农产品近红外光谱品质检测软件系统的设计与实现

在中国加入WTO后，利用近红外光谱技术进行快速、准确的农产品品质检测技术与方法研究非常迫切，为满足对样品组分定量预测软件的需求，设计并实现了农产品近红外光谱品质检测软件系统。采用了面向对象编程技术，向量、矩阵运算的封装技术，结构化存储与复合文档等软件实现技术。该系统由光谱文件管理，光谱显示，光谱信号处理(预处理)，光谱校正模型的建立与管理，未知样品的组分浓度预测等五大功能模块构成。具有多种光谱仪器光谱格式(SPC、TXT、JWS、MAT、ASF等)兼容性，光谱分析功能全面性，算法(PCR、PLS、GA、ANN、Wavelet、Wavelet Package等)多样性，软件系统易维护性，用户使用操作方便性等特点。实例分析表明，无论采用本系统的PLS-NIR模型，还是采用本系统的PCA-MBP-NIR模型，组分浓度预测精度均很高。本系统为农产品品质检测近红外光谱建模和预测提供了很好的技术支持，具有重要的应用价值。

Design and implementation of near infrared spectroscopy analysis software system for agricultural product quality detection

After China's entry into the WTO, it becomes more and more urgent to study fast and precise agricultural product quality detection technology and method based on Near Infrared Spectroscopy Analysis(NIR). A NIR software system for agricultural product quality detection is developed to meet the need for quantitative software to predict constituent concentration. Some software implementation technology is adopted, such as object-oriented programming technology, vector-matrix encapsulation technology, structured storage and compound file technology, and so on. This system is composed of five functional modules, spectrum file management, spectrum displaying, spectrum pre-processing, calibration model building and management, unknown sample constituent concentration predicting, and so on. In this system, many spectral formats, such as SPC, TXT, JWS, MAT, ASF, are compatible, function and algorithms, such as PCR, PLS, GA, ANN, Wavelet, Wavelet Package, are provided. The system is of stability and security, and can be maintained and used easily. The case analysis shows that, the prediction results of PLS-NIR model and PCA-MBP-NIR model of this system are all very precise. The system is very useful, and provides very good technological support for building NIR model and concentration prediction in agricultural product quality detection.