Arid Zone Research ›› 2022, Vol. 39 ›› Issue (4): 1293-1302.doi: 10.13866/j.azr.2022.04.29

• Agricultural Ecology • Previous Articles     Next Articles

Soil pH inversion based on electromagnetic induction data in cotton field of southern Xinjiang

WANG Jiawen1(),PENG Jie1(),JI Wenjun2,BAI Jianduo1,FENG Chunhui1,LI Hongyi3   

  1. 1. College of Plant Science, Tarim University, Alar 843300, Xinjiang, China
    2. College of Land Science and Technology, China Agricultural University, Beijing 100083, China
    3. School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330052, Jiangxi, China
  • Received:2021-06-22 Revised:2021-10-29 Online:2022-07-15 Published:2022-09-26
  • Contact: Jie PENG E-mail:wjwzky@126.com;pjzky@163.com

Abstract:

Soil salinity aggregation will change soil acidity or alkalinity. As an important land resource reserve area in China, soil salinization and secondary salinization problems are frequent in Xinjiang, Therefore, accurately obtaining soil salinity information and effectively improving soil salinity is beneficial to regulating the contradiction between agricultural irrigation and freshwater resources. Such regulation is of considerable important to the sustainable development of agricultural production and ecological environment. In this study, the soil pH value of cotton fields in Alar Reclamation Area, southern Xinjiang, was taken as the research object, and the EM38-MK2 geodetic conductivity meter was used on the basis of electromagnetic induction technology to obtain soil apparent conductivity data of nine cotton fields in the Reclamation Area. In each cotton field, soil apparent conductivity thresholds were collected in accordance with cotton fields of 0-0.375, 0.375-0.75, 0.75-1.00 m depth, 54 profile samples were collected from three soil layers, and 486 soil profile samples were collected from nine cotton fields. The linear regression model between soil pH and soil apparent conductivity was constructed using two ideas of the global and different regions and combined with geostatistical software to quantify in cotton fields in the Reclamation Area. The two-tailed test results revealed that the correlation coefficients between apparent conductivity and soil pH were 0.60-0.95 for the idea of different regions under the condition of P < 0.01; while those for the global regions were 0.28-0.46. Both findings were highly significant negative correlations, indicating that EM38-MK2 could be used for the determination of soil pH. Linear regression models between apparent conductivity data and soil pH were constructed using the global region and different regions. The zonal models 0.74 ≤ R2 ≤ 0.93 and 2.00 ≤ RPD ≤ 3.50, which have smaller RMSE, showed high accuracy, indicating that the accuracy of the different region model is better than that of the global region models. Meanwhile, the accuracy of the soil pH inversion model is also higher in areas with higher salinity. The Kriging interpolation results showed that the soil pH in the deep layer of cotton fields in the Reclamation Area was higher than that in the surface layer due to the influence of winter irrigation, cotton root system and cotton dead leaves. This study aims to provide ideas for the rapid determination of soil pH. Therefore, soil acid-base risk prediction can be accurate, and effective risk countermeasures can be formulated rationally.

Key words: soil pH, soil apparent conductivity, inversion model, cotton fields, the spatial distribution, southern Xinjiang