Guangxi Geographical Indication Crops Research Center of Big Data Mining and Experimental Engineering Technology, Nanning Normal University, Nanning 530001, China.
Research Institute of Forestry Policy and Information, Chinese Academy of Forestry, Beijing 100091, China.
Int J Environ Res Public Health. 2022 Dec 15;19(24):16855. doi: 10.3390/ijerph192416855.
Soil pH is an essential indicator for assessing soil quality and soil health. In this study, based on the Chinese farmland soil survey dataset and meteorological dataset, the spatial distribution characteristics of soil pH in coastal eastern China were analyzed using kriging interpolation. The relationships between hydrothermal conditions and soil pH were explored using regression analysis with mean annual precipitation (MAP), mean annual temperature (MAT), the ratio of precipitation to temperature (P/T), and the product of precipitation and temperature (PT) as the main explanatory variables. Based on this, a model that can rapidly estimate soil pH was established. The results showed that: (a) The spatial heterogeneity of soil pH in coastal eastern China was obvious, with the values gradually decreasing from north to south, ranging from 4.5 to 8.5; (b) soil pH was significantly correlated with all explanatory variables at the 0.01 level. In general, MAP was the main factor affecting soil pH ( = -0.7244), followed by P/T ( = -0.6007). In the regions with MAP < 800 mm, soil pH was negatively correlated with MAP ( = -0.4631) and P/T ( = -0.7041), respectively, and positively correlated with MAT ( = 0.6093) and P*T ( = 0.3951), respectively. In the regions with MAP > 800 mm, soil pH was negatively correlated with MAP ( = -0.6651), MAT ( = -0.5047), P/T ( = -0.3268), and PT ( = -0.5808), respectively. (c) The estimation model of soil pH was: = 23.4572 - 6.3930 × lgMAP + 0.1312 × MAT. It has been verified to have a high accuracy ( = 0.7743, < 0.01). The mean error, the mean absolute error, and the root mean square error were 0.0450, 0.5300, and 0.7193, respectively. It provides a new path for rapid estimation of the regional soil pH, which is important for improving the management of agricultural production and slowing down soil degradation.
土壤 pH 值是评估土壤质量和土壤健康的重要指标。本研究基于中国农田土壤调查数据集和气象数据集，采用克里金插值法分析了中国东部沿海地区土壤 pH 值的空间分布特征。利用回归分析探讨了水热条件与土壤 pH 值之间的关系，以年平均降水量（MAP）、年平均气温（MAT）、降水与气温之比（P/T）和降水与气温的乘积（PT）作为主要解释变量。在此基础上，建立了一种快速估算土壤 pH 值的模型。结果表明：（a）中国东部沿海土壤 pH 值的空间异质性明显，由北向南逐渐降低，范围为 4.5-8.5；（b）土壤 pH 值与所有解释变量在 0.01 水平上显著相关。一般来说，MAP 是影响土壤 pH 值的主要因素（ = -0.7244），其次是 P/T（ = -0.6007）。在 MAP < 800mm 的地区，土壤 pH 值与 MAP（ = -0.4631）和 P/T（ = -0.7041）呈负相关，与 MAT（ = 0.6093）和 P*T（ = 0.3951）呈正相关。在 MAP > 800mm 的地区，土壤 pH 值与 MAP（ = -0.6651）、MAT（ = -0.5047）、P/T（ = -0.3268）和 PT（ = -0.5808）呈负相关。（c）土壤 pH 值估算模型为： = 23.4572-6.3930×lgMAP+0.1312×MAT。验证结果表明，该模型具有较高的精度（ = 0.7743， < 0.01）。平均误差、平均绝对误差和均方根误差分别为 0.0450、0.5300 和 0.7193。该模型为区域土壤 pH 值的快速估算提供了新途径，对提高农业生产管理水平、减缓土壤退化具有重要意义。
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