Water content is crucial to plant growth. Water shortage can cause a decrease in photosynthesis and respiration efficiency during growth, directly leading to the yield of plants and crops. An accurate identification can greatly contribute to the water change of plant leaves in the early stage of water shortage and intervene rapidly. It can greatly reduce the loss of plants and crops due to water shortage. However, there is little change in the water content and no outstanding change in the plant morphology and spectral characteristics during the early stage. It is a high demand for the early identification of plant water content change at present. Two measurements can be widely used in the plant water content. One is the direct measurement (such as drying, and distillation), where the measurement accuracy is higher, generally as the standard of other methods. Another is the indirect measurement using, such as the plant stem diameter, canopy temperature, conductivity, microwave, spectroscopy, and images. In this study, a set of polarized light imaging systems was built to add the light source, and polarizer in the image detection. The polarized light imaging detection was then carried out on the holly leaves with different water content. The polarization of light that carried the multidimensional vector information was used as the information carrier to transmit more abundant information. The multi-dimensional vector that carried in the light polarization information was used to detect the different water content of holly leaves, in order to realize the early identification of water content change. The main conclusions of this study were as follows. 1) The m₁₃ and m₃₂ matrix elements in the Mueller matrix image initially reflected the change of water content of holly leaves, but there was no outstanding difference in the early stage of water content change. 2) The depolarization index image clearly showed the change in the water content of holly leaves at each stage. Specifically, the depolarization index increased with the continuous decrease of the water content of holly leaves. This was because the cells inside the leaves were dehydrated gradually, when the water content of the leaves decreased gradually, leading to the increase of multiple scattering. Thus, the overall depolarization index of leaves increased as well. 3) The mapping relationship was obtained between the water content and depolarization index as after fitting. The determination coefficient of the fitting curve was 0.95. Then, different parts of holly leaves were selected to verify the prediction model. The maximum relative error between the predicted water content and the actual was 4.90%. The polarized light imaging was achieved in the high contrast, strong background noise suppression, and more information, compared with the current commonly used image detection. Furthermore, the cells inside the leaves gradually perished in the process of continuous water loss of holly leaves, leading to the increase in the multiple scattering of light into the leaves and the increase of depolarization index. Therefore, the depolarization index can be used as an important parameter to identify the early changes in the water content of plants and crops. This finding can provide new insight for the early identification of the water changes in plants and crops. A theoretical basis can also be proved for the rapid nondestructive testing of physiological states, such as salt, acid, and fertilizer stress. Therefore, the integration degree of the system can be optimized to improve the portability of the system in the future. The wave plate can also be replaced with the liquid crystal phase retarder to improve the speed and accuracy of image acquisition. The sample database can be established to constantly optimize the improved model for better accuracy of prediction.

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.