Zhu Xingyue, Yu Kaixiong, Zhu Xiaofan, Su Juan, Wu Chi
Shandong Provincial Center for In-Situ Marine Sensors, Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China.
Aixsensor Co., 587 Jinghua Road, Dezhou 253500, China.
Sensors (Basel). 2021 Feb 1;21(3):965. doi: 10.3390/s21030965.
Nowadays, it is still a challenge for commercial nitrate sensors to meet the requirement of high accuracy in a complex water. Based on deep-ultraviolet spectral analysis and a regression algorithm, a different measuring method for obtaining the concentration of nitrate in seawater is proposed in this paper. The system consists of a deuterium lamp, an optical fiber splitter module, a reflection probe, temperature and salinity sensors, and a deep-ultraviolet spectrometer. The regression model based on weighted average kernel partial least squares (WA-KPLS) algorithm together with corrections for temperature and salinity (TSC) is established. After that, the seawater samples from Western Pacific and Aoshan Bay in Qingdao, China with the addition of various nitrate concentrations are studied to verify the reliability and accuracy of the method. The results show that the TSC-WA-KPLS algorithm shows the best results when compared against the multiple linear regression (MLR) and ISUS (in situ ultraviolet spectrophotometer) algorithms in the temperatures range of 4-25 °C, with RMSEP of 0.67 µmol/L for Aoshan Bay seawater and 1.08 µmol/L for Western Pacific seawater. The method proposed in this paper is suitable for measuring the nitrate concentration in seawater with higher accuracy, which could find application in the development of in-situ and real-time nitrate sensors.
如今，对于商业硝酸盐传感器而言，在复杂水体中满足高精度要求仍是一项挑战。基于深紫外光谱分析和回归算法，本文提出了一种用于获取海水中硝酸盐浓度的不同测量方法。该系统由氘灯、光纤分束器模块、反射探头、温度和盐度传感器以及深紫外光谱仪组成。建立了基于加权平均核偏最小二乘法（WA-KPLS）算法并结合温度和盐度校正（TSC）的回归模型。之后，对来自中国青岛西太平洋和鳌山湾添加了不同硝酸盐浓度的海水样本进行研究，以验证该方法的可靠性和准确性。结果表明，在4-25°C的温度范围内，与多元线性回归（MLR）和原位紫外分光光度计（ISUS）算法相比，TSC-WA-KPLS算法显示出最佳结果，鳌山湾海水的RMSEP为0.67 µmol/L，西太平洋海水的RMSEP为1.08 µmol/L。本文提出的方法适用于更高精度地测量海水中的硝酸盐浓度，可应用于原位实时硝酸盐传感器的开发。
