The Dunhuang murals are a precious treasure of China's cultural heritage, yet they have long been affected by salt damage. Traditional methods for detecting salt content are costly, inefficient, and may cause physical harm to the murals. Among current techniques for measuring salt content in murals, hyperspectral remote sensing technology offers a non-invasive, circumventing issues of high costs, low efficiency. Building on this, the study constructs an inversion model for the Electrical Conductivity (EC) values of mural plaster subjected to phosphate erosion, through the integration of Fractional Order Differentiation (FOD), a novel three-band spectral index, and the Partial Least Squares Regression algorithm. The specific research contents include: (1) Initially, in preparation for the experiments, the materials used to create the samples underwent a rigorous desalting process, and phosphate solutions were prepared using deionized water to ensure uniform experimental conditions and the accuracy of the results. These meticulous preprocessing steps guaranteed that the measured EC values exhibited a clear correlation with the phosphate content. Subsequently, by employing qualitative experimental analysis techniques, this study was able to more accurately simulate the real-world scenarios of mural plaster affected by salt damage, enabling a deeper investigation into the mechanisms by which salts inflict microscopic damage to murals. (2) Explores the absorption mechanisms and characteristic spectral bands of the Electrical Conductivity (EC) values measured after the phosphate erosion of mural plaster. By integrating the optimal spectral indices, a univariate linear regression model is constructed, providing a basis for the rapid quantitative measurement of electrical conductivity in murals. (3) By comparing the accuracy of the Phosphate Simple Ratio (PSR) and Phosphate Normalized Difference Index (PNDI) spectral indices based on the linear regression model, the first six orders of the highest accuracy spectral index were selected as the optimal three-band spectral index combination, used as explanatory variables, with mural plaster electrical conductivity as the response variable, employing the PLSR method to construct the mural phosphate content high-spectral feature inversion model. The study's findings include: (1) Surfaces of samples deteriorated by phosphate erosion formed numerous irregularly shaped crystal clusters, exhibiting uneven characteristics. (2) By comparing the outcomes of different orders of fractional differentiation, it was found that the model performance reached its optimum at a 0.3 order of differentiation for both PSR and PNDI data, with a determination coefficient (Q2) of 0.728. (3) Utilizing PLSR, this study employed the previously determined optimal six-order three-band spectral index combination as explanatory variables, with salt content as the response variable, successfully constructing the high-spectral feature inversion model for mural electrical conductivity with a determination coefficient (Q2) of 0.815. This provides an effective technical means for monitoring the salt damage conditions of precious cultural heritage such as murals.

Terracotta figurines excavated from archaeological sites frequently exhibit salt damage due to moisture -salt transport. Understanding this dynamic within the terracotta figurines and soil system is essential for accurately predicting salt damage and implementing well-informed, timely preventative measures. While moisturesalt transport in the soils of historical sites is well -documented, the numerical modeling of this process is rare, specifically within the Terracotta figurines -soil coupled system. In the present work, a numerical model focused on the Terracotta figurine -soil system at Emperor Qin's Mausoleum Museum (China) was established, which employed the variable saturation Richards flow equation and the Fickian advection-diffusion equation. The model was validated using soil column experiments. The results showed that the semi -buried figurines were more susceptible to salt damage, with uneven salt distribution primarily due to moisture -salt transport at the interface. After the excavation, the first month was identified as a critical period for rapid migration of moisture and salt, representing the highest risk of damage. These insights offer a framework for estimating the risk of salt damage over time, underpinning the development of future abatement strategies. This study not only advances the understanding of salt damage in Terracotta figurines but also lays the groundwork for safeguarding these archaeological treasures.

The increasing global phenomenon of soil salinization has prompted heightened interest in the physiological ecology of plant salt and alkali tolerance. Halostachys caspica belonging to Amaranthaceae, an exceptionally salt-tolerant halophyte, is widely distributed in the arid and saline-alkali regions of Xinjiang, in Northwest China. Soil salinization and alkalinization frequently co-occur in nature, but very few studies focus on the interactive effects of various salt and alkali stress on plants. In this study, the impacts on the H. caspica seed germination, germination recovery and seedling growth were investigated under the salt and alkali stress. The results showed that the seed germination percentage was not significantly reduced at low salinity at pH 5.30-9.60, but decreased with elevated salt concentration and pH. Immediately after, salt was removed, ungerminated seeds under high salt concentration treatment exhibited a higher recovery germination percentage, indicating seed germination of H. caspica was inhibited under the condition of high salt-alkali stress. Stepwise regression analysis indicated that, at the same salt concentrations, alkaline salts exerted a more severe inhibition on seed germination, compared to neutral salts. The detrimental effects of salinity or high pH alone were less serious than their combination. Salt concentration, pH value, and their interactions had inhibitory effects on seed germination, with salinity being the decisive factor, while pH played a secondary role in salt-alkali mixed stress.

The Dunhuang murals are a precious treasure of China's cultural heritage, yet they have long been affected by salt damage. Traditional methods for detecting salt content are costly, inefficient, and may cause physical harm to the murals. Among current techniques for measuring salt content in murals, hyperspectral remote sensing technology offers a non-invasive, circumventing issues of high costs, low efficiency. Building on this, our study developed a high-spectral feature inversion model for mural phosphate content using Fractional Order Differentiation (FOD), a novel three-band spectral index, and Partial Least Squares Regression (PLSR) algorithm. The specific research contents include: 1) Exploring the absorption mechanism of phosphates and their characteristic bands, combined with the optimal spectral index to construct a univariate linear regression model, providing a basis for rapid quantitative measurement of mural phosphate content. 2) By comparing the accuracy of the PSR and PNDI spectral indices based on the linear regression model, the first six orders of the highest accuracy spectral index were selected as the optimal three-band spectral index combination, used as explanatory variables, with mural plaster electrical conductivity as the response variable, employing the PLSR method to construct the mural phosphate content high-spectral feature inversion model. The study's findings include:1) By comparing the outcomes of different orders of fractional differentiation, it was found that the model performance reached its optimum at a 0.3 order of differentiation for both PSR and PNDI data, with a determination coefficient (R-2) of 0.728. 2) Utilizing PLSR, this study employed the previously determined optimal six-order three-band spectral index combination as explanatory variables, with salt content as the response variable, successfully constructing the high-spectral feature inversion model for mural phosphate content with a determination coefficient (R-2) of 0.815. This provides an effective technical means for monitoring the salt damage conditions of precious cultural heritage such as murals.