低成本电容式湿度传感器在巴西塞拉多三种土壤中的应用评估

Rodrigo Moura Pereira, D. Sandri, J. S. Silva Júnior
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引用次数: 1

摘要

土壤湿度传感器为农业提供了新的自动化和计算机化解决方案。然而,它的使用仍然需要事先校准,以证明其估计土壤湿度的准确性。因此,在本研究中,使用与Arduino微控制器集成的电容式传感器SKU:SEN0193开发了土壤湿度监测原型。基于巴西联邦区塞拉多地区红黄拉托索尔(RYL)、Regolitic Neosol (RN)和红色拉托索尔(RL)变形样品的体积水分与传感器输出电压之间的关系,对原型进行了校准。对传感器的校正得到二阶多项式模型,RYL的R²在0.93 ~ 0.96之间,RN的R²在0.89 ~ 0.92之间,RL的R²在0.86 ~ 0.88之间。体积湿度的均方根误差(RMSE)分别为0.08、0.12和0.15 cm3。RYL、RN和RL分别为cm-3。工作电压为5.00 V时,传感器的读数变异性较小,变异系数(CV)在0.21 ~ 1.54%之间,而工作电压为3.30 V时,传感器的CV在3.27 ~ 17.84%之间。建议对每种土壤类型的SKU:SEN0193进行校准,以便获得RYL, RN和RL的可靠含水量估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of low-cost capacitive moisture sensors in three types of soils in the Cerrado, Brazil
Soil moisture sensors enabled new automation and computerization solutions in agriculture. However, its use still requires prior calibrations to attest its accuracy to estimate soil moisture. Thus, in this study a prototype for soil moisture monitoring was developed using the capacitive sensor SKU:SEN0193 integrated with the Arduino microcontroller. The prototype was calibrated based on the relationship between volumetric moisture and sensor output voltage in deformed samples of Red-yellow Latosol (RYL), Regolitic Neosol (RN), and Red Latosol (RL) of the Cerrado region, Federal District, Brazil. The calibration of sensors resulted in a second-degree polynomial model with R² between 0.93 and 0.96 for RYL, 0.89 and 0.92 for RN, and 0.86 and 0.88 for RL. Root mean square errors (RMSE) of volumetric moisture were 0.08, 0.12, and 0.15 cm3.cm-3 for RYL, RN, and RL, respectively. Sensors at operating voltage of 5.00 V showed less variability of readings, with coefficient of variation (CV) between 0.21 and 1.54%, while sensors at 3.30 V showed CVs between 3.27 and 17.84%. It is recommended to calibrate the SKU:SEN0193 for each soil type in order to obtain reliable estimates of water content for RYL, RN, and RL.
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