WO2024263735A1

WO2024263735A1 - In-situ soil nitrate sensing system

Info

Publication number: WO2024263735A1
Application number: PCT/US2024/034762
Authority: WO
Inventors: Shalini Prasad; Vikram Narayanan DHAMU; Mohammad A. ELDEEB
Original assignee: Soil In Formation Pbc
Current assignee: Soil In Formation Pbc
Priority date: 2023-06-20
Filing date: 2024-06-20
Publication date: 2024-12-26
Anticipated expiration: 2025-12-20
Also published as: AU2024314885A1

Abstract

An in-situ, or interfacial, soil sensor is provided, which includes one or more electrodes. The soil sensor is configured to detect levels of nitrate in a sample of soil, the sensor including: a working electrode coated in a composite sensing film, where the composite sensing film includes: an active sensing component functionalized to detect nitrate, an encapsulant component, and a sealant component.

Description

IN-SITU SOIL NITRATE SENSING SYSTEM

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application 63/509,156 filed on June 20, 2023, the content of which is incorporated herein in its entirety.

BACKGROUND

[0002] Soil and water are vital components of the Earth's ecosystem, both playing a major role in maintaining the ecological balance of the planet and sustaining mankind. For instance, the correct use of resources such as water and fertilizers in agriculture application has enormous societal (e.g., health, economic, etc.) importance as well as importance at an environmental level. Governments, corporations, and non-profit groups are working to develop paradigms in which soil and water are protected, regenerated and used more intelligently for the benefit of man and nature. For instance, "regenerative farming" concepts and practices have been proposed and implemented for improving soil health, increasing nutrient levels in crops, improving water use efficiency and reversing climate change through sequestering carbon.

[0003] For farmers, the systematic recording of a wide range of information about their fields helps them to implement quality regenerative farming systems, with the aim of improving the information which the farmers rely on for planning and decision-making to increase productivity, land quality, land assets and to reverse losses or inefficiencies in their farms. Optimization of regenerative agriculture is also important at a macro societal level, by protecting crop-producing land, water availability, quality and safety, and reversing negative environmental impacts due to degenerative, inefficient or careless farming practices. [0004] Traditionally, analytical information for soil health has been obtained by means of manually taking soil samples from various accessible zones to represent various soil regions. The samples are then transported to a laboratory to conduct tests and measurements on these samples to better understand the individual nutrient levels in these soil samples and to estimate the overall soil health and water use efficiency in a whole field, farm or in wider regions. Such traditional measurement systems are both inefficient, suboptimal, and expensive, limiting the utility and affordability to the end-user farmers, and thereby limiting the accessibility and momentum needed to implement such "regenerative farming" methods at scale, among other example disadvantages.

BRIEF DESCRIPTION OF FIGURES

[0005] FIG. 1 is a simplified block diagram showing an example soil sensor system.

[0006] FIG. 2 is a simplified block diagram of illustrating the measurement of nitrate content within a soil sample using an example soil nitrate sensor.

[0007] FIG. 3 is a simplified block diagram illustrating an example deployment of an example soil nitrate sensor.

[0008] FIG. 4A is a simplified block diagram illustrating an example deployment of an example soil nitrate sensor within an example environment.

[0009] FIG. 4B is a diagram illustrating a soil triangle.

[0010] FIGS. 5A-5C are diagrams illustrating example chemical interactions of example compounds used in a composite coating of an example soil sensor.

[0011] FIG. 6 show graphs illustrating an example calibration of an example soil nitrate sensor.

[0012] FIG. 7 is a flow diagram illustrating an example technique for measuring nitrate content within soil using an in-site soil sensor.

[0013] Like reference numbers and designations in the various drawings indicate like elements. DETAILED DESCRIPTION

[0014] Sustainable agriculture is the sought after answer to address the rapid rise in worldwide food demand, which increasingly strains world soil quality leading to desertification, food insecurity, and ecosystem imbalances, among other example issues. Sustainable agriculture solutions would benefit tremendously from improvements in soil health information. Indeed, having real-time soil health information could be used to allow farmers to make more informed decisions that include consideration of soil health, which can lead not only to economically benefits from improved crop yields, but also environmental benefits from more efficient farming, among other examples.

[0015] In an improved implementation, an ion-selective electrode (ISE) electrochemical soil nitrate sensor is described that utilizes electrochemical impedance spectroscopy (EIS) for direct, real-time, continuous soil nitrate measurement at the site (in-situ) without any soil pretreatment. In some implementations, the ISE is applied by drop casting a specialized composite coating onto the working electrode to configure the working electrode to detect the presence of nitrate within surrounding soil (in which the electrode is inserted). The soil sensor may be deployed (and trained) within a variety of different soil textures (e.g., clay, sandy loam, and loamy clay). Non-linear regression models show a nitrate dependent response with R2 > 0.97 for the various soil textures in the nitrate range 5 - 512 ppm for some implementations of an in-situ nitrate soil sensor. Validation of one example implementation of the soil sensor show less than 20% error rate between the measured nitrate and reference nitrate for multiple different soil textures including ones which were not used in the calibration of the sensor, among other example features.

[0016] Soil is a fundamental core element of the environment that directly impacts the growth of plants, crops and other vegetation in addition to having a relationship with other parts of the ecosystem including water and air. There is a major requirement for information related to the physical, chemical, and biological components of soil and thereby its vital association with soil health. Among these groups of parameters, information relating to the chemical profiles of soil can be used to create a soil health index with a high degree of reliability in an in-situ manner. As discussed herein, soil chemistry of a mass of soil (or soil matrix) can be derived using in-field probes that have a significant correlation and a soil health index can be derived using the information derived through such sensors together with information concerning the physical and biological parameters as well as activity in the soil matrix. Commercially, soil quality determines crop yields and the cost of farmland. Accordingly, it may be of particular benefit to obtain thorough dynamic and in-situ information about soil parameters that is synchronized in terms of geological location (space) and period (time) due to variations associated with environmental and land use changes. Implementation of dynamic, in-situ soil sensors, such as discussed herein, may enable to collection of such information to ultimately characterize multiple soil parameters related to soil health from a local as well as global environmental-impact standpoint.

[0017] Soil health/quality is defined by its capacity to function as a sustainable ecosystem that supports plants, animals, and humans alike. Typically, soil health includes three types of soil characteristics: biological, physical, and chemical. Although sometimes used interchangeably, soil quality, from a practical sense, refers to soil chemical and physical properties. For instance, soil health assessment in large part is determined by the nutrient levels in soil. Hence, assessment of soil health parameters in an on-farm setting facilitates quantification and recording of the soil's inherent physio-chemical and biochemical characteristics. Sufficient levels of soil nutrients are required for sustainable agricultural practices that typically increase the health of the agricultural ecosystem and boost crop yields, pasture growth, etc. Currently, soil sampling and evaluation methods involve intrusive approaches to collect and then subsequently and remotely test the soil samples in a laboratory environment that differs from the point of collection. Among these traditional soil evaluation techniques, combustion is one of the most popular techniques to look at soil anatomy. Even with the upcoming research breakthroughs in non-destructive approaches like spectroscopy and tomography-based models, there is a barrier in-terms of accuracy of the methods, especially at soil depths below 5-10 cm, equipment complexity and availability, as well as high costs and high logistical overhead, among other issues.

[0018] There are a wide number of primary, secondary and micronutrients that are required by plants for growth, including soil organic matter, nitrates, etc. An important metric includes the rate of nutrient release for uptake by the crops or plants, which is affected by the availability of the various nutritional sources and other soil parameters. There are a number of electrochemically active and redox substances present in soil that exist in reduced state under ideal conditions (submerged) that contribute to electrochemical activity and in turn have a proportional effect on the soil quality.

[0019] Some soil properties often used to evaluate soil physical properties are bulk density, infiltration parameters, water holding capacity, and soil texture; on the other hand, parameters used for chemical evaluation typically include soil pH, plant available nutrients, soil nitrate, reactive carbon, soil organic matter, and electrical conductivity. Biological properties of soil systems include the diversity and quantity of soil organisms (e.g., soil food web), total organic carbon, soil respiration, and soil enzymatic activity. Overall, each of these individual parameters can be matched to provide information about the soil state which in turn is the end objective.

[0020] Improved sensors may be provided, which leverage soil electrochemistry to correlate soil health in terms of understandable electrochemical signals. Such sensors may be implemented as integrated and miniaturized platforms along with reliable data output (e.g., to local or remote logic instrumented to consume data generated by the sensor). For instance, a sensor device may be implemented as an on-chip in-situ diagnostic platform for continuously monitoring active parameters inside the dynamic soil ecosystem. Using such sensors, data sets may be collected and processed to identify correlations between electrochemical activity and the presence of active substances that contribute to the soil nutrient cycle. Indeed, such improved in-situ soil sensors may permit soil health to be assessed and monitored at an interfacial level using a probe system. Accordingly, the soil matrix may be characterized using the resulting data in order to provide information in terms of various physio-chemical phenomena occurring at the electrode interface. Subsequently this information can be used to correlate that to useful data which helps to understand soil fertility and bioavailability of nutrients for plants and other vegetation at the field level, among other example insights.

[0021] Turning to FIG. 1, a simplified block diagram 100 is shown illustrating an example soil sensing system implemented using one or a collection of computing and/or sensor devices. In one example system, a set of sensors (e.g., 105, 105a-d), such as discussed in the examples below, may be deployed in an agricultural plot 150 to test various areas, or samples (e.g., 110), of a soil under various electrochemical modalities to thereby visualize the composite soil chemistry profile of the plot via a point measurement from different characterization perspectives. Such different perspectives may be collected utilizing a collection of sensors (e.g., 105, 105a-d), which includes sensors dispersed in various areas of the plot and/or different types of sensors (e.g., measuring the same or varied portions of the plot), as well as collecting measurements from the sensors on a rolling or continuous basis so as to survey the development of the soil's health attributes over time. Thus, improved data and resulting insights may be derived in such on-field applications due to the sensor devices capturing the dynamic behavior of soil through sensor readings in a range of temporal and spatial settings. Integration of these measurements from spread-out temporal and spatial points may be used by the system to compute a holistic soil profile for the corresponding region, among other example applications and potential benefits.

[0022] In some implementations, supplemental or cooperating computing systems may be provided to communicate with and consume data generated by the collection of sensors (e.g., 105, 105a-d). In one example, a gateway device or other I/O device (e.g., 115) may be utilized to collect signals and other data generated by the sensor devices (e.g., 105, 105a-d) and collect, aggregate, filter, and/or sort the data for consumption by other computing systems and logic. For instance, a computing system (e.g., 125) may be provided with computational logic to determine correlations between the readings of the sensors (e.g., 105, 105a-d) and corresponding soil attributes, which the sensors are configured to measure. For instance, a sensor (e.g., 105) may include one or more electrodes (e.g., 140), which are to contact soil (e.g., 110) and measure electrochemical characteristics of the soil. The electrode(s) 140, in some implementations, may be coated in a specialized coating to enable the electrode 140 to function appropriately within the sensor 105 to enable the sensor to detect nitrate content within a given soil sample (e.g., 110). For instance, the sensor 105 may generate signals based on these measured electrochemical characteristics. The signals, by themselves, may not directly indicate the level of certain soil health attributes, but through analysis by a correlation engine 155 (e.g., implemented in software and/or hardware of a computing system (e.g., 125)), correlations between certain electrochemical characteristic measurements and corresponding levels of one or more soil health attributes may be determined. While FIG. 1 shows that correlation engine 155 may be executed by a processor 145 and stored in memory 150 of a computing system remote from the sensors (e.g., 105, 105a-d), in some implementations, the hardware and logic of system 125 may be integrated on the sensors themselves to allow this translation between electrochemical readings and various soil health attribute measurements to be determined locally. In some implementations, soil health attribute results determined by a correlation engine 155 may be shared with other computing systems for further storage and/or processing, such as a cloud-based soil-health analysis system (e.g., 130) among other example implementations.

[0023] The rapid rise in food demand is straining our soil to the point that the United Nations (UN) have named food insecurity, desertification, land degradation, and ecosystem imbalance as some of the critical problems to conquer in their Sustainable Development Goals (SDG) report. A major solution to these problems is sustainable agriculture. The National Institute of Food and Agriculture (NIFA) defines sustainable agriculture as a system that integrates plants and animal production that over the long term would satisfy human food requirements, protects the environment and enhances its natural resources, makes efficient use of nonrenewable resources complimented by the natural biological cycle, and improves the quality of life for society and farmers. However to achieve this goal, farmers need to know the health of their soil on a running basis (e.g., throughout the year). [0024] Nitrates are essential plant nutrients, but in excess amounts they can cause significant water quality problems. Excess nitrate amounts can accelerate eutrophication, causing dramatic increases in aquatic plant growth and changes in the types of plants and animals that live in the stream. This, in turn, affects temperature, dissolved oxygen, and other indicators becoming toxic to warm-blooded animals at higher concentrations. Current techniques to quantify soil nitrate are either based on extensive soil sampling for analysis in the laboratory or using proximal sensing methods, which are less accurate. For instance, current techniques for measuring soil nitrate include using a cadmium reduction method which is costly and takes days or weeks between transferring the sample to a lab and then pretreating the sample and analyzing it to generate a soil nitrate reading for the sample. Due to the high expenses of soil analysis, farmers usually test their land only once every two to five years. Traditional techniques do not lend themselves to continuous measurement of soil nutrients.

[0025] In other approaches, image analysis may be performed using unmanned aerial vehicle (UAV) or satellite imagery. For instance, NASA launched a satellite named Soil Moisture Active Passive (SMAP) satellite designated to monitor soil moisture across the globe. Other methods include optical sensors which have great sensitivity towards nitrogen sensing however, greatly suffer from bulky spectrometer hardware, site-specific calibration, and lack accuracy for detecting nutrients that are not fully observed in the Vis-NIR region. Another approach uses a robotic platform that scans a specific field detecting different vegetation and assessing irrigation cycle for the different fields. Such image-based analytical methods require collecting thousands of images stitched together and large processing power to analyze the data. Such demanding hardware may limit the viability, economics, and deployment of such solutions, limiting their utility and adoption.

[0026] In improved implementations, miniaturized sensors may be provided to perform accurate in-situ measurements and deliver readings of soil nitrate on a continuous basis. Such sensor devices may include a microcontroller and a battery in a handheld device to measure the soil nutrients. The simplicity of the hardware allows for weeks or months of data collection before the batteries need to be replaced. The sensors may be calibrated on the soil samples ensuring high measurement accuracy in-situ. In some implementations, such improved in-situ sensor devices may include screen printed electrodes (SPE) enabling low cost, portability, and easy insertion in soil, among other example implementations. Such improved soil sensors for accurate in-situ measurements have the potential to fundamentally improve soil nitrate assessment and monitoring. Continuously monitoring nitrate levels in soil allows efficient use of fertilizers which reduces financial burden on farmers, among other example benefits. This leads to higher crop yield and in turn reducing food shortage worldwide. Tracking nitrate levels in soil also highlights any leaching of nitrate deeper into the soil polluting underground water source or runoff water with high nitrate concentrations into surrounding water bodies turning them toxic to marine life. A sensing platform that includes such in-situ nitrate sensing capabilities may be used to monitor nitrate levels on a daily or weekly basis to benefit governance perspectives for technical assistance, financial incentives and just from an environmental standpoint, monitoring, verification, and reporting, among other example advantages.

[0027] In one example, an improved sensor is provided configured to perform real-time continuous in-situ soil nitrate measurement through the use of electrochemistry. For instance, the sensor may include an ion-selective electrode (ISE) incorporating Tetradodecylammonium (TDDA) nitrate to increase selectivity towards nitrate ions. Some approaches have used open circuit potential (OCP) to measure the concentration of nitrate. However, open circuit potential measures the equilibrium state of soil which technically depicts bulk micro-environment and is not able to gauge dynamic soil phenomenon. In an improved implementing, electrochemical impedance spectroscopy (EIS) may instead be utilized to gauge the soil dynamics, which is not only scientifically significant, but also relevant to build an internet of things (loT)-enabled impedimetric platform for soil signal quantification.

[0028] As shown in FIG. 2, an improved sensor may implement a three-electrode system towards selective detection of nitrate ions in various soil textures. In one example, interfacial-chemical detection of nitrate ions is provided on the sensor using a specialized chemical layer modified surface for nitrate measurement. In FIG. 2, a diagrammatic representation 200 of an example three-electrode sensor is shown with the chemical coating 205 on the working electrode 140, together with a counter electrode 210, and a reference electrode 215, with the working electrode functionalized by the coating to bind with nitrate ions. Electrical contacts (e.g., 220, 230, 235) may be provided on the sensor 105 to correspond to the electrodes (e.g., 140, 210, 215) to allow additional logic circuitry to couple to the electrodes and read the impedance generated (e.g., across the working electrode 140 and reference electrode 210) at the sensor 105 based on the presence of nitrate ions (e.g., 240) in a soil sample. For instance, when a potential is applied to the electrode, while the electrode of the soil nitrate sensor is inserted into a mass of soil, an electrical double layer is formed above the coating 205 within the electrolyte bulk of the soil sample. From this electrical double layer, measurement of nitrate ions within the soil sample by the soil sensor is achieved.

[0029] In one example, the chemical coating (e.g., 205) to be deposited on the working electrode of the improved sensor may be composed of three major components as follows:

[0030] Component 1: This is the main sensing element of the system. In one example, Tetradodecylammonium (TDDA) nitrate may be used which promotes binding/interaction that is captured using electrochemical impedance spectroscopy to track soil nitrate.

[0031] Component 2: Serves as a physical stabilizer element in the composite coating. In one example, the plasticizer 2-Nitrophenyl octyl ether is added to enhance the coating's durability and flexibility providing better longevity and resilience against variations in temperature.

[0032] Component 3: Serves as a support membrane/network layer in this modified electrochemical sensor structure. In one example, Polymeric entities (PVC, PMMA, polyaniline, PEDOT : PSS and similar analogues) may then be added into the composite coating precursor to act as a film sealant that holds the composite against the electrode layer in a functionalized manner. [0033] The composite material (e.g., Components 1, 2 and 3) is then mixed to form a near homogeneous-like physical structure, for instance, by pipette-action, then vortexed (e.g., for 20 minutes) and sonicated (e.g., for 20 minutes) and is then ready to be coated onto the film. The resulting composite ink may then be coated onto the sensor by drop-casting, screen-printing or spin-coating to form a functionalized layer on the working electrode of the 3-layer electrode system (e.g., with precision such that the coating is not deposited on the other electrodes (e.g., reference electrode 210 and counter electrode 215)).

[0034] In some implementations, measurement of the soil nitrate may include impedemetric double layer analysis and modelling to study the interactions at the sensing film, soil nitrate interface and correlate modulations towards nitrate levels (e.g., Electrochemical Impedance Spectroscopy-EIS analysis). As shown in the simplified diagram 300 of FIG. 3, an interface is formed between the soil system (analyte) 305 and the functionalized sensor 105, and this interface is probed using an impedance-based detection technique. The presence of increasing levels of soil nitrate correlate to corresponding changes/modulation in impedance signals, and this is extracted at a specific frequency signature determined experimentally to detect only soil nitrate variations and thereby detect nitrate presence within the soil 305. For instance, the improved nitrate sensor 105 may be inserted in the soil 305 which contains nitrate ions that will bind to the chemical coating on the three-electrode system. The other end of the sensor may be connected to an electronic hardware platform 125, such as a portable potentiostat system, for in-situ on demand measurement and analysis, among other example features. In one example, the hardware platform may include a portable potentiostat system capable of measurements explained previously as well as recording and analyzing output data. Examples of commercially available portable potentiostat systems that the sensor system can be compatible with including but are not limited to: Palmsens emstat series, sensit/sensit BT, pocketstat 2, Metrohm PSTAT mini; among others.

[0035] FIG. 4A is an illustration 400a of an example environment, including a soil matrix region in which one or an array of soil sensor devices (e.g., 105a, 105b, etc.) may be deployed, where at least one of the soil sensor devices is a soil nitrate sensor, such as described in the examples herein. A variety of chemical compounds and soil attributes may be relevant to the analysis of the soil 110. Accordingly, a diverse array of soil sensors may be deployed within the soil region to capture readings describing the presence and concentration of various soil ions or components (e.g., nitrate, carbon, salinity, etc.). In addition to measuring the local health of the soil matrix in contact with the soil sensors 105a, 105b, given the relationship between the soil region's health and the health of nearby bodies of water (e.g., 405), monitoring the presence of nitrate in soil 110 (e.g., using soil sensors 105a, 105b) may serve as a proxy for measuring the likely concentration of nitrate and nearby streams, lakers, or other bodies of water (e.g., 405), among other example uses.

[0036] Turning to FIG. 4B, in one example, as soil textures are widely different, an example soil nitrate sensor may be calibrated against multiple different soil textures, in order to realize a richer calibration and utility of the soil sensor. FIG. 4B is a representation 400b of example soil textures, which may be included in a soil matrix, such as clay, sandy loam, and loamy clay, among other examples.

[0037] In one example, carbon screen printed electrodes, (Dropsens DRP 11L) with a carbon working and counter electrodes and Ag/AgCI reference electrode, are provided. Tetradodecylammonium nitrate (TDDA), high molecular weight Poly (vinyl chloride) (PVC), 2- Nitrophenyl octyl ether (NPOE), Tetrahydrofuran (THF) stabilized with BHT, potassium chloride, and sodium nitrate are used to generate the coating.

[0038] Clay, loamy clay, and sandy loam soils may be used to build a sensor calibration curve for an example soil nitrate sensor. These soil types may be selected as providing a full coverage of the soil texture triangle. In an example calibration of a soil nitrate sensor, air dried soil may be grinded and filtered through a 2 mm mesh to acquire fine soil particles. Dilutions of sodium nitrate (NaNO3) dissolved in deionized (DI) water may be prepared to cover the nitrate range from 0 ppm to 512 ppm. In one example, a mixture of 2 ml of soil and 1 ml of the corresponding NaNO3 solution are prepared for each soil type. Soil samples may be preprepared to provide adequate time to ensure all samples are homogenous.

[0039] In one example, to prepare the nitrate ion-selective coating, 22.5 mg of PVC, 30 mg of NPOE, and 7.5 mg of TDDA are dissolved in 275 pl of THF. The solution is mechanically stirred for 30 min followed by 20 min of sonication in a water bath at room temperature. These two steps are repeated until a homogenous clear solution is obtained. Afterwards, 2 pl of the solution are drop-cast onto the working electrode. The sensors are left to dry at room temperature for 4 hours to ensure complete evaporation of the THF solution. The sensors are then stored in 0.01 M NaNO3 solution overnight before starting the experiments. After the experiment, the sensors are stored in fresh 0.01 M NaNO3 solution until the next experiment.

[0040] In one example, the performance of an example improved sensor may be observed through an experiment where prepared soil samples are incubated on the sensors for 5 min before any measurement was taken. Electrochemical impedance spectroscopy (EIS) is run from 50 kHz to 5 Hz with an amplitude of 10 mV and 0 V DC bias. All plotting and statistical analyses were done using statistical and graphing software. A TDDA Gaussian simulation may be performed for visualization of its interaction. Soil is a reservoir of ions and computational tools can be used to visualize the interaction between the ions. The ionophore, more technically, the selectophore used in this study is the nitrate salt of Tri-dodecyl Methyl Ammonium (TDDA) ion, which is a zwitter ionic species having the big cationic TDDA and anionic nitrate part.

[0041] The species also tends to interact with other ions, majorly present in the soil including ammonium, phosphate, potassium and chloride. To understand the competitive interaction of TDDA-nitrate, the TDDA-N is introduced in a hostile environment surrounded by other major ions present in the soil and the Gaussian simulation is conducted using Hartree-Fock Method with basis set 6-31G-(d). The optimized structure of TDDA-nitrate with other ions is depicted in FIG. 5A and the simplified chemical depiction is demonstrated in FIG. 5B. FIG. 5C depicts the HOMO-LUMO orbital of the TDDA complex with all the competitive ions in its vicinity. [0042] TDDA has a very strong affinity towards NO3- having two strong non-covalent interactions with TDDA moiety. NH4+ has a strong affinity towards phosphate and can be seen interacting with phosphate and TDDA. Cl has a slight interaction with TDDA but there is a negligible chance of presence of Cl as Cl- in soil and hence formation of KCI is inevitable. FIG. 5C depicts HOMO-LUMO representation of the simulated complex and it can be seen that the HOMO electron cloud is surrounded over H2PO4-, whereas LUMO is surrounded over TDDA-nitrate, depicts suitable electron transfer from H2PO4- to NO3-, depicts strong interaction of TDDA with nitrate in the competitive micro-environment, filled with other ions.

[0043] In one example, the sensor response is calibrated against known doses prepared as prescribed previously to cover the range from 0 ppm to 512 ppm. As the PVC membrane contains TDDA, nitrate ions have the highest probability of binding to the ionophore. This change in charge on the electrode surface can be measured using EIS, such as depicted in the graphs 600a-e of FIG. 6 illustrating example performance of an example soil nitrate sensor. As the nitrate concentration in soil increases, the impedance of the electrical double layer (EDL) (which forms at the interface between the sensor electrodes and the soil) decreases. The calibrated dose response (CDR) is calculated using equation 1 where the percentage change in impedance %AZ_mod between the sample with <1 ppm nitrate concentration denoted as Z_0 while Z_m is the measured impedance at every concentration. Due to the slower diffusion rate in soil, every sample is incubated on the sensor for 5-min before measurement.

[0044] This ensures that the EDL reaches equilibrium. Measurements were taken in 1- min intervals up to 15-min where the impedance change was negligible around the 4-min mark. Thus 5-min was chosen as the incubation period. The mean and standard deviation was used in all reported results and plots. As shown in graphs 600c, 600d, and 600e, the sensor's sensitivity varies between the different soils which is related to the density and porosity of the different soil textures. Clay soil had a lower standard deviation across sensors with low resolution while the opposite was observed in sandy loam and loamy clay soils.

[0045] Although the ionophore is specific to nitrate ions, validated by computational results, it may not be immune to changes with the presence of other ions' concentrations. For this purpose, a cross reactivity study may be performed. For instance, a high specificity eliminates incorrect reporting of nitrate concentration due to other ions interfering with the electrical double layer. Three different samples were prepared from the same sandy loam soil stock where one has <1 ppm nitrate labeled as "0 ppm", a sample with 16 ppm nitrate, and the last sample had 25 ppm of potassium with 25 ppm of phosphorus as well labeled as "cocktail". Potassium and phosphorus were chosen as they change frequently similar to nitrate while other ions like carbon change slowly over months.

[0046] The graphs of FIG. 6 show the percentage impedance change of the measured impedance for every sample in the order that they were added. The results show that the impedance stays within ±4% from the <1 ppm sample while having a -21.3% change for the 16 ppm sample. The -4% change from the baseline Z_0 translates to a nitrate concentration of 3 ppm which in all agriculture soils would be denoted as extremely low.

[0047] The efficacy of the system to provide an accurate nitrate concentration from the measured impedance may be determined from the calibration. Table 1 shows the example results from an example calibration. The nitrate concentration of various soil samples of different textures may be measured using the reference cadmium reduction method and compared to the measured nitrate concentration using the soil nitrate sensor. The samples measured by the example sensors have their water content adjusted to 15% - 50% of the sample's weight mimicking agriculture conditions. In one example, the measurements are conducted using three different sensors (N = 3). Graph 600a in FIG. 6 shows an example Pearson correlation analysis between all the measured nitrate values using the proposed sensor system plotted on the y-axis and the reference nitrate values plotted on the x-axis showing a Pearson r of 0.992. Graphs 600b of FIG. 6 shows the two-way Anova between the reference nitrate and measured nitrate for the various soil textures.

TABLE 1: Example Nitrate Sensor Validation Results

[0048] In this particular example, all samples had a p-value of higher than 0.05 excluding one sample (p-value = 0.039) indicating insignificant difference between the reference method and measured nitrate. However, reporting 9.8 ppm rather than the actual 11.9 ppm concentration is not a huge difference but is statistically significant due to the small values being compared. These results show that creating three calibration curves of the textures at the three corners of the soil texture triangle to cover all soil textures is viable. The measured averages, standard deviation, and calculated error percentage are reported in Table 1. The proposed sensor had an error rate of less than 20% across all samples indicating it is suitable for in-situ measurement of soil nitrate. [0049] In one example, an ion-selective screen printed electrode is presented for in-situ soil nitrate sensing. The proposed sensor may not require any sample pre-treatment, and nonetheless accurately measure the nitrate of unbuffered soil samples in the range from 8 ppm to 512 ppm, among other examples. Electrochemical impedance spectroscopy (EIS) provides a nitrate-dependent response across the desired range irrespective of the soil type. Further, EIS provides immunity at frequencies higher than 200 Hz against environmental noise that is dominant at lower frequencies. Multiple (e.g., three) calibration curves may be derived during calibration of the sensor to cover multiple different soil types in the soil texture triangle.

[0050] In some implementations, the soil sensor devices may be hardwired or connect wirelessly (e.g., via an integrated wireless communication module) to supporting hardware capable of recording or performing analytics on the data generated by and received from the sensor devices. In some implementations, such systems may be locally deployed. In other implementations, such systems may include cloud-based computing systems (e.g., which the sensor devices may communicate with via a local gateway devices). In still other implementations, data storage and analytics/interpretation logic may be included on the sensor devices, among other example implementations. As one example, sensor devices may connect to a potentiostat system (e.g., a portable or battery-powered system) capable of performing calculations on measurements obtained from the sensor devices (e.g., discussed in the first and second approaches above), as well as recording and analyzing output data.

[0051] While the examples above illustrate example soil sensor implementations, it should be appreciated that these are presented as illustrative examples only and that a variety of other, additional interfacial soil sensors may be implemented based on and applying the principles described herein, including sensors with varying form factors and substrates, sensors applying different active, encapsulant, and/or sealant layers or coatings, and sensors capable of being used to measure other attributes of soil health (e.g., other soil organic matter compounds). Moreover, multiple sensor designs may be applied and integrated within a single sensor device to enable the device to concurrently measure multiple different soil health attributes (e.g., including nitrate) for a corresponding soil sample matrix and multi-variant analysis of the subject soil. Indeed, an array of soil health attributes may be advantageously measured using soil sensor systems such as described herein to develop measurements of the overall health of a plot of ground (e.g., farmland, ranch land, orchard plots, vineyards, and the like).

[0052] FIG. 7 is a simplified flow diagram 700 illustrating an example technique involving the use of an example in-situ soil sensor. The sensor may be deployed in a particular soil sample (either isolated in a container or representing a portion of a large plot of ground or soil). Electrodes of the soil sensor may be in prolonged and direct contact with the soil and may be configured to react to, measure, or detect chemical properties of the soil based on electrochemical reactions measured at the electrodes of the sensor. The sensor, through the electrodes, may generate signals 705 based on sensing film applied to one or more electrodes of the sensor. The film may include an active sensing component, encapsulant component, and sealant component and may enable the sensor to generate signals corresponding to nitrate levels of the soil. The signals may be sent 710 to a cooperating computing device, which include computer processing hardware and logic to determine 715 correlations between the generated signals and the nitrate level of the soil sample. In some implementations, the cooperating computing device may be different from and remote from the sensor device. In other implementations, the computing device and its hardware may be integrated with the sensor device. Measurement data may be generated 720 based on the determined correlation to indicate a measure of the corresponding soil health attribute. This information may be further used, stored, shared, or tracked to assess, on a continuing basis, the nitrate level in this portion of the soil, and through the deployment of multiple such sensors in multiple nearby soil samples, the overall nitrate attributes of a plot of land and its soil, among other example applications and benefits.

[0053] Note that in this document, references to various features (e.g., elements, structures, modules, components, steps, operations, characteristics, etc.) included in "one embodiment", "example embodiment", "an embodiment", "another embodiment", "some embodiments", "various embodiments", "other embodiments", "alternative embodiment", and the like are intended to mean that any such features are included in one or more embodiments of the present disclosure, but may or may not necessarily be combined in the same embodiments. Furthermore, the words "optimize," "optimization," and related terms are terms of art that refer to improvements in speed and/or efficiency of a specified outcome and do not purport to indicate that a process for achieving the specified outcome has achieved, or is capable of achieving, an "optimal" or perfectly speedy/perfectly efficient state.

[0054] In general, computing systems, which interface with a biosensor via a wired or wireless communication channel, can include electronic computing devices operable to receive, transmit, process, store, or manage data and information associated with the biosensor and other subsystems of the computing system. As used in this document, each of the terms "computer," "processor," "processor device," "microcontroller," or "processing device" is intended to encompass any suitable data processing apparatus. For example, while the microcontroller may be implemented, in some examples, as a single device within the computing system, in other implementations the processing functionality of the system may be implemented using a plurality of computing devices and processors, such as a fog computing system, server pools, a cloud computing system, or other distributed computing system including multiple computers. Further, any, all, or some of the computing devices may be adapted to execute any operating system, including Linux, UNIX, Microsoft Windows, Apple OS, Apple iOS, Google Android, Windows Server, etc., as well as virtual machines adapted to virtualize execution of a particular operating system, including customized and proprietary operating systems.

[0055] In some implementations, all or a portion of a computing platform may function as a wearable device, standalone biosensor device, or other sensor device. A sensor device may connect to and communicate with other computing devices through wired or wireless network connections. For instance, wireless network connections may utilize wireless local area networks (WLAN), such as those standardized under IEEE 802.11 family of standards, home-area networks such as those standardized under the Zigbee Alliance, personal-area networks such as those standardized by the Bluetooth Special Interest Group, cellular data networks, such as those standardized by the Third-Generation Partnership Project (3GPP), and other types of networks, having wireless, or wired, connectivity. For example, an endpoint device may also achieve connectivity to a secure domain through a bus interface, such as a universal serial bus (USB)-type connection, a High-Definition Multimedia Interface (HDMI), or the like.

[0056] It is also important to note that the operations and steps described with reference to the preceding FIGURES illustrate only some of the possible scenarios that may be executed by, or within, the system. Some of these operations may be deleted or removed where appropriate, or these steps may be modified or changed considerably without departing from the scope of the discussed concepts. In addition, the timing of these operations may be altered considerably and still achieve the results taught in this disclosure. The preceding operational flows have been offered for purposes of example and discussion. Substantial flexibility is provided by the system in that any suitable arrangements, chronologies, configurations, and timing mechanisms may be provided without departing from the teachings of the discussed concepts.

[0057] The following examples pertain to embodiments in accordance with this Specification. Example 1 is an apparatus including: a sensor to detect levels of nitrate in a sample of soil, the sensor including: a working electrode coated in a composite coating, where the composite coating includes: an active sensing component functionalized to detect nitrate; an encapsulant component; and a sealant component; and another electrode.

[0058] Example 2 includes the subject matter of example 1, where the encapsulant component includes a material to promote capture of mineral groups from the soil sample.

[0059] Example 3 includes the subject matter of any one of examples 1-2, where the sealant component acts as a support electrolyte for electrochemical transduction.

[0060] Example 4 includes the subject matter of any one of examples 1-3, where the other electrode includes a reference electrode.

[0061] Example 5 includes the subject matter of example 4, where the sensor further includes a counter electrode. [0062] Example 6 includes the subject matter of example 5, where the composite coating is layered over the working electrode.

[0063] Example 7 includes the subject matter of example 6, where the composite coating does not coat the reference electrode or the counter electrode.

[0064] Example 8 includes the subject matter of example 6, where the composite coating includes a mixture of the active sensing component, the encapsulant component, and the sealing component.

[0065] Example 9 includes the subject matter of any one of examples 1-8, further including circuitry to: apply a voltage; and detect impedance at the sensor based on presence of nitrate in the soil sample.

[0066] Example 10 includes the subject matter of example 9, where the voltage includes a pulsed voltage signal applied across the working electrode and reference electrode.

[0067] Example 11 includes the subject matter of example 10, where the pulsed voltage signal is applied according to a particular frequency associated with detection of varied levels of nitrate.

[0068] Example 12 includes the subject matter of any one of examples 9-11, further including a communication module to send a signal to another computing device to communicate the detected impedance.

[0069] Example 13 includes the subject matter of any one of examples 1-12, where the sensor includes an in-situ soil sensor.

[0070] Example 14 includes the subject matter of any one of examples 1-13, where the active sensing component includes Tetradodecylammonium nitrate.

[0071] Example 15 includes the subject matter of any one of examples 1-14, where the encapsulant component includes a plasticizer.

[0072] Example 16 includes the subject matter of any one of examples 1-15, where the sealant component includes a polymeric compound. [0073] Example 17 is a method including: applying a voltage across a working electrode and a reference electrode of an in-situ soil sensor deployed in a soil sample, where the working electrode is coated with a composite coating functionalized for the detection of nitrate within soil, and the composite coating includes an active sensing component, an encapsulant component, and a sealant; and generating impedance signals at the in-situ soil sensor, where the impedance signals are generated based on concentration of nitrate in the soil sample, where the active sensing component is configured to detect the nitrate.

[0074] Example 18 includes the subject matter of example 17, further including determining, from the impedance signals, a concentration of nitrate within the soil sample.

[0075] Example 19 includes the subject matter of example 18, further including transmitting a signal to another computing device to identify the impedance signals to the other computing device, where the other computing device determines the concentration of nitrate within the soil sample.

[0076] Example 20 includes the subject matter of any one of examples 17-19, where the impedance is measured based on the application of the voltage across the working electrode and the reference electrode.

[0077] Example 21 includes the subject matter of any one of examples 17-20, where the encapsulant component includes a material to promote capture of mineral groups from the soil sample.

[0078] Example 22 includes the subject matter of any one of examples 17-21, where the sealant component acts as a support electrolyte for electrochemical transduction.

[0079] Example 23 includes the subject matter of any one of examples 17-22, where the other electrode includes a reference electrode.

[0080] Example 24 includes the subject matter of example 23, where the sensor further includes a counter electrode.

[0081] Example 25 includes the subject matter of example 24, where the composite coating is layered over the working electrode. [0082] Example 26 includes the subject matter of example 25, where the composite coating does not coat the reference electrode or the counter electrode.

[0083] Example 27 includes the subject matter of example 25, where the composite coating includes a mixture of the active sensing component, the encapsulant component, and the sealing component.

[0084] Example 28 includes the subject matter of any one of examples 17-27, where the voltage includes a pulsed voltage signal applied across the working electrode and reference electrode.

[0085] Example 29 includes the subject matter of example 28, where the pulsed voltage signal is applied according to a particular frequency associated with detection of varied levels of nitrate.

[0086] Example 30 includes the subject matter of example 17-27, further including sending a signal to another computing device to communicate the detected impedance.

[0087] Example 31 includes the subject matter of any one of examples 17-30, where the active sensing component includes Tetradodecylammonium nitrate.

[0088] Example 32 is a system including means to perform the method of any one of examples 17-31.

[0089] Example 33 is a system including: a sensor device including: a plurality of electrodes, where the plurality of electrodes includes a working electrode coated in a composite sensing coating, where the composite sensing coating includes an active sensing component functionalized to detect nitrate, an encapsulant component, and a sealant component; and circuitry to generate an impedance based on concentration of nitrate in a soil sample when in contact with the working electrode; and an analysis system including: a processor; analytics logic executable by the processor to determine, from the impedance, a value of the concentration of nitrate in the soil sample.

[0090] Example 34 includes the subject matter of example 33, further including a plurality of sensor devices deployed in a plurality of soil samples within an environment. [0091] Example 35 includes the subject matter of any one of examples 33-34, where the sensor device includes an in situ soil sensor.

[0092] Example 36 includes the subject matter of any one of examples 33-35, where the encapsulant component includes a material to promote capture of mineral groups from the soil sample.

[0093] Example 37 includes the subject matter of any one of examples 33-36, where the sealant component acts as a support electrolyte for electrochemical transduction.

[0094] Example 38 includes the subject matter of any one of examples 33-37, where the other electrode includes a reference electrode.

[0095] Example 39 includes the subject matter of example 38, where the sensor device further includes a counter electrode.

[0096] Example 40 includes the subject matter of example 39, where the composite coating is layered over the working electrode.

[0097] Example 41 includes the subject matter of example 40, where the composite coating does not coat the reference electrode or the counter electrode.

[0098] Example 42 includes the subject matter of any one of examples 40-41, where the composite coating includes a mixture of the active sensing component, the encapsulant component, and the sealing component.

[0099] Example 43 includes the subject matter of any one of examples 33-42, where the sensor device further includes circuitry to: apply a voltage; and detect impedance at the sensor based on presence of nitrate in the soil sample.

[00100] Example 44 includes the subject matter of example 43, where the voltage includes a pulsed voltage signal applied across the working electrode and reference electrode.

[00101] Example 45 includes the subject matter of example 44, where the pulsed voltage signal is applied according to a particular frequency associated with detection of varied levels of nitrate. [00102] Example 46 includes the subject matter of any one of examples 43-45, where the sensor device further includes a communication module to send a signal to another computing device to communicate the detected impedance.

[00103] Example 47 includes the subject matter of any one of examples 33-46, where the sensor includes an in-situ soil sensor.

[00104] Example 48 includes the subject matter of any one of examples 33-47, where the active sensing component includes Tetradodecylammonium nitrate.

[00105] Example 49 includes the subject matter of any one of examples 33-48, where the encapsulant component includes a plasticizer.

[00106] Example 50 includes the subject matter of any one of examples 33-49, where the sealant component includes a polymeric compound.

[00107] Although the present disclosure has been described in detail with reference to particular arrangements and configurations, these example configurations and arrangements may be changed significantly without departing from the scope of the present disclosure. Numerous other changes, substitutions, variations, alterations, and modifications may be ascertained to one skilled in the art and it is intended that the present disclosure encompass all such changes, substitutions, variations, alterations, and modifications as falling within the scope of the appended claims.

Claims

CLAIMS:

1. An apparatus comprising: a sensor to detect levels of nitrate in a sample of soil, the sensor comprising: a working electrode coated in a composite coating, wherein the composite coating comprises: an active sensing component functionalized to detect nitrate; an encapsulant component; and a sealant component; and another electrode.

2. The apparatus of Claim 1, wherein the encapsulant component comprises a material to promote capture of mineral groups from the soil sample.

3. The apparatus of any one of Claims 1-2, wherein the sealant component acts as a support electrolyte for electrochemical transduction.

4. The apparatus of any one of Claims 1-3, wherein the other electrode comprises a reference electrode.

5. The apparatus of Claim 4, wherein the sensor further comprises a counter electrode.

6. The apparatus of Claim 5, wherein the composite coating is layered over the working electrode.

7. The apparatus of Claim 6, wherein the composite coating does not coat the reference electrode or the counter electrode.

8. The apparatus of Claim 6, wherein the composite coating comprises a mixture of the active sensing component, the encapsulant component, and the sealing component.

9. The apparatus of any one of Claims 1-8, further comprising circuitry to: apply a voltage; and detect impedance at the sensor based on presence of nitrate in the soil sample.

10. The apparatus of Claim 9, wherein the voltage comprises a pulsed voltage signal applied across the working electrode and reference electrode.

11. The apparatus of Claim 10, wherein the pulsed voltage signal is applied according to a particular frequency associated with detection of varied levels of nitrate.

12. The apparatus of any one of Claims 9-11, further comprising a communication module to send a signal to another computing device to communicate the detected impedance.

13. The apparatus of any one of Claims 1-12, wherein the sensor comprises an in-situ soil sensor.

14. The apparatus of any one of Claims 1-13, wherein the active sensing component comprises Tetradodecylammonium nitrate.

15. The apparatus of any one of Claims 1-14, wherein the encapsulant component comprises a plasticizer.

16. The apparatus of any one of Claims 1-15, wherein the sealant component comprises a polymeric compound.

17. A method comprising: applying a voltage across a working electrode and a reference electrode of an in-situ soil sensor deployed in a soil sample, wherein the working electrode is coated with a composite coating functionalized for the detection of nitrate within soil, and the composite coating comprises an active sensing component, an encapsulant component, and a sealant; and generating impedance signals at the in-situ soil sensor, wherein the impedance signals are generated based on concentration of nitrate in the soil sample, wherein the active sensing component is configured to detect the nitrate.

18. The method of Claim 17, further comprising determining, from the impedance signals, a concentration of nitrate within the soil sample.

19. The method of Claim 18, further comprising transmitting a signal to another computing device to identify the impedance signals to the other computing device, wherein the other computing device determines the concentration of nitrate within the soil sample.

20. The method of any one of Claims 17-19, wherein the impedance is measured based on the application of the voltage across the working electrode and the reference electrode.

21. The method of any one of Claims 17-20, wherein the encapsulant component comprises a material to promote capture of mineral groups from the soil sample.

22. The method of any one of Claims 17-21, wherein the sealant component acts as a support electrolyte for electrochemical transduction.

23. The method of any one of Claims 17-22, wherein the other electrode comprises a reference electrode.

24. The method of Claim 23, wherein the sensor further comprises a counter electrode.

25. The method of Claim 24, wherein the composite coating is layered over the working electrode.

26. The method of Claim 25, wherein the composite coating does not coat the reference electrode or the counter electrode.

27. The method of Claim 25, wherein the composite coating comprises a mixture of the active sensing component, the encapsulant component, and the sealing component.

28. The method of any one of Claims 17-27, wherein the voltage comprises a pulsed voltage signal applied across the working electrode and reference electrode.

29. The method of Claim 28, wherein the pulsed voltage signal is applied according to a particular frequency associated with detection of varied levels of nitrate.

30. The method of any one of Claims 17-29, further comprising sending a signal to another computing device to communicate the detected impedance.

31. The method of any one of Claims 17-30, wherein the active sensing component comprises Tetradodecylammonium nitrate.

32. A system comprising means to perform the method of any one of Claims 17-31.

33. A system comprising: a sensor device comprising: a plurality of electrodes, wherein the plurality of electrodes comprises a working electrode coated in a composite sensing coating, wherein the composite sensing coating comprises an active sensing component functionalized to detect nitrate, an encapsulant component, and a sealant component; and circuitry to generate an impedance based on concentration of nitrate in a soil sample when in contact with the working electrode; and an analysis system comprising: a processor; analytics logic executable by the processor to determine, from the impedance, a value of the concentration of nitrate in the soil sample.

34. The system of Claim 33, further comprising a plurality of sensor devices deployed in a plurality of soil samples within an environment.

35. The system of any one of Claims 33-34, wherein the sensor device comprises an in situ soil sensor.

36. The system of any one of Claims 33-35, wherein the sensor device comprises the apparatus of any one of Claims 1-16.

37. The system of any one of Claims 33-36, wherein the active sensing component comprises Tetradodecylammonium nitrate.