模型传递是近红外光谱分析技术中一个关键的共性基础技术问题, 通过在同一工作原理的两台仪器之间寻求可行的数学方法, 使得在一台仪器上建立的模型能够应用于另外一台仪器样品光谱响应的预测, 对近红外技术的实际应用具有重要意义。 以150份烤烟作为试验样品, 以两台布鲁克公司MPA近红外光谱仪, 一台热电公司Antaris近红外光谱仪作为研究对象, 通过积分球漫反射检测技术获得光谱数据。 采用一阶导数(first-order derivative, 1st Der)和标准正态变量变换（standard normal variate, SNV)对光谱数据进行处理分析, 计算不同仪器间光谱的残差值、 残差一阶矩、 残差信号概率密度和最大信噪比等参数, 并采用偏最小二乘法（partial least squares, PLS）建立烤烟总糖含量数学模型, 检验模型传递效果。 结果表明, 一阶导数具有降低残差一阶矩, 将仪器偏差信号转换为标准高斯分布的优点, 但同时会降低信噪比。 标准正态变量变换同样可以降低一阶矩, 同时可大幅度提高信噪比, 但无法将仪器偏差信号转换为标准高斯分布, 需要进一步的信号处理。 一阶导数与SNV相结合可保留两种方法的优点, 同时在一定程度上弥补每种方法单独处理的缺点, 是一种可以消除以积分球漫反射作为光谱测量方式的因仪器厂家或型号不同、 使用年限不同等原因所产生的噪声的处理方法, 可实现傅里叶型近红外光谱仪之间的模型传递效果的明显改善。

Model transfer is a key common technical problem in the near infrared spectral analysis technology. By seeking feasible mathematical methods between the two instruments that have the same working principle, we can make the model which was set up on one instrument be applied to another one. In this paper, with 150 flue-cured tobaccos as test samples, with two Bruker MPA near infrared spectrometer and one Thermo Antaris near infrared spectrometer as the research object. We obtained spectral data by integrating sphere diffuse reflectance. Processed and analyzed the spectral data by using the first derivative and standard normal variate (SNV) transformation, and calculated the value of residual error between different instruments, first moment, signal probability density and maximum signal to noise ratio(SNR) and so on. Also, we established mathematical model of total sugar content by partial least squares (PLS) to test the effect of model transfer. The results showed that first derivative could reduce the first moment and transfer the deviation between different instruments into the standard Gaussian distribution, but at the same time, it could also put SNR down. SNV could also reduce the first moment and even could do better than first derivative, and it could increase SNR significantly, but SNR could not transfer the deviation into standard Gaussian distribution, which would need other ways to make up for it. The combination method of the first derivative and SNV can retain the advantages of both, and make up for the disadvantages of individual treatment, and it can settle the model transfer problem caused by different instrument types and different using time between different instruments that work in the principle of Fourier, which is based on the integrating sphere diffuse reflectance. This method is an ideal model transfer method without the prototype.