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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jin Huali Wang Jinshui Yan Lihui Guo Rui Luo Li |
| Copyright Year | 2011 |
| Description | Author affiliation: College of Food Science and Technology, Henan University of Technology, Zhengzhou, China, 450052 (Jin Huali; Wang Jinshui; Yan Lihui; Guo Rui; Luo Li) |
| Abstract | The 107 samples of wheat flour were scanned directly by NIRS and their protein contents were measured by Joe Dumars combustion method. The protein content model was built up using near infrared spectroscopy (NIRS) and the FOSS system as the analyzer. The influences on the model of factors, such as the mathematics methods and optics treatment methods were studied. Experimental results indicated that the optimal model was built by using the Modified partial least square (MPLS) under none scattering approach and two rank differential coefficient derivative preprocessing method, its standard deviation of cross validation (SECV) was 0.4112%, fore cast standard deviation(SEP) was 0.492%, predicted RSQ was 0.937. To sum up, the NIRS technique can realize fast detection of flour protein content and provide technical support for food regulator when they are monitoring the flour market. |
| Starting Page | 1087 |
| Ending Page | 1091 |
| File Size | 118858 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424495740 |
| e-ISBN | 9781424495771 |
| DOI | 10.1109/ICAE.2011.5943977 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-05-27 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Proteins Analytical models Chemical analysis Wheat flour Nondestructive testing NIR Predictive models Model Data models Calibration Mathematical model Protein content |
| Content Type | Text |
| Resource Type | Article |
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