Soil temperature detection based on acoustic method and improved Wyllie model

被引:0
|
作者
Ye, Yong [1 ,2 ]
Chen, Yongru [3 ]
Chen, Yingyi [1 ]
Li, Zhao [1 ]
Chen, Yuan [1 ]
Zeng, Ye [1 ]
Li, Jun [1 ,2 ,4 ]
机构
[1] South China Agr Univ, Coll Engn, Guangzhou 510642, Peoples R China
[2] Guangdong Lab Lingnan Modern Agr, Guangzhou 510642, Peoples R China
[3] Univ Calif Los Angeles, Coll Letters & Sci, Los Angeles, CA 90095 USA
[4] Natl Key Lab Agr Equipment Technol, Beijing 100083, Peoples R China
关键词
Soil Moisture Content; Soil Temperature; Acoustic Velocity; Sandy Loam Soil; VELOCITY; SOUND;
D O I
10.1016/j.geoderma.2024.116948
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Soil temperature is one of the important environmental factors for the underground parts of plants. It is important to detect soil temperature in agricultural production. Acoustic waves serve as effective carriers of soil information, providing a reliable means to detect soil physical properties. In order to detect the temperature of sandy loam soil based on acoustic technology, this study extends the application of Wyllie model to the temperature measurement of sandy loam soil. The relationship between soil temperature and acoustic velocity is explored. A model of soil moisture content-soil temperature-acoustic velocity (MTV) for temperature measurement in sandy loam soil is proposed by extending the temperature-velocity of sound relationship with the introduction of a variable empirical coefficient related to soil moisture beta(theta). In order to determine the parameters of proposed model, a pulsed acoustic velocity detection system was built in this paper. The influence of temperature on the acoustic velocity in sandy loam soil was analyzed through experiments. Based on the experimental results, the key parameters of the MTV model are refined. Finally, a validation experiment was carried out on sandy loam soil. The maximum estimation error of soil temperature based on the MTV model for sandy loam soil temperature estimation is 8.55 %. The results indicate that the MTV model proposed in this study can be used for temperature estimation in sandy loam soil, providing a theoretical basis for the development of acoustic soil physical information detection sensors.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] Soil water content detection based on acoustic method and improved Brutsaert's model
    Xu, Yan
    Li, Jun
    Duan, Jieli
    Song, Shuaishuai
    Jiang, Rui
    Yang, Zhou
    GEODERMA, 2020, 359
  • [2] Corrigendum: Soil water content detection based on acoustic method and improved Brutsaert's model
    Xu, Yan
    GEODERMA, 2022, 407
  • [3] An improved method for separating soil and vegetation component temperatures based on diurnal temperature cycle model and spatial correlation
    Liu, Xiangyang
    Tang, Bo-Hui
    Li, Zhao-Liang
    Zhou, Chenghu
    Wu, Wenbin
    Rasmussen, Mads Olander
    REMOTE SENSING OF ENVIRONMENT, 2020, 248
  • [4] Cheating Detection Method Based on Improved Cognitive Diagnosis Model
    Li, Zhizhuang
    Zhu, Zhengzhou
    Xie, Qiongyu
    ADVANCES IN WEB-BASED LEARNING - ICWL 2019, 2019, 11841 : 84 - 91
  • [5] A fast motion detection method based on improved codebook model
    Xu, Cheng
    Tian, Zheng
    Li, Renfa
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2010, 47 (12): : 2149 - 2156
  • [6] Improved Moving Objects Detection Method Based on Codebook Model
    Liu Liwei
    Li Hongwei
    Yu Shuo
    PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC), 2013, : 1351 - 1354
  • [7] A Small Target Detection Method Based on the Improved FCN Model
    Ma, Guofeng
    ADVANCES IN MULTIMEDIA, 2022, 2022
  • [8] A Shadow Detection Method Based on Improved Gaussian Mixture Model
    Li, Jing
    Wang, Geng
    2013 IEEE 4TH INTERNATIONAL CONFERENCE ON ELECTRONICS INFORMATION AND EMERGENCY COMMUNICATION (ICEIEC), 2014, : 62 - 65
  • [9] Study on the Detection of Soil Water Content Based on the Pulsed Acoustic Wave (PAW) Method
    Xu, Yan
    Duan, Jieli
    Jiang, Rui
    Li, Jun
    Yang, Zhou
    IEEE ACCESS, 2021, 9 : 15731 - 15743
  • [10] Microscopic hyperspectral imaging and an improved detection model based detection of Mycogone perniciosa chlamydospore in soil
    Wei, Xuan
    Liu, Yongjie
    Song, Qiming
    Zou, Jinping
    Wen, Zhiqiang
    Li, Jiayu
    Jie, Dengfei
    EUROPEAN JOURNAL OF AGRONOMY, 2024, 152