Soil Electrical Conductivity Sensors Research Articles

Design and Performance Evaluation of an In Situ Online Soil Electrical Conductivity Sensor Prototype Based on the High-Performance Integrated Chip AD5941

Soil electrical conductivity has an important influence on the growth and development of plants. The existing real-time soil electrical conductivity detection device is affected by temperature, inconvenient to use, expensive, etc.; therefore, based on the classical four-terminal method of soil electrical conductivity detection principle, in this study, we aim to improve the limitations of the constant current source, selecting the high-performance integrated chip AD5941, optimizing the detection circuit and probe structure, improving the achievability of the detection circuit, and designing a type of in situ on-line real-time access to a soil electrical conductivity detection device, and improve the detection accuracy by temperature compensation. In this paper, dynamic performance, steady state performance, radial sensitivity range, and calibration test are carried out for the soil electrical conductivity detection prototype. The test results show that the dynamic response speed of the prototype is less than 50 ms, the steady state error is not more than ±2%, and the radial measurement sensitivity range is 8~10 cm. A comparison with the commercial sensor shows that the linear fit of the two measurements reaches 0.9995, and the absolute error ranges from −61.40 µS/cm to 23.90 µS/cm, with a relative error range of −1.94~1.86%. It shows that the performance of the two sensors is comparable, but the quality/price ratio of the prototype is much higher than that of the commercialized product. In this study, it is demonstrated that a high-precision, low-cost, and easy-to-use in situ online soil electrical conductivity detection device can be provided for agricultural and forestry production.

Temporal Stability of Management Zone Patterns: Case Study with Contact and Non-Contact Soil Electrical Conductivity Sensors in Dryland Pastures.

Precision agriculture (PA) intends to validate technological tools that capture soil and crop spatial variability, which constitute the basis for the establishment of differentiated management zones (MZs). Soil apparent electrical conductivity (ECa) sensors are commonly used to survey soil spatial variability. It is essential for surveys to have temporal stability to ensure correct medium- and long-term decisions. The aim of this study was to assess the temporal stability of MZ patterns using different types of ECa sensors, namely an ECa contact-type sensor (Veris 2000 XA, Veris Technologies, Salina, KS, USA) and an electromagnetic induction sensor (EM-38, Geonics Ltd., Mississauga, ON, Canada). These sensors were used in four fields of dryland pastures in the Alentejo region of Portugal. The first survey was carried out in October 2018, and the second was carried out in September 2020. Data processing involved synchronizing the geographic coordinates obtained using the two types of sensors in each location and establishing MZs based on a geostatistical analysis of elevation and ECa data. Although the basic technologies have different principles (contact versus non-contact sensors), the surveys were carried out at different soil moisture conditions and were temporarily separated (about 2 years); the ECa measurements showed statistically significant correlations in all experimental fields (correlation coefficients between 0.449 and 0.618), which were reflected in the spatially stable patterns of the MZ maps (averaging 52% of the total area across the four experimental fields). These results provide perspectives for future developments, which will need to occur in the creation of algorithms that allow the spatial variability and temporal stability of ECa to be validated through smart soil sampling and analysis to generate recommendations for sustained soil amendment or fertilization.

Viticultural Manipulation and New Technologies to Address Environmental Challenges Caused by Climate Change

Climate change is a critical challenge for the global grape and wine industry, as it can disrupt grapevine growth, production, and wine quality. Climate change could influence the cost-effectiveness and growth of the wine industry in different wine regions since grapevine development is deeply dependent on weather (short-term) and climate (long-term) conditions. Innovation and new technologies are needed to meet the challenge. This review article addresses the impact of climate change on grapevines, such as vine phenology, pest and disease pressure, crop load, and grape and wine composition. It also reviews recent advances in the areas of viticultural manipulation and relevant technologies to potentially reduce the impact of climate change and help growers improve grape quality. Remote sensing is used for vineyard microclimate monitoring; thermal sensors combined with UAVs, aircraft, or satellites are used for water management; soil electrical conductivity sensors have been developed for soil mapping. Viticultural manipulations, such as regulated deficit irrigation for water use efficiency and berry-ripening delay for growing quality fruit, are also discussed. The review assesses future directions for further technological development, such as soil and vine water monitoring devises, precision viticulture, and artificial intelligence in vineyards.

Development of signal analysis algorithm for apparent soil electrical conductivity sensor

For the spatial characterization of the soil in agricultural fields, the use of sensors is an alternative to collecting soil samples for laboratory analysis. Among such sensors, those that measure apparent soil electrical conductivity (EC a ) are distinctive. In EC a sensors based on electrical resistivity, perfect soil–electrode contact is required for a reliable EC a measurement. Thus, this study aimed to develop and evaluate an algorithm for the analysis of the signals used in a soil EC a sensor based on electrical resistivity. Two criteria were selected for analysing the signals read by the sensor. The first criterion verifies whether the read signals have a square wave shape. The second criterion evaluates whether the main frequency of a read signal is similar to that of the applied signal, as set by the user. The algorithm was evaluated using signals obtained from soil EC a measurements conducted under laboratory and field conditions. In the laboratory, the absence of soil–electrode contact was simulated by connecting a resistor to the electrodes. In the field, the EC a measurements were performed in clayey and sandy soils under low and high moisture conditions. The simulation of the absence of soil–electrode contact showed that the algorithm was effective for detecting the unsuitability of the read signals for EC a calculation in eight of the ten scenarios. The results of the field measurements in soil with low moisture content demonstrated that the algorithm could detect signals that were inappropriate for EC a calculation. • Development of signal analysis algorithm for soil apparent electrical conductivity sensor. • Algorithms to analyse the waveform and main frequency of the read signal. • Does not perform measurements in the absence of soil-electrode contact. • Greater reliability in measuring the apparent electrical conductivity of the soil.

Portable Soil Electrical Conductivity Sensor System Based on Electromagnetic Pulsed Eddy Current method

Soil salinization is one of the major environmental geological concerns around the world. The rapid survey of soil conductivity is urgent to reflect the salinization degree in time, while current methods rely on lab-test or electronic probe-based ones, which are not efficient on saving cost and improving efficiency. In this paper, a new electrical conductivity sensor based on electromagnetic pulsed eddy current strategy is proposed to meet the purpose of rapid and efficient survey of soil conductivity. Relevant software was also designed and tested. To facilitate the in-field test, a portable system was constructed.

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

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.

Application of geographical information system for farm mechanization education and training

Precision farming is managing each crop production input such as fertilizer, water, lime, herbicide, insecticide and seed on a site-specific basis to reduce waste, increase profit and maintain the quality of the environment. Without some remarkable enabling assisting technologies, the individual treatment of each plant is impossible and the concept of precision farming would not be feasible. Based on the trip, we can gain more information about the new technology that applies nowadays in agriculture. By using remote sensing that transmitted data from GPS, we can used to determination of generic object type, character and property as well as it’s abstract meaning. Besides, the application of remote sensing has been used in soil electrical conductivity sensor which used for show the variability of soil properties in detail and rapidly using simple equipment with less cost and labor force. Action maps will then be produced for farmers to apply fertilizers at different rates according to the delineated zones.