| 无损检测10种植物叶片含水量的通用模型 |
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| 引用本文： | 郑俊波.无损检测10种植物叶片含水量的通用模型[J].浙江农业学报,2019,31(10):1717. |
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| 作者姓名： | 郑俊波 |
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| 作者单位： | 浙江省中药研究所有限公司,浙江 杭州 310023 |
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| 基金项目： | 浙江省中药研究所天台团队科技特派员项目(47) |
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| 摘 要： | 对植物叶片含水量进行快速、准确和无损检测有助于诊断植物缺水程度。以10种植物叶片为研究对象,自行设计平行板电容传感器,改进电阻测量方法,对叶片电容和电阻进行检测。采用SPSS 19.0软件对测量数据进行组内相关系数分析,验证数据的可靠性。将叶片分成训练集和测试集,用Excel软件对训练集进行回归分析,建立叶片含水量与电容、电阻的拟合模型,并利用拟合模型对测试集叶片含水量进行预测。结果表明,10种植物叶片电容测量值可靠性良好,红叶石楠和杨梅叶片电阻测量值可靠性良好,女贞、无患子、紫荆和桂花叶片电阻测量值可靠性一般,珊瑚树叶片电阻测量值可靠性较差。经Excel回归分析,决定系数R2为0.978 8,调整R2为0.977 4,P=7.85×10-37,拟合方程为Z=86.0897-628.471X-1-11.1753Y+117.2954Y·X-1,模型拟合效果良好。利用该模型对测试集叶片含水量进行预测,与烘干法比较误差值为-2.53%~1.46%。因此,该模型可以作为该10种植物叶片含水量预测的通用模型。
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| 关 键 词： | 无损检测 电容 电阻 叶片含水量 模型 |
| 收稿时间： | 2019-05-13 |
Study on general models for non-destructive inspection of leaf moisture content of 10 plants |
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| ZHENG Junbo.Study on general models for non-destructive inspection of leaf moisture content of 10 plants[J].Acta Agriculturae Zhejiangensis,2019,31(10):1717. |
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| Authors: | ZHENG Junbo |
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| Institution: | Zhejiang Research Institute of Traditional Chinese Medicine Co., Ltd., Hangzhou 310023, China |
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| Abstract: | Rapid, precise and non-destructive determination on moisture content of plant leaves have contributed to diagnosis of water deficiency. Ten plants were used as samples to detect their leaf capacitance and resistance by using the self-designed parallel-plate capacitor and improving resistance measuring method. Measured data was analyzed by SPSS 19.0 software for intraclass correlation coefficient (ICC) to verify reliability of the data. The leaves were divided into training set and test set. The training set was analyzed with Excel regression. The fitting equation was established among leaf moisture content, capacitance and resistance. The fitting equation was used to predict the leaf moisture content in the test set. It was shown that the data reliability of leaf capacitance among 10 plants was good. The data reliability of leaf resistance was good in Photinia × fraseri Dress and Myrica rubra (Lour.) S. et Zucc., and general in Ligustrum lucidum Ait., Sapindus mukorossi Gaertn, Cercis chinensis and Osmanthus sp., and poor in Viburnum odoratissinum. By Excel regression analysis, coefficient of determination (R2) was 0.978 8, adjusted R2 was 0.977 4, significant value P=7.85×10-37, fitting equation Z=86.0897-628.471X-1-11.1753Y+117.2954Y·X-1, the fitting effect of the model was good. The errors were -2.53%-1.46% compared with the drying method to predict the moisture content of test set with this model. This model could be used as a generic model to predict leaf moisture content of these 10 plants. |
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| Keywords: | non-destructive inspection capacitance resistance leaf moisture content model |
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