrared reflectance spectroscopy. J. Korean Soc. Hort, Sci. 41: 65-70 (2000)
10 Lee HJ, Byun SM, Kim HS. Studies on the dietary fiber of brown rice and milled rice. Korean J. Food Sci. Technol. 20: 576-584 (1988)
11 Czuchajowska Z, Szczodrak J, Pomeranz Y. Characterization and estimation of barley polysaccharides by near-infrared spectroscopy. I. Barleys, starches, and ${\beta}$-D-glucans. Cereal Chem. 69: 413-418 (1992)
12 Bae YM, Cho SI, Chun, JG. Measurement of fat content in potatochips by near-infrared spectroscopy. Korean J. Food Sci. Technol. 28: 916-921 (1996)   과학기술학회마을
13 Han CS, Natsuga MY. Development of a constituent prediction model of domestic rice using near infrared reflectance analyzer (I)-Constituent prediction model of brown and milled rice. J. Korean Soc. Agric. Mech. 21: 198-210 (1996)   과학기술학회마을
14 Reeves JB. Discriminant analysis of selected food ingredients by near infrared diffuse reflectance spectroscopy. J. Near Infrared Spectrose. 5: 209-221 (1997)   DOI
15 AOAC. Official Method of Analysis of AOAC lntl, 17th ed. Method 985.29. Association of Official Analytical Chemists International, Gaithersburg, MD, USA (2000)
16 Choi JS, Ahn HH, Nam HJ. Comparison of nutritional composition in Korean rices. J. Korean Soc. Food Sci. Nutr, 31: 885-892 (2002)   과학기술학회마을   DOI
17 Cho HJ, Ha YL. Determination of honey quality by near infrared spectroscopy. Korean J. Food Sci. Technol. 34: 356-360 (2002)   과학기술학회마을
18 Harris SS. Health claims for foods in the international market. Food Technol. 46: 92-92 (1992)
19 Kim YB. Utilization on the near-infrared (NIR) for the chemical composition analysis of foods (I). Food Technol. 9: 24-37 (1996)
20 ASTM. Standard practices for infrared, multi-variate, quantitative analysis. Vol. 03.06, Doc. E1655-94. In: American Society of Testing and Materials Annual book of standards. ASTM, West Conshohochen, PA, USA (1995)
21 Kim BJ, Park EH, Suh HS. Use of near infrared reflection spectroscopy for determination of grain components in barley. Korean J. Crop Sci. 40: 716-722 (1995)   과학기술학회마을
22 Szczodrak J, Czuchajowska Z, Pomeranz Y. Characterization and estimation of barley polysaccharides by near-infrared spectroscopy. II. Estimation of total ${\beta}$-D-glucans. Cereal Chem. 69: 419-423 (1992b)
23 Kim YH, Kang CS, Lee YS. Quantification of tocopherol and tocotrienol content in rice bran by near infrared reflectance spectroscopy. Korean J. Crop Sci. 49: 211-215 (2004)
24 Kim EH, Maeng YS, Woo SJ. Dietary fiber contents in some cereals and pulses. Korean J. Nutr. 26: 98-106 (1993)   과학기술학회마을
25 Chae JC, Jung MS, Jun DK, Son YM. Relationship between yield and quality of rice varieties grown in reclaimed saline paddy field. Korean J. Crop Sci. 47: 259-262 (2002)