Using the total protein content in mycelia of oyster mushroom cultured in plate medium as the index, the spectral information in 1 000-1 799 nm region was collected to establish a quantitative prediction model for the...Using the total protein content in mycelia of oyster mushroom cultured in plate medium as the index, the spectral information in 1 000-1 799 nm region was collected to establish a quantitative prediction model for the parameters of strains through partial least squares regression combined with chemometrics. The results showed that the optimal spectral pretreatment method was the combination of Savitzky-Golay smoothing＋Savitzky-Golay derivative＋MSC＋Mean-Centefing. Parameters of the quantitative model including RC, SEC, RP, SEP, MF, SEP /SEC were all in the reasonable regions. The correlation coefficient of the real value and predictive value of the model was 0.672 63. The prediction model had better reliability, robustness and predictive effects, so it could be used for protein content detection in mycelia.展开更多
基金Supported by Natural Science Foundation of Shandong Province(ZR2015PC003)Earmarked Fund for National Edible Mushroom Industrial System Construction:Jinan Comprehensive Test Station(CARS-24)+3 种基金Agricultural Improved Variety Project of Shandong Province(2014-2017)Key Laboratory of Wastes Matrix Utilization,Ministry of AgricultureShandong Provincial Key Laboratory of Agricultural Non-point Source Pollution Control and PreventionFund of Science and(Technology Innovative Engineering of Shandong Academy of Agricultural Sciences CXGC2017A01)~~
文摘Using the total protein content in mycelia of oyster mushroom cultured in plate medium as the index, the spectral information in 1 000-1 799 nm region was collected to establish a quantitative prediction model for the parameters of strains through partial least squares regression combined with chemometrics. The results showed that the optimal spectral pretreatment method was the combination of Savitzky-Golay smoothing＋Savitzky-Golay derivative＋MSC＋Mean-Centefing. Parameters of the quantitative model including RC, SEC, RP, SEP, MF, SEP /SEC were all in the reasonable regions. The correlation coefficient of the real value and predictive value of the model was 0.672 63. The prediction model had better reliability, robustness and predictive effects, so it could be used for protein content detection in mycelia.
