Factors Acquisition and Content Estimation of Farmland Soil Organic Carbon Based upon Internet of Things

• Published in: Chinese geographical science 2017-06, Vol.27 (3), p.431-440
• Main Authors: Wu, Qiulan, Liang, Yong, Li, Ying, Wang, Xizhi, Yang, Lei, Wang, Xiaotong
• Format: Article
• Language: English
• Subjects: Agricultural land; Carbon; Earth and Environmental Science; Estimating techniques; Farms; Geography; Internet of Things; Organic carbon; Organic chemicals; Organic soils; Soil depth; Soils; Tillage; Wheat; 估算模型; 农田土壤; 动态模拟模型; 因子; 土壤有机碳; 实时数据采集; 有机碳含量; 物联网
• ISSN: 1002-0063; 1993-064X
• DOI: 10.1007/s11769-017-0875-9

Aiming at the shortage of sufficient continuous parameters for using models to estimate farmland soil organic carbon（SOC） content, an acquisition method of factors influencing farmland SOC and an estimation method of farmland SOC content with Internet of Things（IOT） are proposed in this paper. The IOT sensing device and transmission network were established in a wheat demonstration base in Yanzhou Distict of Jining City, Shandong Province, China to acquire data in real time. Using real-time data and statistics data, the dynamic changes of SOC content between October 2012 and June 2015 was simulated in the experimental area with SOC dynamic simulation model. In order to verify the estimation results, potassium dichromate external heating method was applied for measuring the SOC content. The results show that： 1） The estimated value matches the measured value in the lab very well. So the method is feasible in this paper. 2） There is a clear dynamic variation in the SOC content at 0.2 m soil depth in different growing periods of wheat. The content reached the highest level during the sowing period, and is lowest in the flowering period. 3） The SOC content at 0.2 m soil depth varies in accordance with the amount of returned straw. The larger the amount of returned straw is, the higher the SOC content.