Chauchard F, Roger J M, Bellon-Maurel V, Abrahamsson C, Andersson-Engels S, Svanberg S
Information and Technologies for Agro-processes, Cemagref BP 5095, 34033 Montpellier Cedex 1, France.
Appl Spectrosc. 2005 Oct;59(10):1229-35. doi: 10.1366/000370205774430828.
Time-resolved spectroscopy is a powerful technique permitting the separation of the scattering properties from the chemical absorption properties of a sample. The reduced scattering coefficient and the absorption coefficient are usually obtained by fitting diffusion or Monte Carlo models to the measured data using numerical optimization techniques. However, these methods do not take the spectral dimension of the data into account during the evaluation procedure, but evaluate each wavelength separately. A procedure involving multivariate methods may seem more appealing for people used to handling conventional near-infrared data. In this study we present a new method for processing TRS spectra in order to compute the absorption and reduced scattering coefficients. This approach, MADSTRESS, is based on linear regression and a two-dimensional (2D) interpolation procedure. The method has allowed us to calculate absorption and scattering coefficients of apples and fructose powder. The accuracy of the method was good enough to provide the identification of fructose absorption peaks in apple absorption spectra and the construction of a calibration model predicting the sugar content of apples.
时间分辨光谱学是一种强大的技术，它能够将样品的散射特性与化学吸收特性分离开来。通常使用数值优化技术，通过将扩散或蒙特卡罗模型拟合到测量数据来获得约化散射系数和吸收系数。然而，这些方法在评估过程中并未考虑数据的光谱维度，而是分别对每个波长进行评估。对于习惯处理传统近红外数据的人来说，涉及多变量方法的程序可能更具吸引力。在本研究中，我们提出了一种处理时间分辨光谱（TRS）的新方法，以计算吸收系数和约化散射系数。这种方法，即MADSTRESS，基于线性回归和二维（2D）插值程序。该方法使我们能够计算苹果和果糖粉末的吸收系数和散射系数。该方法的准确性足以识别苹果吸收光谱中的果糖吸收峰，并构建预测苹果糖分含量的校准模型。
