Development of Prediction Model for Capsaicinoids Content in Red-Pepper Powder Using Near-Infrared Spectroscopy - Particle Size Effect
2011
Mo, C.Y., National Academy of Agricultural Science, RDA, Suwon, Republic of Korea | Kang, S.W., National Academy of Agricultural Science, RDA, Suwon, Republic of Korea | Lee, K.J., National Academy of Agricultural Science, RDA, Suwon, Republic of Korea | Lim, J.G., National Academy of Agricultural Science, RDA, Suwon, Republic of Korea | Cho, B.K., Chungnam National University, Daejeon, Republic of Korea | Lee, H.D., National Academy of Agricultural Science, RDA, Suwon, Republic of Korea
In this research, the near-infrared absorption from 1,100-2,300 nm was used to measure the content of capsaicinoids in the red-pepper powder by using the Acousto-optic tunable filters (AOTF) spectrometer with sample plate and sample rotating unit. Non-spicy red-pepper samples from one location (Younggwang-gun. Korea) were mixed with spicy one (var. Chungyang) to make samples separated by particle size (below 0.425 mm, 0.425-0.71 mm, and 0.71-1.4 mm). The Partial Least Squares Regression (PLSR) model to predict the capsaicinoid content on particle sizes was developed with measured spectra by AOTF spectrometer and used to analyze the amount of capsaicinoids by HPLC. The PLSR Model of red-pepper powder of below 0.425 mm, 0.425-0.71 mm, and 0.71-1.4 mm with cross validation had R∧V² = 0.948-0.979 and Standard Error of Prediction (SEP) = 6.56-7.94 mg%. The prediction error of smaller particle size of red-pepper powder was low. The best PLSR model was found in pretreatment of Range Normalization, Standard Normal Variate, and 1st Derivatives of red-pepper powder of below 1.4 mm with cross validation, having R∧V² = 0.959 and SEP = 8.82 mg%.
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