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基于荧光原理的叶绿素a传感器校准方法研究
Study on Calibration Method of Chlorophyll-a Sensor Based on Fluorescence Principle
  
DOI:
中文关键词:  单一藻种  现场数据  叶绿素a  荧光  校准方法
英文关键词:single algae species  field data  chlorophyll-a  fluorescence  calibration method
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中文摘要:
      利用传感器对水体叶绿素a 浓度进行原位测量是获取实时、连续、长时间序列数据的重要手段。本文在对RBR 传感器和ECO(Environmental Characterization Optics)传感器进行原理分析和线性度、稳定性、重复性等基本性能测试的基础上,利用单一藻种培养液和2020年南海北部海域现场数据校准传感器,并对新的传感器校准系数进行验证。结果表明:两台传感器使用新系数比原出厂系数的叶绿素a 浓度测量准确度有明显提高。RBR 传感器现场数据校准系数的计算结果与叶绿素a 标准值误差最小,平均绝对误差从1.93 μg/L 减小到0.35 μg/L,平均相对误差从55.1%减小到10.9%;ECO 传感器藻液系数明显优于出厂系数和现场数据校准系数的计算结果,平均绝对误差从1.76 μg/L 减小到0.59 μg/L,平均相对误差从50.3%减小到15.1%。传感器测量准确度的提高,可为海洋环境监测、海洋生态灾害预警等工作获取真实可靠数据提供支撑。
英文摘要:
      In situ measurement of chlorophyll-a concentration by sensors is an important means to obtain real-time, continuous and long time series data. Based on the principle analysis of RBR and ECO (Environmental Characterization Optics) chlorophyll-a fluorescence sensors and basic performance tests such as linearity, stability and repeatability, this paper uses a single algae seed culture solution and field data in the northern waters of the South China Sea in 2020 to calibrate the sensors, and verifies the new sensor calibration coefficient. The results show that the accuracy of chlorophyll-a concentration measurement with the new coefficient of the two sensors is obviously improved compared with the original factory-produced coefficient. For RBR sensor, the mean absolute error decreases from 1.93 μg/L to 0.35 μg/L, and the mean relative error decreases from 55.1% to 10.9%. The algal fluid coefficient of ECO sensor is significantly better than the calculated results of factory coefficient and field data calibration coefficient.Themeanabsoluteerrordecreasesfrom1.76μg/Lto0.59 μg/L, and the mean relative error decreases from 50.3% to 15.1%. The improvement of sensor measurement accuracy can provide important data support for marine environment monitoring and marine ecological disaster early warning.
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