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通过人工模拟涝胁迫,在不同时期测定涝胁迫下白桦(Betula platyphylla)叶和茎的电阻抗图谱(electrical impedance spectroscopy,EIS)和相应叶和茎的含水量及细胞膜透性。对叶和茎EIS参数与其含水量以及细胞膜透性数据分别进行相关分析,采用单变量线性和非线性回归技术,选取部分样本数据建立涝胁迫下白桦叶和茎的含水量估测模型,并利用其余的样本对模型进行检验。用EIS法和电导法估测其耐涝时间。取得如下结果。(1)随着涝胁迫时间的延长,涝处理中白桦叶和茎的含水量均呈下降趋势。(2)涝胁迫下叶的EIS中弧顶电抗值呈降低的趋势,而茎的EIS中弧顶电抗值呈先升高,后降低的趋势。(3)涝胁迫下白桦叶和茎的含水量及细胞膜透性与部分EIS参数显著相关,并通过选取相关性最佳的EIS参数,构建了涝胁迫下叶和茎含水量的估算模型。其中,高频电阻率(r)对叶和茎含水量的估算效果最好,最佳估算模型分别为y叶=1.066 8e-0.11x和y茎=0.000 7x2+0.003 7x+0.525 4。对以上模型进行测试和检验,均取得了较为理想的预测精度,分别为84.30%和94.34%。表明可以用EIS信息估测涝胁迫下白桦叶和茎的含水量,其估算模型有较高的可靠性与普适性。(4)白桦实生苗可忍受30天以上涝害胁迫。该研究结果对利用EIS技术监测逆境下林木生理状况及生长趋势具有实用价值。
Through artificial simulated waterlogging stress, the electrical impedance spectroscopy (EIS) and corresponding leaf and stem water content and cell membrane permeability of Betula platyphylla leaves and stems were measured at different periods under waterlogging stress. Leaf and stem EIS parameters and their moisture content and membrane permeability data were analyzed separately, using univariate linear and nonlinear regression techniques, select part of the sample data to establish waterlogging under waterlogging leaf and stem water content estimation model, and use The rest of the samples tested the model. EIS method and conductivity method were used to estimate the flood time. Obtain the following results. (1) With the prolongation of waterlogging stress, the water content of leaves and stems in waterlogging all showed a decreasing trend. (2) Under the waterlogging stress, the peak resistance of EIS in the leaves tends to decrease, while the peak resistance of EIS in the stems increases first and then decreases. (3) Water content and cell membrane permeability of leaves and stems under waterlogging stress were significantly correlated with some EIS parameters. By calculating the EIS parameters with the best correlation, an estimation model of water content of leaves and stems under waterlogging stress was constructed. Among them, high-frequency resistivity (r) had the best estimation effect on leaf and stem water content. The best estimation model was y leaf = 1.066 8e-0.11x and y stem = 0.000 7x2 + 0.003 7x + 0.525 4 respectively. The above models have been tested and tested, have achieved a more satisfactory prediction accuracy, respectively 84.30% and 94.34%. It is indicated that the EIS information can be used to estimate the water content of leaves and stems under waterlogging stress. The estimation model has high reliability and universality. (4) Birch seedlings can tolerate waterlogging stress for more than 30 days. The results of this study have practical value for monitoring the physiological status and growth trend of forest trees under the stress of EIS.