Paper
3 March 2008 Feasibility study on variety identification of rice vinegars using visible and near infrared spectroscopy and multivariate calibration
Fei Liu, Yong He, Li Wang
Author Affiliations +
Proceedings Volume 6621, International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection; 662120 (2008) https://doi.org/10.1117/12.790948
Event: International Symposium on Photoelectronic Detection and Imaging: Technology and Applications 2007, 2007, Beijing, China
Abstract
The feasibility of visible and near infrared (Vis/NIR) spectroscopy, in combination with a hybrid multivariate methods of partial least squares (PLS) analysis and BP neural network (BPNN), was investigated to identify the variety of rice vinegars with different internal qualities. Five varieties of rice vinegars were prepared and 225 samples (45 for each variety) were selected randomly for the calibration set, while 75 samples (15 for each variety) for the validation set. After some pretreatments with moving average and standard normal variate (SNV), partial least squares (PLS) analysis was implemented for the extraction of principal components (PCs), which would be used as the inputs of BP neural network (BPNN) according to their accumulative reliabilities. Finally, a PLS-BPNN model with sigmoid transfer function was achieved. The performance was validated by the 75 unknown samples in validation set. The threshold error of prediction was set as ±0.1 and an excellent precision and recognition ratio of 100% was achieved. Simultaneously, certain effective wavelengths for the identification of varieties were proposed by x-loading weights and regression coefficients. The prediction results indicated that Vis/NIR spectroscopy could be used as a rapid and high precision method for the identification of different varieties of rice vinegars.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fei Liu, Yong He, and Li Wang "Feasibility study on variety identification of rice vinegars using visible and near infrared spectroscopy and multivariate calibration", Proc. SPIE 6621, International Symposium on Photoelectronic Detection and Imaging 2007: Photoelectronic Imaging and Detection, 662120 (3 March 2008); https://doi.org/10.1117/12.790948
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KEYWORDS
Near infrared spectroscopy

Neural networks

Spectroscopy

Calibration

Visible radiation

Autoregressive models

Reliability

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