|
|||||
|
|
Artificial neural network for quantitative determination of total protein in yogurt by infrared spectrometry |
|
| Authors: | Mohammadreza Khanmohammadi Amir Bagheri Garmarudi Keyvan Ghasemi Miguel de la Guardia |
| Affiliation: | a Department of Chemistry, Faculty of Science, Imam Khomeini International University, Qazvin, Iran b Department of Chemistry & Polymer Laboratories, Engineering Research Institute, Tehran, Iran c Analytical Chemistry Department, Universitat de Valencia, Jerònim Muñoz building, C/Dr. Moliner, 50, 46100 Burjassot, Valencia, Spain |
| Abstract: | A method has been introduced for quantitative determination of protein content in yogurt samples based on the characteristic absorbance of protein in 1800-1500 cm− 1 spectral region by mid-FTIR spectroscopy and chemometrics. Successive Projection Algorithm (SPA) wavelength selection procedure, coupled with feed forward Back-Propagation Artificial Neural Network (BP-ANN) model was the benefited chemometric technique. Relative Error of Prediction (REP) in BP-ANN and SPA-BP-ANN methods for training set was 7.25 and 3.70 respectively. Considering the complexity of the sample, the ANN model was found to be reliable, while the proposed method is rapid and simple, without any sample preparation step. |
| Keywords: | Yogurt Protein content ATR-FTIR Artificial neural network Back propagation Successive Projection Algorithm |
| 本文献已被 ScienceDirect 等数据库收录！ | |