Estimation of wheat flour ash contents by electron spin resonance spectroscopy with partial least squares regression analysis
2016
Kameya, H. (National Food Research Institute, National Agriculture and Food Research Organization, Tsukuba-shi, Ibaraki (Japan)) | Tsuta, M. | Fujita, K. | Todoriki, S. | Sugiyama, J.
In this study, we investigated the potential utility of electron spin resonance (ESR) spectroscopy combined with multivariate analysis for the easy and rapid estimation of ash content in wheat flour. Japanese 'Kitahonami' wheat was assessed using this method. Partial least squares (PLS) regression analysis was performed using the ESR spectra and wheat quality parameters (protein content, volume weight, falling number and moisture content) as independent variables, and ash content values obtained by combustion as dependent variables. The correlation coefficient between measured and predicted ash content from the PLS regression analysis was 0.683.
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