基于近红外光谱的土壤参数快速分析系统

Development of an Analyzing System for Soil Parameters Based on NIR Spectroscopy

应用面向对象的软件开发理念开发了基于近红外光谱的土壤参数快速分析系统。系统设计了SOIL类,SOIL类的实例化对象即为具有某种特定类型、特定物理性质以及光谱特性的土壤样本。系统主要包括文件操作、光谱预处理、样品分析、建模和验证以及样品测定等子功能。系统首先接收土壤标定样本集的目标参数及光谱数据文件,并对其进行各种预处理,将处理结果显示在终端,并将建立的模型保存在模型数据库。系统通过预测土壤参数界面读取模型数据库中保存的各种模型及其参数,并将读入的待测样本光谱信息代入选定的模型,从而实现土壤参数分析功能。系统采取Visual C++6.0和Matlab7.0协同完成功能开发,并采用AccessXP来建立和管理模型数据库。

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented （OO） technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the aceurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run ou tof equipment. The parameters and spectral data files （ ＊. xls） of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their param- eters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C＋ ＋6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.