期刊
SCIENTIA AGRICOLA
卷 79, 期 4, 页码 -出版社
UNIV SAO PAULO, ESALQ
DOI: 10.1590/1678-992X-2020-0253
关键词
soil dielectric constant; soil water content; model selection; dielectric-based sensor
资金
- Coordination for the Improvement of Higher Level Personnel (CAPES) [001, CAPES/ANA 88887.144979/201700, AUXPE 593/2018]
- Brazilian National Council for Scientific and Technological Development (CNPq) [306511/2017-7, 202938/2018-2]
- Minas Gerais State Agency for Research and Development (FAPEMIG) [APQ-00802-18, CAGAPQ-01053-15]
- Sao Paulo State Research Support Foundation (FAPESP) [2019/23853-5, 2017/50241-5, IAEA/CRPD12014-CN23713]
This study compares regression models used for calibration of soil moisture sensors and investigates the relation between soil attributes and the adjusted parameters of the specific calibration equations. The findings suggest that site-specific calibrations can provide more accurate measurements.
Electromagnetic sensors are widely used to monitor soil water content (theta); however, site-specific calibrations are necessary for accurate measurements. This study compares regression models used for calibration of soil moisture sensors and investigates the relation between soil attributes and the adjusted parameters of the specific calibration equations. Undisturbed soil samples were collected in the A and B horizons of two Ultisols and two Inceptisols from the Mantiqueira Range in Southeastern Brazil. After saturation, the Theta Probe ML2X was used to obtain the soil dielectric constant (e). Several readings were made, ranging from saturation to oven-dry. After each reading, the samples were weighted to calculate. (m3 m-3). Fourteen regression models (linear, linearized, and nonlinear) were adjusted to the calibration data and checked for their residue distribution. Only the exponential model with three parameters met the regression assumptions regarding residue distribution. The stepwise regression was used to obtain multiple linear equations to estimate the adjusted parameters of the calibration model from soil attributes, with silt and clay contents providing the best relations. Both the specific and the general calibrations performed well, with RMSE values of 0.02 and 0.03 m(3) m(-3), respectively. Manufacturer calibration and equations from the literature were much less accurate, reinforcing the need to develop specific calibrations.
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