具有波段选择稳定的近红外光谱法用于确定糖炼厂废水中的COD
Tao Pan1, Zenghai Chen1, Jiemei Chen1
1Key Laboratory of Optoelectronic Information and Sensing Technologies of Guangdong Higher Educational Institutes, Jinan University, Huangpu Road West 601, Tianhe District, Guangzhou 510632, China. tpan@jnu.edu.cn.
Analytical methods : advancing methods and applications
|March 7, 2026
概括
近红外 (NIR) 谱学提供了一种快速,无试剂的方法,用于确定炼糖厂废水中的化学氧需求 (COD). 这项研究确定了使用NIR进行准确的COD分析的最佳光谱区域和参数,从而实现了专门仪器的开发.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 环境科学 环境科学
背景情况:
- 化学氧气需求 (COD) 是监测废水质量的关键参数.
- 传统的COD测定方法耗时且涉及危险的试剂.
- 开发用于COD分析的快速,无试剂的方法对于有效的废水管理至关重要.
研究的目的:
- 开发一种快速,无试剂的方法来确定炼糖厂废水中的化学氧需求 (COD).
- 为了确定最佳的光谱区域和化学测量方法,以准确的基于NIR的COD分析.
- 为设计用于废水分析的专用NIR仪器提供可靠的模型.
主要方法:
- 采用近红外 (NIR) 光谱技术进行样本分析.
- 移动窗口部分最小方形 (MWPLS) 用于光谱数据建模.
- 萨维茨基-戈莱 (SG) 平滑应用于光谱数据预处理.
- 进行了严格的波段选择和模型验证.
主要成果:
- 短波NIR区域 (780nm至1100nm) 被确定为用于COD确定的信息.
- 最佳的SG光滑涉及第5次导数,第5度多项式和7个光滑点.
- 优化的波段 (808nm至964nm) 产生了25.0 mg L-1的验证根平均平方预测误差 (V-SEP) 和0.966.6的预测验证相关系数 (V-Rp).
- 开发的模型显示出良好的预测精度和稳定性.
结论:
- 与MWPLS和SG光滑相结合的NIR光谱学提供了一种可靠的方法,用于快速,无试剂的糖炼厂废水中COD的确定.
- 该研究为环境监测的便携式和专用NIR仪器的开发提供了宝贵的见解.
- 这种方法支持高效和可持续的废水处理过程.
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