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Prediction of Chemical Compositions for On-line Quality Measurement of Red Pepper Powder Using Near Infrared Reflectance Spectroscopy (NIRS) 원문보기

Food science and biotechnology, v.14 no.2 = no.62, 2005년, pp.280 - 285  

Lee, Sun-Mee (Department of Food & Nutrition, Seoul National University) ,  Kim, Su-Na (Korea Food Research Institute) ,  Park, Jae-Bok (Korea Food Research Institute) ,  Hwang, In-Kyeong (Department of Food & Nutrition, Seoul National University)

Abstract AI-Helper 아이콘AI-Helper

Applicability of near infrared reflectance spectroscopy (NIRS) was examined for quality control of red pepper powder in milling factories. Prediction of chemical composition was performed using modified partial least square (MPLS) techniques. Analysis of total 51 and 21 red pepper powder samples by ...

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제안 방법

  • The objectives of this study were to predict the chemical composition, including moisture, capsaicinoid, and total sugar contents, and color value using NIRS, and to investigate the applicability of NIRS to the on-line measurement of red pepper powder in milling factories.
  • The optimum number of MPLS factors was determined by cross validation; the best calibration equation was developed based on the highest coefficient of determination (R2) and the lowest standard error of cross-validation (SECV) to prevent over-fitting. SECV was calculated such that the number of cross-validation group was '4', and calibration by 3/4 samples in calibration set samples (n=153) and validation by others were also performed.

데이터처리

  • SECV was calculated such that the number of cross-validation group was '4', and calibration by 3/4 samples in calibration set samples (n=153) and validation by others were also performed. After establishing the equations, samples in the validation set were used to assess the prediction accuracy of the calibration equation based on the standard error of prediction (SEP), coefficient of determination (R2), and bias.
  • on dry weights. Statistical analysis was performed by ANOVA and bncan's multiple range tests (alpha = 0.05) using the SAS software (21).

이론/모형

  • Moisture content and ASTA color value Moisture content and ASTA (American Spice Trade Association) color value were determined by AOAC method (18) and ASTA-20.1 method (19), respectively. Red pepper powder (70-100 mg) was added to 100 mL acetone, and the mixture was stored at 0℃ for 4 hr with intermittent stirring.
  • NIRS Calibration for the experimental contents of red pepper powder The prediction equations for capsaicinoids contents, moisture contents, ASTA color value, and total sugar contents were developed using the modified partial least square (MPLS) regression method. For correction of the scatter effect, standard normal variation and de-trend (SNVD) mathematical procedures were applied.
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