玉米干全酒精糟(Distillers’s Dried Grains with Solubles,简称DDGS)是一种重要的蛋白质饲料原料,因乙醇生产设备和工艺类型存在较大差异,不同来源和批次玉米DDGS中氨基酸含量的差异较大。通过采集国内外不同工艺、年份和产地的具有...玉米干全酒精糟(Distillers’s Dried Grains with Solubles,简称DDGS)是一种重要的蛋白质饲料原料,因乙醇生产设备和工艺类型存在较大差异,不同来源和批次玉米DDGS中氨基酸含量的差异较大。通过采集国内外不同工艺、年份和产地的具有代表性的110份玉米DDGS样品,依据国家标准方法测定氨基酸含量,并借助光栅型光谱仪采集近红外漫反射光谱,构建了18种氨基酸的定量分析模型。研究结果显示:天冬氨酸、谷氨酸等10种氨基酸定量分析模型的决定系数在0.85~0.95,苏氨酸、丝氨酸等7种氨基酸定量分析模型的决定系数在0.73~0.82,赖氨酸定量分析模型的决定系数(0.62)最低,模型的RMSEP在0.03~0.19,可用于玉米DDGS中氨基酸含量的快速获取。展开更多
One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated ...One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated a combination of time-resolved LIBS and convolutional neural networks(CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R_c^2?=?0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network(ANN), showing R_v^2?=?0.6318 and the root mean square error of validation(RMSEV)?=?0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R_v^2?=?0.7366 and RMSEV?=?0.7855.These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K.However, due to limited calibration samples, the two-dimensional models presented over-fitting.The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R_v^2?=?0.9968 and RMSEV?=?0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.展开更多
文摘玉米干全酒精糟(Distillers’s Dried Grains with Solubles,简称DDGS)是一种重要的蛋白质饲料原料,因乙醇生产设备和工艺类型存在较大差异,不同来源和批次玉米DDGS中氨基酸含量的差异较大。通过采集国内外不同工艺、年份和产地的具有代表性的110份玉米DDGS样品,依据国家标准方法测定氨基酸含量,并借助光栅型光谱仪采集近红外漫反射光谱,构建了18种氨基酸的定量分析模型。研究结果显示:天冬氨酸、谷氨酸等10种氨基酸定量分析模型的决定系数在0.85~0.95,苏氨酸、丝氨酸等7种氨基酸定量分析模型的决定系数在0.73~0.82,赖氨酸定量分析模型的决定系数(0.62)最低,模型的RMSEP在0.03~0.19,可用于玉米DDGS中氨基酸含量的快速获取。
基金supported by National Natural Science Foundation of China (Grant No. 61505253)National Key Research and Development Plan of China (Project No. 2016YFD0200601)
文摘One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this paper investigated a combination of time-resolved LIBS and convolutional neural networks(CNNs) to improve K determination in soil. The time-resolved LIBS contained the information of both wavelength and time dimension. The spectra of wavelength dimension showed the characteristic emission lines of elements, and those of time dimension presented the plasma decay trend. The one-dimensional data of LIBS intensity from the emission line at 766.49 nm were extracted and correlated with the K concentration, showing a poor correlation of R_c^2?=?0.0967, which is caused by the matrix effect of heterogeneous soil. For the wavelength dimension, the two-dimensional data of traditional integrated LIBS were extracted and analyzed by an artificial neural network(ANN), showing R_v^2?=?0.6318 and the root mean square error of validation(RMSEV)?=?0.6234. For the time dimension, the two-dimensional data of time-decay LIBS were extracted and analyzed by ANN, showing R_v^2?=?0.7366 and RMSEV?=?0.7855.These higher determination coefficients reveal that both the non-K emission lines of wavelength dimension and the spectral decay of time dimension could assist in quantitative detection of K.However, due to limited calibration samples, the two-dimensional models presented over-fitting.The three-dimensional data of time-resolved LIBS were analyzed by CNNs, which extracted and integrated the information of both the wavelength and time dimension, showing the R_v^2?=?0.9968 and RMSEV?=?0.0785. CNN analysis of time-resolved LIBS is capable of improving the determination of K in soil.
