Journal
FOOD AND BIOPROCESS TECHNOLOGY
Volume 2, Issue 2, Pages 229-233Publisher
SPRINGER
DOI: 10.1007/s11947-008-0180-9
Keywords
Yogurt; Soluble solids content; pH value; Least squares support vector machines; Partial least squares
Categories
Funding
- National Science and Technology Support Program [2006BAD10A09]
- Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE
- Natural Science Foundation of China [30671213]
- Science and Technology Department of Zhejiang Province [2005C12029]
Ask authors/readers for more resources
Visible/near infrared spectroscopy (Vis/NIRs) technique was applied to non-destructive quantification of sugar and pH value in yogurt. Partial least squares (PLS) analysis and least squares support vector machine (LS-SVM) were implemented for calibration models. In this paper, three brands (Mengniu, Junyao, and Guangming) were set as the calibration, and the remaining two brands (Yili and Shuangfeng) were used as prediction set. In the LS-SVM model, the correlation coefficient (r), root mean square error of prediction, and bias in prediction set were 0.9427, 0.2621A degrees Brix, 1.804e-09 for soluble solids content, and 0.9208, 0.0327, and 1.094e-09 for pH, respectively. The correlation spectra corresponding to the soluble solids content and pH value of yogurt were also analyzed through PLS method. LS-SVM model was better than PLS models for the measurements of soluble solids content and pH value. The results showed that the Vis/NIRs combined with LS-SVM models could predict the soluble solids content and pH value of yogurt.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available