See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/349428959 Determination of soil nutrients (NPK) using optical methods: a mini review Article in Journal of Plant Nutrition · February 2021 DOI: 10.1080/01904167.2021.1884702 CITATIONS READS 28 17,199 5 authors, including: Revati Potdar 8 PUBLICATIONS 34 CITATIONS Alok Verma Society for Applied Microwave Electronics Engineering & Research 28 PUBLICATIONS 33 CITATIONS SEE PROFILE SEE PROFILE A. Kulkarni Symbiosis International University 157 PUBLICATIONS 1,988 CITATIONS SEE PROFILE All content following this page was uploaded by Revati Potdar on 13 October 2021. The user has requested enhancement of the downloaded file. Journal of Plant Nutrition ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/lpla20 Determination of soil nutrients (NPK) using optical methods: a mini review Revati P. Potdar , Mandar M. Shirolkar , Alok J. Verma , Pravin S. More & Atul Kulkarni To cite this article: Revati P. Potdar , Mandar M. Shirolkar , Alok J. Verma , Pravin S. More & Atul Kulkarni (2021): Determination of soil nutrients (NPK) using optical methods: a mini review, Journal of Plant Nutrition, DOI: 10.1080/01904167.2021.1884702 To link to this article: https://doi.org/10.1080/01904167.2021.1884702 Published online: 16 Feb 2021. Submit your article to this journal View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=lpla20 JOURNAL OF PLANT NUTRITION https://doi.org/10.1080/01904167.2021.1884702 Determination of soil nutrients (NPK) using optical methods: a mini review Revati P. Potdara, Mandar M. Shirolkarb, Alok J. Vermac, Pravin S. Morea, and Atul Kulkarnib a Nano Material Application Laboratory, Department of Physics, The Institute of Science, Dr. Homi Bhabha State University, Mumbai, India; bSymbiosis Centre for Nanoscience and Nanotechnology, Symbiosis International (Deemed University), Pune, India; cSociety for Applied Microwave Electronics Engineering and Research (SAMEER), IIT Campus, Powai, Mumbai, India ABSTRACT ARTICLE HISTORY In the present situation, plants have to meet the food supply demand for a large and increasing population. In order to get high yield, it is essential for the plantations to be nourished with soil containing an appropriate amount of nutrients like Nitrogen (N), Phosphorus (P) and Potassium (K). Various methods such as, physical (optical) and chemical (electrochemistry) have been adopted to analyze the soil nutrients. This paper reviewed optical methods of soil nutrient detection suitable for building a portable sensor because it can sense nutrients in dry soil samples directly without the need for complicated sample pretreatments. We concentrate and elaborate on optical methods of experimentation. Starting from laboratory testing standards followed in India we move on to off the lab crude methods like soil testing kits and colorimetric approaches. Further, we review the effective and utilitarian spectroscopic approaches and also the technologically advanced and latest methods like imaging systems, microfluidic, and micro-electromechanical system (MEMs) based sensors. However, optical methods are affected by environmental factors that affect the accuracy of sensor results. This paper then discusses boons and curses of optical methods of soil nutrient sensing. It also explains briefly the working of each method and mentions the most recent advancements made in the given testing method. We hope that this paper can serve as a guide for the experimenters and give a direction for carrying out further work required in developing a portable and efficient soil NPK detection sensor. Received 10 August 2020 Accepted 29 September 2020 KEYWORDS Colorimetry; IR spectroscopy; optical sensing; portable sensor; soil nutrients Introduction Soil contains 16 essential elements like carbon, hydrogen, oxygen, nitrogen, calcium, etc. for the proper completion of the plants life cycle. Out of these, three macronutrients Nitrogen (N), Phosphorus (P) and Potassium (K), (NPK), are especially important because they play a very significant role in the development of plants and are required in large quantities (Basu 2011). Nitrogen is a major component of chlorophyll and amino acids and is an important factor in plant growth. Phosphorus is an important constituent of plant deoxyribonucleic acid (DNA) and ribonucleic acid (RNA), it plays an important role in the development of roots and production of seeds. Whereas, Potassium plays an indirect role in the plant development like activating over 80 enzymes throughout the plant. Thus, these elements are very important and must be present at CONTACT Pravin S. More atul.kulkarni@scnn.edu.in ß 2021 Taylor & Francis Group, LLC pravin.more@gov.in; pravin.more@iscm.ac.in; Atul Kulkarni atul.kulkarni@scnn.edu.in; 2 R. P. POTDAR ET AL. optimum level in the soil for proper plant growth, and if required, their quantity must be replenished by the application of NPK fertilizers. Insufficient use of fertilizers results in poor plant yield, whereas the excessive use of fertilizers makes the soil contaminated. But to maximize crop production and due to lack of infrastructure, farmers in India are seen to supply fertilizers to the soil blindly. It is not feasible for the farmers to test their soil nutrient concentration at regular intervals due to economic problems and due to the nonavailability of the soil testing laboratory in close vicinity of the field. Also, it takes months for the result of the soil tests to become available to the farmers. Thus, there is a need for rapid and on-the-go measurement of soil nutrients. A low-cost soil testing probe will help the farming community to check the nutrient status on the field itself and encourage the judicious use of fertilizers to enhance the yield and hence increase the profitability. Researchers worldwide are trying to solve the problem of building an in situ sensor and are constantly increasing the knowledge on measurement of soil macronutrients (NPK). Currently, techniques like optical sensing, laboratory measurement, ion-selective electrodes, chemical methods, Inductively Coupled Plasma (ICP) spectroscopy, and fluorescence spectroscopy are widely known. But most of these techniques are either costly, involve complicated setups, or are unsuitable for in situ measurement. The most frequently used methods are: Electrochemical sensing which makes use of ion-selective electrodes that generate a current or voltage in response to the activity of selected ions. Optical sensing which uses either spectroscopic or colorimetric technique. According to the literature review, optical sensing seems to be a promising candidate for building a low-cost, portable soil nutrient sensor because optical sensors are portable, easy to use, and are small in size. They have attractive characteristics like low cost, light-weight, and high flexibility (Tagad et al. 2013). The optical sensing techniques are being studied by researchers worldwide because they have several advantages over electrical methods, such as high sensitivity, selectivity, repeatability, and immunity from electromagnetic interference. This sensing technique records and analyses the reflectance, absorption, or transmittance spectrum of materials to identify them in a nondestructive manner. In agriculture, for sensing purpose, the amount of energy reflected from the soil surface is usually measured (Stenberg et al. 2010). In the light of soil macronutrient sensing, this paper reviews standard protocol followed for laboratory soil testing in Section 2; setting up the rationale behind portable soil testing sensor. The paper then moves onto reviewing the optical techniques like spectroscopic, colorimetric technique and imaging technique in detail in Section 3. Followed by conclusion in Section 4. Soil NPK estimation using standard protocol An elaborate description of the standard laboratory testing procedure followed in India is given in the section below. Table 1 provides soil fertility level classification of NPK depending on their kg/ha values and is required for interpreting the test results. Table 1. Soil fertility levels of nutrients N, P and K (Government Documentation Manual 2009) (Shah and Pawar 2009). Soil fertility levels Very low Low Medium Moderately high High Very high Nitrogen (kg/ha) Less than 140 141–280 281–420 421–560 561–700 Greater than 700 Phosphorus (kg/ha) Less than 7 7.1–14 14.1–21 21.1–28 28.1–35 More than 35 Potassium (kg/ha) Less than 100 101–150 151–200 201–250 251–300 More than 300 JOURNAL OF PLANT NUTRITION 3 Determination of available phosphorus from soil (Olsen method) (Pansu and Gautheyrou 2006) Olsen’s reagent is made up of sodium bicarbonate and is used for extracting phosphorus from soils with pH > 6.5. It also works well with calcareous soils. It separates Ca-phosphates, Al-phosphates and Fe-phosphates in the soil by precipitating Ca as CaCO3. Thus, extract obtained by adding Olsen’s reagent to soil and filtering the content contains our required phosphorus which is further treated with ammonium molybdate to obtain blue colored solution of phosphor– molybdate complex. The intensity of the blue color provides a measure for the concentration of P, in the test solution. Extraction and estimation 1. 2. 3. 4. 5. 6. Add two spoons of Darco-G-60 followed by 50 ml of 0.5 NaHCO3 solution to 2.5 g soil Cork the flask and shake for 30 minutes then filter the contents to collect the filtrate. Pipette out 5 ml of the NaHCO3 exact into 25 ml volumetric flask. Add two drops of 2, 4-paranitrophenol and 5 N H2SO4 drop by drop with intermittent shaking till yellow color disappears. Dilute the contents to about 20 ml with distilled water and then add 4 ml solution containing ammonium molybdate, antimony potassium tartarate and ascorbic acid. Make up the volume, shake it and measure the intensity of blue color at 660 nm on Spectronic 20 or using red filter on colorimeter. Calculations Available P kg=ha ¼ R Total volume of extract 1 2:24 106 106 Volume of aliquot taken weight of soil where R is the concentration in parts per million (ppm) from standard curve. Determination of available potassium in soil (ammonium acetate extractable) by flame photometer (Pansu and Gautheyrou 2006) Available potassium in soil is extracted using ammonium acetate solution. Ammonium acetate when mixed in soil reacts with potassium compounds in the soil to form potash. The potassium from potash is then detected using flame photometry. Extraction and estimation 1. Add 25 ml extracting solution to 5 g soil and shake it for 5 min. Filter the contents and collect the filtrate. 2. Atomize the above extract on flame photometer and record the readings. Calculations: Available K ¼ R Volume of extracted soil solution 2:24 106 106 Soil weight where R is the concentration in ppm from the standard curve. 4 R. P. POTDAR ET AL. Soil available nitrogen detection by alkaline permanganate method (Hussain and Malik 1985) Ammonia is removed from soil by oxidization process. For the oxidation reaction to take place, potassium permanganate (KMnO4) is mixed with sodium hydroxide (NaOH). Removed ammonia is collected in boric acid to form ammonium borate. For quantitative identification of nitrogen, ammonium borate is titrated with sulfuric acid (H2SO4). The volume of acid required for titration is substituted in the formula to get result. Extraction and estimation 1. 2. 3. 4. Put 20 ml distilled water and 20 g soil in a 1000 ml distillation flask. Add 100 ml of potassium permanganate (0.32%) and 100 ml of sodium hydroxide solution (2.5%) to the flask. Stopper the flask immediately and start distillation. The tip of the condenser should dip in the 20 ml of boric acid solution in the beaker. On heating, ammonia will be liberated which will be absorbed in the boric acid. The original wine red/pink red color turns to green with the absorption of ammonia. Collect nearly 100 l of the distillate in about 30 min and add to 1 l of 0.02 N H2SO4 to get the original pink red wine color and record the burette reading. Observations and calculations H2SO4 required for titrating sample¼X ml H2SO4 required for blank sample¼Y ml Available nitrogen Kg=ha ¼ ðX–YÞ Normality of H2 SO4 0:014 2:24 106 1 Weight of the soil As can be seen above, the laboratory testing depends heavily on chemical extraction, with the selection of extractant (a chemical solution) based on soil properties like pH and soil chemistry. Following the chemical extraction, the concentration of nutrients is measured using a setup procedure. Lastly, the concentration of the extracted nutrients is converted into the standard unit of kg/ha so that it can be correlated with soil fertilizer needs. Thus, laboratory testing is an ordeal which is not so used by farmers. Most of the small-scale farmers in India do not usually check the quality and health of their soils. Laboratory testing services are scarce and irregular, also the test results take very long (many months) to become available. For the reasons stated above, it is better to have an alternate, reliable soil testing approach with added benefits like portability so that it can be used for in situ soil testing. This approach can be used to supplement the laboratory chemistry analysis. Hence, the paper henceforth focuses on rapid testing methods that have the advantage of portability, ease of testing and quicker results as compared to conventional laboratory testing. Soil NPK estimation by optical measurements The optical soil measurement methods in this paper can be classified into six types. Visible–infrared (Vis–IR) spectroscopy, inductively coupled plasma spectroscopy, fluorescence spectroscopy; and colorimeters are used for measuring soil nutrients. In IR spectroscopy, infrared radiation interacts with soil matter, and the transmittance/absorption of IR radiation coming out JOURNAL OF PLANT NUTRITION 5 from the sample is analyzed to get nutrient values. Reflectance spectroscopy detects the level of energy reflected by soil particles and relates it to the concentration of soil elements. The colorimetric technique correlates the color of the soil extract to reference charts and measures the level of soil nutrients. In fluorescence spectroscopy, Ultraviolet (UV)/visible radiation absorbed by the soil sample results in fluorescence emission, which is recorded to measure nutrient values. Chappelle et al. (1984) explored the use of laser-induced fluorescence spectroscopy for nutrient deficiencies of plants. Plants with Phosphorus and Nitrogen deficiencies had a decrease in the intensity in their fluorescence spectrum at 690 and 740 nm. In Inductively coupled plasma optical emission spectroscopy (ICP-OES), electromagnetic radiation at wavelengths characteristic of a particular element is emitted. Yang et al. (2018) used ICP-OES for determining Phosphorus amount in the soil. The subsequent sections provide an exhaustive review of the most frequently used and widely researched optical techniques. Vis–IR spectroscopy Vis–IR spectroscopy is a physical nondestructive, rapid, reproducible and low-cost technique that characterizes materials according to the energy absorbed by the material in the wavelength range 700 nm 1 nm. Each soil nutrient has its own and unique spectral feature which helps in its quantification and identification. It is a type of nonliquid nutrient testing method which makes it a cutting-edge technique for soil analysis. The procedure is very convenient and truly portable in the sense that, it requires almost no sample preparation. To extract quantitative information out of the IR spectra it is required to use calibration curve obtained from multivariate techniques. The calibration curve is used to find unknown concentration of a solution by using the graph of intensity of spectrum versus known concentration. Thus, over the other methods, spectroscopic methods for soil analysis are advantageous and easy. The only limitation of the method is the soil mapping and generation of appropriate database. The application of IR spectroscopy to soil is being studied from 1960 and is used extensively for determining soil Carbon and Nitrogen content. Vis–IR spectroscopy is now being studied for its use in determining soil Phosphorus and Potassium content. Table 2 enlists prominent and potential literature on NPK detection based on Vis–IR spectroscopy. Masrie et al. (2018) presented a device in Institute of Electrical and Electronics Engineers (IEEE) 2018 conference. It was an Arduino UNO and light emitting diode (LED) based portable device for measurement of soil NPK. The LEDs used had wavelengths of 470 nm (for N), 660 nm (for K) and 950 nm (for P) and the absorption response for N was found to be 32 V, for P 4.6 V and for K 19.8 V, respectively. The device uses intensity of absorbed radiation and rate of light absorption values to quantify the nutrients in the soil. This work has laid the foundation for developing portable optical NPK detection sensors based on Vis–IR spectroscopy. Xiao and He (2019) in their 2019 paper reported that the accuracy of detecting soil nitrogen by near-infrared (NIR) spectroscopic methods is largely affected by soil particle size, soil type, color and other physiochemical properties. They found that smaller the particle size, stronger is the intensity of reflection in the soil NIR spectra. Thus, they showed that there are multiple environmental and other factors affecting the detection of nitrogen which have to be minimized in order to better the detection results. Pretreatment of soils was found to be extremely helpful in removing the dependency of soil nitrogen detection on the unwanted environmental factors. On a similar note Peng et al. (2019) studied different pretreatment methods for analytical grade detection of soil nutrients through NIR spectroscopy using the AvaField spectrometer. They discovered that genetic algorithm – back propagation neural network optimization results in accurate detection of soil total nitrogen, total phosphorus and total potassium. This nutrient determination was verified through semi-micro Kjeldahl method, molybdenum blue UV spectrophotometer method and flame photometer method for NPK respectively. Also, they found that partial least-squares Couteaux, Berg, and Rovira (2003) Dinakaran et al. (2016) Ehsani et al. (1999) Feng (2011) Fystro (2002) Jahn et al. (2006) Lee et al. (2003) Linker et al. (2004) Mouazen, Baerdemaeker, and Ramon (2006) Mouazen et al. (2010) Nie et al. (2017) Qiao and Zheng (2011) Shi et al. (2015) Udelhoven, Emmerling, and Jarmer (2003) Wetterlind, Stenberg, and Soderstrom (2010) Zornoza et al. (2008) 3. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 4. 5. Citation Bogrekci and Lee (2007) Chacon Iznaga et al. (2014) Sr. no. 1. 2. 0.60 P 0.68 K 0.80 N 0.79 In situ Vis–NIR spectroscopy 0.85 0.72–N 0.84–P 0.68–K 0.95 0.9865, 0.99, 0.99 0.11 5.8 mg/g P 5.3 mg/g K 0.02% N Potassium Total N, P and K Total potassium Total nitrogen 0.0168 0.47 g/kg Nitrogen, phosphorus and potassium Nitrogen Phosphorus and potassium Phosphorus, potassium Nitrate Phosphorus and potassium Soil nitrate ion Total nitrogen Total nitrogen Nitrogen Soil NO3––N Total nitrogen Element detected Phosphorus Phosphorus and K2O 1 %–4 % 0.0033, 0.02860, 0.00275 1.353–1.667 P 0.202–0.224 K 1.77–1.94 93 ppm – 0.50–0.69 P 0.33–0.43 K 0.68–0.74 18.60 mg/kg 8.76 mg/kg 0 to 140 mg/L 0.36 g/kg 0.0684 0.01 6–38 mg/kg <20% – RSMEP/RMSEC 0.72–P 0.24–K 0.93 0.87 0.9724 0.85 >0.9 0.955 R2 0.78–0.92 0.16–0.63 for K 0.68–0.83 for P In situ Vis–NIR spectroscopy with PLS. ASD FieldSpec-II spectrometer Vis–NIR spectroscopy and relating total N to SOM Vis–NIR spectroscopy with BPNN-LVs IR spectroscopy 900 to 1700 nm. Based on soil pretreatment and PLS, UVE and CARS NIR spectroscopy with principal component analysis and LS-SVM MEMS based NIR absorption spectroscopy Relating chemical properties of soil to spectral characteristic 400 to 2498 nm ATR FTIR mid infrared range with PLSR model In situ Vis–NIR ATR-FTIR mid infrared NIR spectroscopy with MPLS NIR absorbance 1800 to 2300 nm with Fast Fourier Transform Vis short wavelength near infrared spectroscopy Vis–NIR NIR spectroscopy MPLSR Details of spectroscopic technique used UV–Vis–NIR spectroscopy Vis/NIR spectroscopy with LWR, SVM Table 2. Summary of Vis–IR spectroscopic methods for NPK measurement. Successful detection of N but poor calibration results for P and K. Data calibration is taken for only 25 samples. Distinguishes between high and low levels Requires soil preprocessing and relatively large prediction errors Only nitrogen detection. Not portable only the source is MEMS based Only potassium measurement Requires intensive soil pretreatment Medium correlation for K and poor results for P Requires more accuracy Requires spectrometer Requires bulky spectrophotometer Cannot measure low concentrations Requires spectrophotometer Only nitrogen detection Soil moisture affects results Requires site specific calibration Overlap of some wavelengths between phosphorus and K2O Requires spectrophotometer Limitations for in situ measurement 6 R. P. POTDAR ET AL. JOURNAL OF PLANT NUTRITION 7 regression (PLSR) the most effective multivariate analysis technique employed most frequently till now is not an effective technique for nutrient detection. Xiao et al. (2018) showed that instead of the entire spectrum using the subset of required and material sensitive wavelengths enhances the nitrogen detection by a large extent. On a similar note Kawamura et al. (2019) worked on detection of nutrients using wavebands. They used genetic algorithm for selecting wavebands. They worked on detecting soil oxalate extractable Phosphorus. Now, phosphorus is not directly detectable so it is correlated with Aluminum (Al) and Iron (Fe) elements in soil for detection purpose. Out of the complete wavelength range 400 2400 nm only 4.7% was found to be useful in the prediction. Selected waveband range is 400–600 nm. Also, they found that PLS regression combined with waveband selection improved detection of soil oxalate extractable Phosphorus. Jin et al. (2020) studied 29 pretreatment methods and 8 regression algorithms for removing the dependency of spectroscopic determination of soil potassium on environmental factors. Combination of three methods namely: Savitzky–Golay, standard normal variate and dislodge tendency was found to work the best. Laboratory verification of potassium detection was done using flame photometer. Wavelength range used was 350–1700 nm. Yet there was some dependence on environmental factors which doesn’t make the method very reliable. Yao et al. (2019) analyzed NIR spectrum of different soil types. They found that the absorbance values differed due to soil organic matter and color of the soil. They worked on developing a model to get rid of these dependencies using radial basis neural network and Monte-Carlo noninformation variable elimination and continuous projection algorithm. Reflectance spectroscopy Reflectance spectra are of three types: internal reflectance, diffuse reflectance and specular reflectance. Most of the soil nutrient detection is done using diffuse reflectance spectroscopy. Table 3 shows briefly reviews some prominent reflectance-based sensing techniques: Based on the near-infrared reflection spectroscopy, Du et al. (2019) published a set of detailed instructions and research on diffuse reflectance technique for soil nitrogen detection. They developed a portable nitrogen detector. They used a small, compact Fourier transform infrared (FTIR) coupled spectroscope with a supporting software for data acquisition and spectral analysis. They identified wavelengths for soil nitrogen as 1500 1850 and 2000 2400 nm for nitrogen containing groups. Their reported work has 0.934 coefficient of determination and root mean square error (RMSE) 1.923 indicating good quality nitrogen determination by diffuse reflectance spectroscopy. Hu et al. (2016) studied the effect of using a small region of wavelength 1100–2450 nm for sensing soil phosphorus and potassium and found that narrower sensing range is beneficial in making sensors. They also discovered that the inclusion of direct orthogonal signal correction pretreatment method reduces the error by 25 to 39%. Mukherjee and Laskar (2019) developed a Vis–NIR diffuse reflectance spectroscopy-based sensor for measurement of NPK in soil extracts. Absorbance for nitrogen was observed at 850, 620 630 nm for Phosphorus and 460 470 nm for potassium. Raman spectroscopy Raman spectroscopy is a rapid soil nutrient testing tool. It uses a strong beam of visible or ultraviolet light to illuminate the sample and collect the scattered Raman spectra. Based on vibrations and rotations of radiation excited molecules, Raman spectra signature can provide structural information which serves as a key for sample identification. Surface enhanced Raman spectroscopy (SERS) based water-soluble nitrogen detection was reported by Dong et al. (2018). The characteristic peaks of nitrogen were found to be 1028, 1370, 1436 and 1636 cm1 using SERS based on Opto trace Raman (OTR) 202. The calibration 5. 6. 3. 4. 2. 1. Sr. no. Bogrekci and Lee (2005) Dalal and Henry (1986) Ehsani et al. (1999) Guerrero et al. (2010) Shi et al. (2015) Vagen, Shepherd, and Walsh (2006) Citation Diffuse reflectance spectroscopy Vis–NIR reflectance NIR reflectance spectroscopy 1100 to 2500 nm NIR reflectance with PLSR NIR reflectance spectroscopy with PLSR UV/Vis/NIR reflectance spectroscopy Details of technique used 0.9184 0.96 0.953 0.88–0.95 Total nitrogen Soil mineral nitrogen Total nitrogen nitrogen Total nitrogen 6.5 ppm 0.2–0.5 g/kg – 0.64 g/kg 0.014% > 0.92 Element detected Phosphorus RSMEP/RMSEC 0.61–0.93 13.5–850.3 mg/kg R2 Table 3. Summary of reflectance spectroscopy methods for NPK measurement. Limitations for in situ measurement Portable Requires site specific soil spectral libraries At lower concentrations the prediction is poor. Results differ for different colors of soil. Requires site specific calibration Regional – scale study Requires spectrophotometer 8 R. P. POTDAR ET AL. JOURNAL OF PLANT NUTRITION 9 equation developed is y ¼ 93.491x þ 1771.5 pointing out the capability of using SERS for watersoluble nitrogen detection. Vogel et al. (2017) reported using deep ultraviolet Raman microspectroscopy for characterization of phosphorus compounds. Lee and Bogrekci (2007) invented and patented a portable Raman sensor for soil nutrient detection. The device comprises of BTC111E miniature thermoelectric (TE) cooled fiber coupled charge coupled device (CCD) spectrometer, sample compartment and power supply. They used Raman spectrum range of 340 3640 cm1 in their invention. The sensor is capable of remote detection and quantification of soil nutrients like phosphorus, nitrogen and potassium. Larar et al. (2012) studied soil phosphorus concentration using Raman spectroscopy. They extracted the useful signal from the original Raman spectrum for each sample by using bior 4.4 wavelet packet on a platform of Matlab R2011. Spectrum was recorded in the range of 239 4045 cm1. PLS models were used to forecast the phosphorus concentration. It was found that environmental factors affect Raman signature and hence results. Also, the spectrum of the cuvette and base sand was found to interfere a lot with the phosphate Raman signature. Reported R2 is 0.937 and root mean square error of prediction (RMSEP) is 244.57 indicating effectiveness of Raman spectroscopy for phosphorus detection. Colorimetric Soil testing kits perform a quick, on-the-spot, and approximate measurement of nutrients present in the soil (McCoy and Donohue 1979). These kits use the principle of colorimetric technique for analyzing the soil nutrients. The colorimetric method compares the color change of the solution with calibrated reference color charts. The shade of the color on the color chart indicates a range of concentration. By relating color of the solution to concentration of nutrients, colorimetric method measures the fertility level of nutrients (NPK) in the soil. The universal method followed in all the soil testing kits is: mixing the soil sample with extracting solutions and filtering through a filter paper to get an extracted solution containing nutrients. Adding coloring reagents to get a colored solution. Evaluating the colored solution using the colorimetric technique described above to measure the concentration of nutrients (NPK) present in the soil sample. The color change associated with the soil sample indicates the range of nutrient concentration in the solution, i.e., low, medium, or high nutrients in the soil. These kits are semi-quantitative, economical, simple, and convenient to use, which makes them famous and readily available in the market. Results obtained from soil testing kit are deduced by visual color observations making these kits somewhat unreliable. Also, we can get only approximate values and not actual concentration from these kits. To remove the dependency of the soil testing kit’s color interpretation by naked eye and to improve its accuracy, a combination of sensors, microcontrollers, and optical fiber can be used to make an independent, portable, and accurate soil sensor. The color sensing element used in the colorimeter is photocells converts the light intensity into current and records the output on a galvanometer. To further automate the process, microcontrollers can be used to compare these measured signals with calibrated values and display the result on a liquid crystal display (LCD) screen. Given below is the detailed review of all such sophisticated colorimetric approaches for soil nutrient sensing: Masrie et al. (2017) presented a conference paper entitled detection of NPK soil nutrients using optical transducer. The optical transducer was made up of three LEDs as a light source and a photodiode as a light detector. The nutrient absorbs the light from the LED, and the photodiode converts the remaining light to current. An Arduino microcontroller then processed the current values thus converting the light output from the optical fiber into voltage which is then displayed as a digital reading on LCD screen. Test results of various soil samples showed that the optical sensor developed by Masrie et al. could evaluate the amounts of NPK soil content as high, medium, and low levels. Agarwal et al. (2018) built a NPK measurement sensor based on 10 R. P. POTDAR ET AL. colorimetry, Arduino Uno and Naive Bayes classification. The system is made up of components like color sensor, microcontroller Arduino Uno, and soil testing kit. Depending upon the color intensity of solution, system can sense the amount of soil Nitrogen, Phosphorus, and Potassium in medium, low and high levels. The results are verified using Naive Bayes classifier. Liu et al. (2016) in their paper reported a miniature microfluidic channel and MEMS technology based colorimetric sensor for sensing NPK elements. It is a MEMS-based low-cost, high-precision, portable sensor capable of measuring ppm level concentration of soil nutrients. The portable sensor is made up of components like micro-fluidic channel, light sources, processing circuit, and a displayer. Photocells are used to convert the light intensity into electrical signals like current, voltage, etc. These signals are lastly filtered to remove noise and amplified. Further, the microcontroller unit (MCU) deals with these measured signals and displays the results on the mini-LED displayer. The detection limit for measuring nitrogen was found to be 83.6 ppm, for phosphorus 143 ppm, and potassium 40.9 ppm using this sensor. Monterio-Silva et al. (2019) built a compact, modular direct UV–Vis spectroscopy-based sensing system coupled with optical fiber bundle. It uses deuterium light source-based spectrometer with transmission optical fibers and a reflection probe for insertion of samples. Aqueous solution of NPK containing fertilizers could be investigated with the said device. Absorbance wavelength for nitrate and nitrite ion was found to be 302 and 352 nm. But the system was plagued by interference of competing ions in the spectra which could not be resolved using linear or logarithmic regression models. Artificial intelligence algorithm was found to solve the problem of interference in spectrum. Thus, the device could be used real time by covariance modes to correctly account for interferences in the prediction model. Yokota, Okada, and Yamaguchi (2007) developed an LED optical sensor for determination of soil nutrients. The compact optical sensor consists of three LEDs and an input/output (I/O) data processing peripheral interface controller (PIC) microcontroller and can detect ammonianitrogen, nitrate-nitrogen and phosphorus in aqueous solution. The soil filtrated solution was color-developed using the soil analyzer – Dr. soil and further processed using the PIC based sensor. Detection limit achieved by the sensor is around 1 mg/100 g. Optical imaging Chen et al. (2019) reported a unique technique for determining the nutrient status in plants. According to them analyzing images of plant leaves could help predict potassium deficiency in plants. Matrix laboratory (MATLAB) software and support-vector machines (SVM) calibration model were used together to analyze leaf image and derive potassium level from the given information. Li, Jia, and Le (2019) used 900 1700 nm wavelength for detecting total soil nitrogen content using a hyperspectral imaging system. They developed a fully automatic and currently lab-based device. It uses a combination of hyperspectral imaging technology and chemometrics. Uniform variable elimination – extreme learning machine (UVE-ELM) prediction model was used. Total nitrogen content was verified using the Kjeldahl method. Aitkenhead et al. (2017) developed PHYLIS: Portable Hyperspectral Low-Cost Imaging System. It uses Microsoft visual studio 2010 software and is capable of sensing NPK. But there is a need to develop appropriate libraries for the device to be used in the field. Conclusion The purpose of this review was to study the research done in the field of optical sensing of soil nutrients–NPK. It is clear from the research reviewed that substantial technological advances have been made in the field of soil nutrient testing till this date. As seen in the paper; Vis–IR spectroscopy can detect nitrogen, phosphorus and potassium with R2 0.99, 0.78 and 0.80, respectively. The concentration of nutrients detected is as low as JOURNAL OF PLANT NUTRITION 11 1 ppm. But it showed poor results for prediction of Potassium and Phosphorus since Phosphorus and Potassium could not be directly absorbed in the Vis–NIR region. They have to be correlated with some soil properties or other elements for detection purpose. Thus, it has great potential for sensing nitrogen content in the soil and it is a very reliable, sensitive and accurate technique. However, it was found that the detection of soil nutrients depends on variations in soil and environmental factors resulting in poor detection accuracy. According to review of papers since 2017, this problem can be solved by applying pretreatment methods and different calibration methods. The only concern with spectroscopic methods is that typical spectrometers are bulky and expensive, and requirement of site-specific calibration. Overall a lot of progress has happened in the spectroscopy field which makes it an excellent choice for easy nutrient detection. There also has been a lot of research conducted on the use of reflectance spectroscopy and Raman spectroscopy for the determination of the nutrients. Diffuse reflectance spectroscopy can detect nitrogen with R2 0.99 and phosphorus with R2 in the range 0.61–0.93. Also, it was found that instead of using the entire range of spectrum, using only a subset of wavelengths could reduce the detection errors and make the method better. The problem of detecting phosphorus is solved by using Raman spectroscopy. It can detect phosphorus with 0.937 R2 in the wavenumber range 200 4000 cm1 Raman spectroscopy thus has excellent phosphorus detection capacity so much so that it was used as an investigation tool to determine various chemical forms of phosphorus in soil. From the review it appears that colorimetric methods can be used to develop a portable, costeffective optical sensor for soil macronutrient detection. In general, the colorimetric technique doesn’t need expensive equipment and perfect measurement conditions or good database or sophisticated analysis techniques. Most of the results reported are in approximate levels instead of precise values. But the novel chip-level colorimeter designed by Liu et al. (2016) is capable of detecting ppm concentration of soil nutrients. Thus, further research on colorimeter-based soil nutrient detection can be carried out for developing a cost-effective portable sensor. Research findings suggest that the solution-based soil extractant can be replaced by ion-selective membranes to make the colorimeter-based sensor more compact and convenient. The latest trend in the field of nutrient testing is the use of imaging techniques. Currently this method is at an underdeveloped stage and extensive studies will have to be carried out before the imaging techniques become a prominent name in the nutrient sensing field. Although much research has happened in the optical sensing field, a cost-effective portable soil NPK sensor still does not exist in the Indian market. Thus, to this date, a promising, accurate, reliable, capable sensor based on optical methods does not exist in the market. It is clear that there is an ardent need for developing a sensor. From the review conducted it is found that MEMS based colorimetry and spectroscopy are the best approaches available in making a sensor. The colorimetry might be the best available economic approach for doing so because it is cheap and makes a simple device where site-specific calibration is not required. Whereas, spectroscopy offers the most accurate and reliable sensing, but this approach tends to be expensive because of the portable spectrometers required. 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