SYSTEM AND METHOD FOR DETERMINING AQUEOUS NITRATE CONCENTRATION IN SOLUTION CONTAINING DISSOLVED ORGANIC CARBON
20220229036 · 2022-07-21
Inventors
Cpc classification
G01N21/6486
PHYSICS
G01N2021/646
PHYSICS
International classification
Abstract
The invention relates to a system for determining a level of nitrate in a water sample, including: (a) an optical flow cell which is at least partially transparent and which is configured to contain a sample of water; (b) a first illuminator for illuminating the sample by light in a first wavelength, and a first photodetector for collecting the first-wavelength illumination, following the light passage through the sample; (c) a second illuminator for illuminating the sample within the cell by light in a second, fluorescence-exciting wavelength, and a second photodetector for collecting illumination in a third, fluorescence-emission wavelength from the sample; and (d) an analysis unit for determining the combined effect of nitrate+DOC within the sample on the absorbance of light, determining a concentration of DOC within the sample based on fluorescence emission from the sample, and subtracting the effect of DOC from the combined effect of nitrate+DOC on the absorbance, thereby to determine a concentration of nitrate within the sample.
Claims
1. A system for determining a level of nitrate in a water sample, comprising: a. an optical flow cell which is at least partially transparent and which is configured to contain a sample of water; b. a first illuminator for illuminating the sample within the cell by light in a first wavelength, and a first photodetector for collecting the first-wavelength illumination, following the light passage through the sample; c. a second illuminator for illuminating the sample within the cell by light in a second, fluorescence-excitation wavelength, and a second photodetector for collecting illumination in a third, fluorescence-emission wavelength from the sample; and d. an analysis unit for: d.1. determining a combined effect of nitrate+DOC within the sample on absorbance, said combined effect of nitrate+DOC being proportional to a rate of absorbance of light due to said illumination by said first illuminator, said absorbance being determined from a difference between a level of illumination by said first illuminator and a level of collected illumination by said first photodetector; d.2. determining a concentration of DOC within the sample, said DOC concentration being proportional to an intensity of said fluorescence emission from the sample due to said illumination by said second illuminator, and as collected by said second photodetector; and d.3. subtracting said effect of DOC from said effect of nitrate+DOC on the absorbance, thereby to determine the concentration of nitrate within the sample.
2. The system according to claim 1, further comprising a first look-up table, for converting the difference as measured in step (d.1) to a nitrate+DOC concentration level.
3. The system according to claim 1, further comprising a second look-up table for converting said fluorescence emission as measured in step (d.2) to a DOC concentration level.
4. The system according to claim 1, further comprising a third look-up table, for calibrating the subtraction result of step (d.3) based on a specific type of DOC known to be in the specific tested sample, wherein said type of DOC reflects a specific chemical DOC composition.
5. The system according to claim 2, wherein a mathematical equation is used to convert absorbance and/or fluorescence measurements to concentration levels.
6. The system according to claim 4, further comprising one or more additional illuminators, and one or more additional photodetectors, in order to measure absorbance and/or fluorescence emission in additional wavelengths, thereby to determine a specific type of DOC within the sample.
7. The system according to claim 6, further comprising one or more additional look-up tables, for converting the measured absorbance and/or fluorescence emissions in said additional wavelengths to a specific type of DOC.
8. The system according to claim 1, wherein said analysis unit comprises a mathematical model to extract the value of nitrate based on said measurements of absorption and fluorescence, wherein the mathematical model comprising:
9. The system according to claim 1, wherein said analysis unit applies a machine learning technique comprising: a. generating a plurality of absorption and fluorescence measurements for different values of nitrate concentration and various DOC types and respective concentrations; b. selecting and adapting one or more deep learning networks; c. training at least one of the selected deep learning networks; and d. using the trained network to calculate the nitrate concentration based on absorption and fluorescence measurements.
10. The system according to claim 1, wherein said first wavelength is selected from the bands of 200-250 nm and 280-320 nm.
11. The system according to claim 1, wherein said second excite wavelength is within a band of 225 nm-600 nm.
12. The system according to claim 1, wherein said third, fluorescence em1ss10n wavelength is within a band of 250 nm-700 nm.
13. The system according to claim 1, further comprising a first filter for assuring that radiation only in the first wavelength arrives the first photodetector.
14. The system according to claim 1, further comprising a second filter for assuring that radiation only in the third wavelength arrives the second photodetector.
15. The system according to claim 1, wherein the water sample is taken from a soil or from a water reservoir.
16. The system according to claim 1, wherein the water sample is collected from a cultivated soil by a porous interface, and is provided in a low flow-rate through the optical flow cell.
17. A method for determining a concentration rate of nitrate in a water sample, comprising: a. providing the sample; b. illuminating the sample in a first wavelength, and determining a combined effect of nitrate+DOC within the sample on absorbance, said concentration of nitrate+DOC being proportional to a rate of absorbance of light due to said illumination in said first wavelength, said absorbance being determined from a difference between a level of illumination in said first wavelength before passing the sample and a level of collected illumination in said first wavelength following passage through the water sample; c. illuminating the water sample in a second, exciting wavelength, and determining an effect of DOC within the sample, said effect of DOC being proportional to an intensity of fluorescence emission from the sample in a third wavelength due to said illumination of the sample in said second wavelength; and d. deducting the effect of DOC from the combined effect of nitrate+DOC on the absorbance, as determined, thereby to obtain the concentration of nitrate in the sample.
18. The method according to claim 17, further using a first look-up table for converting said absorbance to a nitrate+DOC concentration levels.
19. The method according to claim 17, further using a second look-up table for converting said fluorescence emission to a DOC concentration level.
20. The method according to claim 17, further using a third look-up table, for calibrating the deduction result based on a specific type of DOC known to be in the specific tested sample, wherein said type of DOC reflects a specific chemical DOC composition.
21. The method according to claim 18, wherein a mathematical equation is used to convert absorbance and/or fluorescence measurements to concentration levels.
22. The method according to claim 17, further measuring absorbance and/or fluorescence emission in additional wavelengths, thereby to determine a specific type of DOC within the sample.
23. The method according to claim 17, further comprising use of a mathematical model to extract the value of nitrate based on said measurements of absorption and fluorescence, wherein the mathematical model comprising:
24. The method according to claim 17, wherein said first wavelength is selected from the bands of 200-250 nm, or 280-320 nm.
25. The method according to claim 17 wherein said second, excite wavelength is in the order of 225-400 nm.
26. The method according to claim 17, wherein said third, fluorescence emission wavelength is in the order of 250 nm-500 nm.
27. The method according to claim 17, wherein the water sample is taken from a soil or from a water reservoir.
28. The method according to claim 17, further applying a machine learning technique, comprising the steps of: a. generating a plurality of absorption and fluorescence measurements for different values of nitrate concentration and different types of DOC, and their respective DOC concentrations; b. selecting one or more deep learning networks; c. training the network and selecting a one with a best performance; and d. calculating the nitrate concentration based on said absorption and fluorescence measurements.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
[0050] In the drawings:
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DETAILED DESCRIPTION
[0059] The invention provides an optical system for determining a level of nitrate in a cultivated soil, which overcomes drawbacks of similar prior art systems. In brief: [0060] a. The system can use low-cost and low-energy components, such as LED type light sources and semiconductor type photodetectors; [0061] b. While prior art systems are based on absorption measurement only, the system of the invention measures: (i) absorption resulting from illumination by a first light source to measure a combined effect of both nitrate and DOC; and (ii) a florescence emission resulting from illumination by a second light source to measure the concentration of DOC, and cancel its effect on the absorption measurement by use of a signal processing algorithm. Such a dual-measurement technique enables separation of the effect of DOC from the combined effect of nitrate+DOC on the measurement, thereby the technique enables determination of the actual concentration of nitrate in the water sample. This structure and analysis eliminate the necessity to utilize a cumbersome system with a relatively high power and high-cost light-source, and the necessity to utilize a spectrometer in order to determine an optimal operational frequency in which the effect of DOC on the measurement is minimal; [0062] c. The system applies algorithms to calculate the nitrate concentration; [0063] d. The system applies one or more databases for calibrating the measurement. Optionally, several databases are used to accommodate for different types of soils (therefore different compositions of materials and optical properties within the DOC); [0064] e. A second embodiment of the system of the invention applies a mathematical model of the DOC concentration as a function of fluorescence power and the light absorption as a function of nitrate+DOC concentration and solves an equation of two variables; [0065] f. A third embodiment of the system of the invention applies many measurements to train a deep learning network, which is later used to calculate the nitrate concentration based on two measurements of absorption and fluorescence measurements.
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[0069] Soils from five different agricultural fields of the coastal plain of Israel, were collected and analyzed for this study, including: organic and conventional greenhouses for vegetable crops, open field which is used for rotating mixed crop, and a citrus's orchard. These sites were chosen to represent a spectrum of typical agricultural practices on different soils. In addition, commercial hummus soil mixture from “Dovrat” commercial compost was also examined to represent a potential impact of compost application in agriculture on the soil water DOC.
[0070] Soil solution samples were obtained from a soil and DDW mixture. The mixtures were left to stand for 24 hours to allow the solution to achieve a chemical equilibrium with the soil natural DOC. The soil phase and liquid phase in each sample was separated by a standard laboratory centrifuge, and the suspended solids were removed by 0.22 μm membrane filters. The samples were then diluted to obtain a series of replicas reflecting different DOC concentrations. Each replica of DOC concentration was spiked with a specific volume of 10,000 ppm standard potassium nitrate solution, to obtain between 4 to 6 different nitrate concentrations per each level of DOC. As a result, a matrix composed of 25 to 30 samples of different combinations of DOC and nitrate concentrations, ranging from zero to about a 1000 ppm nitrate, and between zero to about 100 ppm DOC was created from the soil extracts at each agricultural site.
[0071] The initial values of DOC and Total Nitrogen (TN) in each sample were estimated by an Analytic Jena multi N/C 2100s TOC/TN analyzer, while the nitrate concentration in each sample was determined by Dionex ICS 5000 Ion chromatograph. The absorption of each of the samples at 300 nm was determined using TECAN Spark 10M multimode microplate reader spectrophotometer. The light absorbance was defined by the Lambert-Beer equation:
[0072] where I reflects the light intensity after passing through the examined solution and Io is the light intensity of the source, or the light intensity of the source after passing through DDW as a reference.
[0073] A fluorescence spectroscopy technique was applied to measure the DOC concentration in the examined solution. The fact that the DOC fluorescence spectroscopy is not affected by the presence of nitrate in the solution makes it easy to separate the unique effect of absorption by nitrate and DOC. Fluorescence measurements were performed by TECAN Infinite M200 spectrophotometer with excitation (EX)/Emission (EM) at 350/451 nm. The results of the chemical and spectral analyses were used to obtain a series of matrix databases containing nitrate and DOC concentrations and absorbance at 300 nm (one per sampling site). In theory, the application of a UV absorption technique on aqueous nitrate solutions should be resulted in a clear linear correlation between the absorption rate and nitrate concentration.
[0074] Where: Nitrate is the nitrate concentration (ppm), DOC indicates the DOC concentration (ppm), Abs indicates the absorbance as measured at 300 nm (arbitrary units), and P.sub.00, P.sub.10, and P.sub.01 are the coefficients as obtained from the regressions.
[0075] Fluorescence emission at 451 nm from samples with known DOC concentrations were used to develop a calibration curve for each site, as shown in
[0076] Measurements of DOC concentration, as achieved from fluorescence emission at 451 nm, along with the total absorbance at 300 nm, enabled the estimation of nitrate concentration in a series of solutions obtained from the previously mentioned field sites (
[0077] In the embodiment above, a calibration with respect to the concentration of nitrate uses a prior knowledge of the type of DOC at the soil where the specific nitrate-concentration determination is actually performed (i.e., what is the additional effect of the specific mixture of the DOC at that area on the absorption). Based on this prior knowledge, a calibration is performed.
[0078] In still another embodiment, the identification of the type of DOC at the area may be obtained automatically. In one alternative, the system measures the nitrate concentration in various DOC types by use of a two-phase procedure, as follows: [0079] a. A first phase in which three optical measurements of the solution are performed. The optical measurement may include either two absorption measurements and one fluorescence measurement, or one absorption measurement and two fluorescence measurement. Other combinations of absorbance and fluorescence measurements at many wavelengths may be used to get more accurate determination of the DOC type. Each optical measurement is performed at a different wave length; [0080] b. A second phase in which, based on the results of the above first-phase measurements and prior-knowledge from data-base look-up tables that were prepared for different DOCs in advance, the system identifies which specific calibration equation or calibration curve to use.
[0081] In an embodiment of the invention, the analysis unit comprises a mathematical model to extract the value of nitrate based on the measurements of absorption, based on the Beer Lambert equation:
[0082] Where A is the measured absorbance at a given wavelength (λ(nm)), ε(λ) is the molar attenuation coefficient (L mol.sup.−1 cm.sup.−1) at a given wavelength (λ(nm)), C is the examined Ion concentration (mol L.sup.−1) and l is an optical pathlength (cm).
[0083] Nitrate concentration can be then obtained by a set of two equations with two unknowns as following:
[0084] From consolidating equation (1)+(2) we can extract the nitrate concentration (equation (3)):
[0085] Where A is the measured absorbance at a given wavelength (λ.sub.1,2 (nm)), εNO.sub.3.sup.−1, Doc (λ.sub.1,2 (nm)) is a molar attenuation coefficient for either the nitrate or the DOC (L mol.sup.−1 cm.sup.−1) at a given wavelength (λ.sub.1,2 (nm)), C.sub.DOC is the DOC concentration (mol L.sup.−1) as obtained from said second photodetector, C.sub.NO3 is a nitrate concentration (mol L.sup.−1), and/is an optical pathlength (cm).
[0086] In still another embodiment, a machine learning technique may be used. The machine learning may include the following phases: [0087] a. Generation of many absorption and fluorescence measurements for different values of nitrate concentration and various DOC types and respective concentrations; [0088] b. Selection and adaption of one or more deep learning networks from known results; [0089] c. Training of the network and selection of a one promising a best performance; [0090] d. Use of the trained network to calculate the nitrate concentration based on absorption and fluorescence measurements in a manner as described above.
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[0092] While some embodiments of the invention have been described by way of illustration, it will be apparent that the invention can be carried into practice with many modifications, variations and adaptations, and with the use of numerous equivalents or alternative solutions that are within the scope of persons skilled in the art, without departing from the spirit of the invention or exceeding the scope of the claims.