基于OJIP曲线差异性特征的水体综合毒性表征参数构建

Characterization Parameter Construction for Comprehensive Toxicity of Water Based on Differential Features of OJIP Curve

以藻类多相瞬态叶绿素荧光动力学曲线OJIP为基础,提取曲线间距离、形状和角度特征之间的差异,进行曲线差异性度量。同时,采用K最近邻(KNN)分类算法评价并选择分类效果较好的特征组合,利用不同特征对毒性强度表征作用的贡献率分配权重进行特征融合,构建水体综合毒性表征参数PIFCD。在此基础上,以普通小球藻为受试对象,在DCMU、DBMIB、MV、马拉硫磷、克百威毒性物质胁迫下,对比现有的Fv/Fm、PI_(ABS)两种表征参数,从毒性响应、最低检测限和最高响应浓度三个方面,验证所构建PI_(FCD)参数的有效性与优越性。结果表明:PI_(FCD)对5种毒性物质均响应灵敏,与Fv/Fm相比可检测更多种类的污染物;PI_(FCD)对5种毒性物质的最低检测限分别比PI_(ABS)降低了90.34%、41.66%、81.91%、95.43%和77.66%,同时对高浓度毒性物质的检测能力更强。

The algal multiphase transient chlorophyll fluorescence kinetic curve(also known as the OJIP curve)is employed to extract differences in distance,shape,and angle features,and curve differences are thereby measured.The Knearest neighbor(KNN)classification algorithm is used to evaluate those features and select the combination of features with a better classification effect.Weights are assigned according to the contribution rates of different features to toxicity intensity characterization for feature fusion,which is followed by the construction of the characterization parameter PI_(FCD) of the comprehensive toxicity of water.Moreover,Chlorella vulgaris is adopted as the test algae species to compare PI_(FCD) with the current characterization parameters Fv/Fm and PI_(ABS)under the stress of toxic substances(DCMU,DBMIB,MV,Malathion,and Carbofuran).The effectiveness and superiority of the proposed parameter PI_(FCD) are verified from the aspects of toxicity response,minimum detection limit,and maximum response concentration.The results show that PI_(FCD) is sensitive to all the five toxic substances and can detect more kinds of pollutants than Fv/Fm.The minimum detection limits of PI_(FCD) for the five toxic substances are respectively 90.34%,41.66%,81.91%,95.43%,and 77.66%lower than those of PI_(ABS).PI_(FCD) also demonstrates a higher detection ability for high-concentration toxic substances.