中国地理科学 ›› 2017, Vol. 27 ›› Issue (3): 431-440.doi: 10.1007/s11769-017-0875-9

• 论文 • 上一篇    下一篇

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

WU Qiulan1, LIANG Yong1, LI Ying2, WANG Xizhi3, YANG Lei1, WANG Xiaotong4   

  1. 1. School of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, China;
    2. School of Economics and Management, Shandong Agricultural University, Tai'an 271018, China;
    3. Institute of Agricultural Sciences of Yanzhou District in Jining, Yanzhou 272100, China;
    4. School of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
  • 收稿日期:2016-06-13 修回日期:2016-09-07 出版日期:2017-06-27 发布日期:2017-05-09
  • 通讯作者: LIANG Yong. E-mail: liang_9322@126.com E-mail:liang_9322@126.com
  • 基金资助:

    Under the auspices of National High-tech R&D Program of China (No. 2013AA102301), National Natural Science Foundation of China (No. 71503148)

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

WU Qiulan1, LIANG Yong1, LI Ying2, WANG Xizhi3, YANG Lei1, WANG Xiaotong4   

  1. 1. School of Information Science and Engineering, Shandong Agricultural University, Tai'an 271018, China;
    2. School of Economics and Management, Shandong Agricultural University, Tai'an 271018, China;
    3. Institute of Agricultural Sciences of Yanzhou District in Jining, Yanzhou 272100, China;
    4. School of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
  • Received:2016-06-13 Revised:2016-09-07 Online:2017-06-27 Published:2017-05-09
  • Contact: LIANG Yong. E-mail: liang_9322@126.com E-mail:liang_9322@126.com
  • Supported by:

    Under the auspices of National High-tech R&D Program of China (No. 2013AA102301), National Natural Science Foundation of China (No. 71503148)

摘要:

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.

关键词: Internet of Things (IOT), soil organic carbon (SOC), factors acquisition, SOC content estimation, Soil-C model

Abstract:

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.

Key words: Internet of Things (IOT), soil organic carbon (SOC), factors acquisition, SOC content estimation, Soil-C model