Development of signal analysis algorithm for apparent soil electrical conductivity sensor

2021 ◽  
Vol 211 ◽  
pp. 183-191
Author(s):  
Emanoel Di Tarso dos Santos Sousa ◽  
Daniel Marçal de Queiroz ◽  
Andre Luiz de Freitas Coelho ◽  
Domingos Sárvio Magalhães Valente
Keyword(s):  
Electrical Conductivity ◽  
Signal Analysis ◽  
Soil Electrical Conductivity ◽  
Analysis Algorithm ◽  
Conductivity Sensor

Development and Testing of a Low-Cost Portable Apparent Soil Electrical Conductivity Sensor Using a Beaglebone Black

2020 ◽  
Vol 36 (3) ◽  
pp. 341-355
Author(s):  
Daniel M. Queiroz ◽  
Emanoel D. T. S. Sousa ◽  
Won Suk Lee ◽  
John K. Schueller
Keyword(s):  
Electrical Conductivity ◽  
Soil Properties ◽  
Precision Agriculture ◽  
Low Cost ◽  
Satellite System ◽  
Mountainous Area ◽  
Soil Electrical Conductivity ◽  
Resistivity Method ◽  
Conductivity Sensor ◽  
Global Navigation Satellite

Abstract.The adoption of apparent soil electrical conductivity (soil ECa) sensors has increased in precision agricultural systems, especially in systems pulled by vehicles. This work developed a portable soil sensor for measuring soil ECa that could be used without vehicles in mountainous areas and small farms. The developed system was based on the electrical resistivity method. The system measured the electrical conductivity by applying a square wave signal at frequencies defined by the user. The acquired data were georeferenced using a low-cost global navigation satellite system (GNSS) receiver. The sensor system was developed using a BeagleBone Black, a low-cost single-board computer. A user interface was developed in C++, and a touch screen with a resolution of 800×480 pixels was used to display the results. This interface performed statistical analysis, and the results were used to guide the user to identify more field locations to be sampled to increase mapping accuracy. The system was tested in a coffee plantation located in a mountainous area and in a sugarcane plantation in Minas Gerais, Brazil. The system worked well in mapping the soil ECa. The apparent soil electrical conductivities measured using frequencies of 10, 20, 30, and 40 Hz were highly correlated. In the sugarcane field that had more variation in soil texture, a greater number of soil properties presented a significant correlation with the soil ECa. Keywords: Electrical conductivity, Geostatistics, Precision agriculture, Soil properties, Soil sensing, Spatial variability.

scholarly journals Farklı Buğday Çeşitlerinde Bitki Büyüme İndisi İle Toprak Elektriksel İletkenlik Değerleri Arasındaki İlişki

2020 ◽  
Vol 8 (5) ◽  
pp. 1154-1159
Author(s):  
Uğur Yegül ◽  
Maksut Barış Eminoğlu ◽  
Burak Şen ◽  
Savaş Kuşçu
Keyword(s):  
Electrical Conductivity ◽  
Plant Growth ◽  
Vegetation Index ◽  
Growth Index ◽  
Soil Electrical Conductivity ◽  
Conductivity Sensor ◽  
Two Parameters ◽  
The Relationship

This research was carried out in Haymana Research Farm of Ankara University. Three different varieties of wheat were used in the study. These varieties were; Kırgız-95, Kırkpınar-79, and Svevo. The aim of the study was to determine the relationship between soil electrical conductivity values and vegetation index. In the study, EM38, electrical conductivity sensor, and GreenSeeker, vegetation index sensor were used. The obtained values were evaluated statistically, and the relationships between the two parameters were determined. As a result of the research, the relationships between the electrical conductivity of the soil and plant growth index values were found to be negative (R2) as 0.7718 for Kyrgyz-95, 0.7675 for Kırkpınar-79 and 0.7807 for Svevo.

Measurement of Electrical Conductivity into Tomato Cultivation Beds using Small Insertion Type Electrical Conductivity Sensor Designed for Agriculture

2011 ◽  
Vol 131 (6) ◽  
pp. 211-217 ◽  
Author(s):  
Kazuko Kawashima ◽  
Masato Futagawa ◽  
Yoshihiro Ban ◽  
Yoshiyuki Asano ◽  
Kazuaki Sawada
Keyword(s):  
Electrical Conductivity ◽  
Conductivity Sensor

scholarly journals Spatial and Temporal Variability of Soil Salinity in the Yangtze River Estuary Using Electromagnetic Induction

2021 ◽  
Vol 13 (10) ◽  
pp. 1875
Author(s):  
Wenping Xie ◽  
Jingsong Yang ◽  
Rongjiang Yao ◽  
Xiangping Wang
Keyword(s):  
Electrical Conductivity ◽  
Spatial Distribution ◽  
Soil Salinity ◽  
Yangtze River ◽  
Laboratory Data ◽  
River Estuary ◽  
Yangtze River Estuary ◽  
Soil Electrical Conductivity ◽  
The Yangtze River ◽  
The Yangtze River Estuary

Soil salt-water dynamics in the Yangtze River Estuary (YRE) is complex and soil salinity is an obstacle to regional agricultural production and the ecological environment in the YRE. Runoff into the sea is reduced during the impoundment period as the result of the water-storing process of the Three Gorges Reservoir (TGR) in the upper reaches of the Yangtze River, which causes serious seawater intrusion. Soil salinity is a problem due to shallow and saline groundwater under serious seawater intrusion in the YRE. In this research, we focused on the temporal variation and spatial distribution characteristics of soil salinity in the YRE using geostatistics combined with proximally sensed information obtained by an electromagnetic induction (EM) survey method in typical years under the impoundment of the TGR. The EM survey with proximal sensing method was applied to perform soil salinity survey in field in the Yangtze River Estuary, allowing quick determination and quantitative assessment of spatial and temporal variation of soil salinity from 2006 to 2017. We developed regional soil salinity survey and mapping by coupling limited laboratory data with proximal sensed data obtained from EM. We interpreted the soil electrical conductivity by constructing a linear model between the apparent electrical conductivity data measured by an EM 38 device and the soil electrical conductivity (EC) of soil samples measured in laboratory. Then, soil electrical conductivity was converted to soil salt content (soil salinity g kg−1) through established linear regression model based on the laboratory data of soil salinity and soil EC. Semivariograms of regional soil salinity in the survey years were fitted and ordinary kriging interpolation was applied in interpolation and mapping of regional soil salinity. The cross-validation results showed that the prediction results were acceptable. The soil salinity distribution under different survey years was presented and the area of salt affected soil was calculated using geostatistics method. The results of spatial distribution of soil salinity showed that soil salinity near the riverbanks and coastlines was higher than that of inland. The spatial distribution of groundwater depth and salinity revealed that shallow groundwater and high groundwater salinity influenced the spatial distribution characteristics of soil salinity. Under long-term impoundment of the Three Gorges Reservoir, the variation of soil salinity in different hydrological years was analyzed. Results showed that the area affected by soil salinity gradually increased in different hydrological year types under the impoundment of the TGR.

scholarly journals The Relationship between Soil Electrical Parameters and Compaction of Sandy Clay Loam Soil

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 114
Author(s):  
Katarzyna Pentoś ◽  
Krzysztof Pieczarka ◽  
Kamil Serwata
Keyword(s):  
Electrical Conductivity ◽  
Magnetic Susceptibility ◽  
Precision Agriculture ◽  
Soil Compaction ◽  
Soil Layer ◽  
Soil Parameters ◽  
Soil Electrical Conductivity ◽  
Electrical Parameters ◽  
Management Zones ◽  
Additional Information

Soil spatial variability mapping allows the delimitation of the number of soil samples investigated to describe agricultural areas; it is crucial in precision agriculture. Electrical soil parameters are promising factors for the delimitation of management zones. One of the soil parameters that affects yield is soil compaction. The objective of this work was to indicate electrical parameters useful for the delimitation of management zones connected with soil compaction. For this purpose, the measurement of apparent soil electrical conductivity and magnetic susceptibility was conducted at two depths: 0.5 and 1 m. Soil compaction was measured for a soil layer at 0–0.5 m. Relationships between electrical soil parameters and soil compaction were modelled with the use of two types of neural networks—multilayer perceptron (MLP) and radial basis function (RBF). Better prediction quality was observed for RBF models. It can be stated that in the mathematical model, the apparent soil electrical conductivity affects soil compaction significantly more than magnetic susceptibility. However, magnetic susceptibility gives additional information about soil properties, and therefore, both electrical parameters should be used simultaneously for the delimitation of management zones.

scholarly journals A Low-Cost Water Depth and Electrical Conductivity Sensor for Detecting Inputs into Urban Stormwater Networks

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3056
Author(s):  
Baiqian Shi ◽  
Stephen Catsamas ◽  
Peter Kolotelo ◽  
Miao Wang ◽  
Anna Lintern ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Water Depth ◽  
Asset Management ◽  
Low Cost ◽  
Rate Of Change ◽  
Urban Drainage ◽  
Urban Stormwater ◽  
High Resolution Data ◽  
Conductivity Sensor ◽  
Level Sensor

High-resolution data collection of the urban stormwater network is crucial for future asset management and illicit discharge detection, but often too expensive as sensors and ongoing frequent maintenance works are not affordable. We developed an integrated water depth, electrical conductivity (EC), and temperature sensor that is inexpensive (USD 25), low power, and easily implemented in urban drainage networks. Our low-cost sensor reliably measures the rate-of-change of water level without any re-calibration by comparing with industry-standard instruments such as HACH and HORIBA’s probes. To overcome the observed drift of level sensors, we developed an automated re-calibration approach, which significantly improved its accuracy. For applications like monitoring stormwater drains, such an approach will make higher-resolution sensing feasible from the budget control considerations, since the regular sensor re-calibration will no longer be required. For other applications like monitoring wetlands or wastewater networks, a manual re-calibration every two weeks is required to limit the sensor’s inaccuracies to ±10 mm. Apart from only being used as a calibrator for the level sensor, the conductivity sensor in this study adequately monitored EC between 0 and 10 mS/cm with a 17% relative uncertainty, which is sufficient for stormwater monitoring, especially for real-time detection of poor stormwater quality inputs. Overall, our proposed sensor can be rapidly and densely deployed in the urban drainage network for revolutionised high-density monitoring that cannot be achieved before with high-end loggers and sensors.

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