徐翔,姬业钦,陈志坚,等. 基于分焦平面偏振成像的冬青卫矛含水率快速无损检测[J]. 农业工程学报,2024,40(3):219-226. DOI: 10.11975/j.issn.1002-6819.202307204
    引用本文: 徐翔,姬业钦,陈志坚,等. 基于分焦平面偏振成像的冬青卫矛含水率快速无损检测[J]. 农业工程学报,2024,40(3):219-226. DOI: 10.11975/j.issn.1002-6819.202307204
    XU Xiang, JI Yeqin, CHEN Zhijian, et al. Rapid nondestructive detection of the moisture content of holly leaves using focal plane polarization imaging[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(3): 219-226. DOI: 10.11975/j.issn.1002-6819.202307204
    Citation: XU Xiang, JI Yeqin, CHEN Zhijian, et al. Rapid nondestructive detection of the moisture content of holly leaves using focal plane polarization imaging[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(3): 219-226. DOI: 10.11975/j.issn.1002-6819.202307204

    基于分焦平面偏振成像的冬青卫矛含水率快速无损检测

    Rapid nondestructive detection of the moisture content of holly leaves using focal plane polarization imaging

    • 摘要: 针对目前在植物含水率检测中存在的使用场景受限、含水率检测不及时等问题,该研究搭建了一套基于分焦平面偏振相机的偏振成像系统,通过对偏振成像信息的解析建立了线偏振度这一物理量与含水率的依赖关系,揭示了偏振光与植物内水分间的相互作用机理,实现了对冬青叶片含水率的快速、无损检测。结果表明:1)针对于不同月份、晴雨天气条件以及不同部位这3种不同影响因素下的冬青卫矛叶片,都可以通过线偏振度来反映其含水率情况,其统一表现为随着含水率的梯度降低,线偏振度逐渐增大;2)该研究通过采集大量的植物叶片建立预测模型,含水率与线偏振度存在较强的负相关关系,决定系数达到0.85,均方误差仅为0.45%;3)另取叶片对含水率检测模型进行验证,结果表明该模型在含水率检测的验证中均方根误差为4.53%,即可以通过线偏振度表征叶片的真实含水率。该研究成果在推动光学手段在植物健康状态检测的进程中具有应用价值。

       

      Abstract: Water has engaged in a series of activities during plant growth. Therefore, the moisture content is one of the most important indicators of plant growth. Water deficiency can lead to a decrease in the stomatal degree on the leaf surface, where the carbon dioxide can flow into the plant leaf. The resulting photosynthetic efficiency can greatly reduce the appearance, nutrition, and total biomass of forestry plants. However, it is still lacking in the rapid detection of moisture content in plants. In this study, a polarization imaging system was proposed using a split-focal plane polarization camera. Polarization images were then analyzed to establish the dependence between the linear polarization and moisture content, in order to reveal the interaction between polarized light and water in plants. The rapid and nondestructive detection was realized for the moisture content of wintergreen leaves. The specific research was as follows. 1) The holly leaves were first collected and dried in a gradient manner. The moisture content was obtained after weighing; 2) A sub-focal plane polarization system was developed to detect the polarization of the gradient-dried holly leaves; 3) A systematic investigation was carried out to clarify the influence of growth states on the moisture content of holly leaves under various months, different parts, as well as sunny or rainy weather conditions. 40 leaves were collected and then divided into 8 groups, with 5 leaves for the control in each group; 4) The holly leaves were detected for the polarization. Stokes parameters were obtained to convert into the linear polarization degrees with clear physical significance and imaging. It was found that the linear polarization degree increased gradually, as the moisture content decreased. There was a strong negative correlation between the leaf moisture content and the linear polarization degree. 5) Rapid detection of moisture content was achieved by the quantitative relationship between moisture content and linear polarization degree after fitting. The degree of linear polarization was only used to detect the moisture content of the target leaf. 6) Other holly leaves were collected and then substituted into the fitting model, in order to verify the prediction of the model. The results show that the moisture content of holly spear leaves was represented by the linear polarization degree in the three growth conditions (months, weather, and parts). Furthermore, the linear polarization degree increased gradually with the decrease in the gradient of moisture content. A prediction model was obtained using the large number of plant leaves. The correlation coefficient reached 0.85, and the MSE was only 0.45%. Verification through the leaf moisture detection system showed that the average relative error of the moisture detection system was 9.50%, and the RMSE was 4.53%. The true moisture content of the leaf was characterized by linear polarization degree. The findings can also provide optical applications in plant health detection.

       

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