National Natural Science Foundation of China（No. 41671218）and Basic Work of the Ministry of Science and Technology of China（No. 2014FY110200A12）
[Objective] Soil iron oxides are found in almost all the types of soils and are good indicators reflecting variation of the environment thanks to their high variability in concentration. Soil iron oxides, mostly in the form of free iron, function as important mineral binders in the soil and have a significant effect on color of the soil. Soil color is an important soil property, described by Munsell color space, in the soil taxonomy. Both soil color and free iron are indicators in the soil taxonomy, and fairly related to each other, but so far few papers have been reported on quantitative relationships between them. [Method] Since soil color is an indicator reflecting genesis and evolution of a soil, it is often used to invert and predict soil properties via modeling. Therefore, in this paper, the typical soil series in the hilly region of Central Sichuan were taken as the research object for analysis of relationships between soil Munsell color and free iron content in the soils. On this basis, a BP neural network model is established to explore differences between the Munsell color based model and the traditional spectral model in predicting soil free iron content. [Result] Results show significantly positive relationships of free iron content with hue, value and chroma of soil Munsell color. When the Munsell color prediction model had 4 neurons in the single hidden layer, the determination coefficient R2 of its test set was 0.94, its standard deviation RMSE 4.20, and its relative analysis error RPD 4.37; When the spectral prediction model had 6 neurons in the single hidden layer, its R2 was 0.98, RMSE 3.35, and RPD 5.99. Both models have demonstrated a high level of goodness of fit and accuracy, though the spectral model is slightly higher than the color model. [Conclusion] Munsell color can be used to predict soil free iron content effectively, but by comparison, the spectral model is a bit higher in goodness of fit and prediction accuracy, which may be attributed to the fewer neurons in the input layer of the color model and the dispersion degree of free iron oxides dispersion degree. Color information is easy to obtain, for some historical soil literature, which do have color data, but lack the data of free iron contents, the Munsell color-based prediction model can be used to figure out an approximate content of free iron in the soil.
余星兴,袁大刚,陈剑科,翁倩,付宏阳,黄宇潇.基于Munsell颜色的土壤游离铁预测研究[J].土壤学报,2021,58(5):1322-1329. DOI:10.11766/trxb202004130048 YU Xingxing, YUAN Dagang, CHEN Jianke, WENG Qian, FU Hongyang, HUANG Yuxiao. Prediction of Soil Free Iron Oxide Content Based on Soils Munsell Color[J]. Acta Pedologica Sinica,2021,58(5):1322-1329.复制