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Temperature correction of substrate moisture measurements made in coir in polytunnel-grown strawberries

机译：多螺孔生长草莓岩体湿度测量的温度校正

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摘要

The aim of this work is to assess the use of temperature corrected substrate moisture data to improve the relationship between environmental drivers and the measurement of substrate moisture content in high porosity soil-free growing media such as coir. Substrate moisture sensor data collected from strawberry plants grown in coir bags installed in a table-top system under a polytunnel illustrate the impact of temperature on capacitance-based moisture measurements. Substrate moisture measurements madein our coir growing medium demonstrate the negative temperature coefficient of the permittivity of water where diurnal changes in moisture content oppose those of substrate temperature. The diurnal substrate temperature variation was seen to range from7 to 25°C resulting in a clearly observable temperature effect in substrate moisture content measurements during the 23-day test period. A temperature correction algorithm is presented in this work that has been derived from the complex refractive indexmodel (CRIM) equation, which was easily calibrated for coir and applied to the substrate moisture and temperature data. The diurnal variations seen with the temperature compensated substrate moisture data now align very well with the expected diurnal water demands of the strawberry plants. To further evaluate the relationship between environmental drivers of solar radiation and vapour pressure deficit with substrate moisture, the temperature correction algorithm was programmed within a GP2 data loggerand controller (Delta-T Devices Ltd.). The GP2 also was employed to collect solar radiation, air temperature and relative humidity data. The resulting comparison of substrate moisture responses to environmental drivers illustrates an improved correlationwith temperature corrected substrate moisture measurements. We conclude that this new temperature correction algorithm addresses the effect of temperature on the relative permittivity of water, which can contribute to observable measurement errors usingcapacitance-based sensor measurements in high porosity soil-free growing substrates such as coir.
机译：这项工作的目的是评估温度校正的基底湿度数据的使用，以改善环境驱动因素之间的关系和在无孔隙率无土壤水分含量的底物水分含量，如益官。从在多阵线下安装在桌面系统中的股东袋中生长的草莓植物中收集的衬底湿度传感器数据说明了温度对基于电容的水分测量的影响。底物水分测量使我们的椰壳生长培养基展示了水的介电常数的负温度系数，其中水分含量的昼夜变化反对衬底温度。昼夜基板温度变化观察到范围为7至25℃，导致在23天的测试期间在底物水分含量测量中明显可观察到的温度效应。在该工作中提出了一种温度校正算法，该工作是从复合折射率（CRIM）方程导出的，这很容易校准COR并施加到基板湿度和温度数据。用温度补偿基板水分数据看的昼夜变化现在与草莓植物的预期昼夜水需求相处得非常良好。为了进一步评估环境驱动因素之间的环境驱动因素与具有基板湿度的蒸气压缺口之间的关系，在GP2数据记录器控制器（Delta-T设备有限公司）内进行了温度校正算法。 GP2也被采用来收集太阳辐射，空气温度和相对湿度数据。由此产生的基板湿度响应对环境驱动器的比较说明了温度校正衬底湿度测量的改进的相关性。我们得出结论，这种新的温度校正算法解决了温度对水的相对介电常数的影响，这可以有助于使用基于高孔隙率无土壤生长基材的远程传感器测量的可观察到的测量误差。

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