Neha Sharma

X-ray fluorescence (XRF) is a useful technique in agricultural science to determine the elemental constituents of plant materials. It allows for quick analysis, high spatial resolution, measurement of multiple elements within a single scan, and requires minimal sample preparation while being nondestructive. In this study, we used wavelength dispersive XRF (WDXRF) to study agricultural diseases. We performed a spectroscopic investigation in agricultural samples to measure the elemental changes caused by infestation. A broad range of major, trace, and heavy elements were detected and quantified in healthy and infested crop samples, and we observed significant changes in the elemental concentrations. We also used laser-induced breakdown spectroscopy (LIBS) in combination with XRF spectrometry. Further improvements will provide exciting perspectives for the application of XRF in the area of plant and agricultural science.

It has been observed that approximately 14 essential elements are needed for the proper growth and development of plants, along with water, hydrogen, oxygen, and carbon dioxide. These nutrient elements are further categorized as macronutrients and micronutrients. Macronutrients, such as calcium, magnesium, nitrogen, potassium, phosphorus, and sulfur, are needed by plants in large amounts (>1000 mg per kg dry weight), whereas micronutrients, including boron, chlorine, copper, iron, manganese, molybdenum, nickel, and zinc, are required by plants in small amounts (<100 mg per kg dry weight) (2). Even though plants require only small amounts of micronutrients, these nutrients are equally important for the proper growth and development of plants.

Trace element detection is important in plant science. The concentration of trace mineral elements in plants, as well as in the soil, can change, and this variability can lead to deficiencies or excess accumulation of these mineral metals (3). Knowledge of the concentrations of trace elements in plants is important for diagnosis of various agricultural crop diseases. Crop disease development depends on three main factors: a susceptible host plant; favorable environmental conditions; and the pathogen involved, sometimes displayed as a “disease triangle” (Figure 1). Environmental conditions, in particular, play a major role in the occurrence and the growth and development of plant diseases; many diseases will not emerge if environmental conditions, such as temperature, relative humidity, soil moisture, soil pH, rain, and water content, are not favorable.

FIGURE 1: Illustration of the plant disease triangle.

Atomic spectroscopy methods are the first choice for assessing the mineral composition of agricultural crop samples. For most atomic spectroscopic techniques, samples preparation is required, such as sample dissolution using a mixture of strong acids (generally nitric and sulfuric) and oxidants (commonly hydrogen peroxide). In many cases, it is easy to dissolve the samples in the solution. Because of the presence of silicon in plant samples, sample preparation usually requires a mechanisms that ensure complete decomposition, to ensure efficient dissolution of metallic elements into solution. Hydrofluoric acid addition, along with evaporation for achieving dryness, is needed to complete the proper dissolution of the analyte; otherwise, the presence of silicon may result in poor recoveries of some elements due to the binding of analytes with the insoluble residues (4).

Proposed methods found in the literature, from large numbers of acid mixtures used in wet washing procedures, reveal a lack of consensus for achieving the complete dissolution of plant specimens. The choice of decomposition method for a given plant sample material must be evaluated carefully, considering each of the matrices and analytes under study. In reviewing these challenges of sample digestion, analytical methods that do not require matrix destruction can be advantageous for such studies.

Nearly all X-ray fluorescence (XRF) techniques have desirable features for the analysis of plant samples. These features include the capability to carry out direct analysis of solid samples, multielemental analysis, the capability to carry out the qualitative analysis along with quantitative determination, a broad dynamic range, high throughput, and low maintenance and analysis cost. The major drawback of XRF is its limited sensitivity for elements like cadmium and lead. The poor precision and accuracy of XRF compared to other atomic absorption spectroscopic techniques is also a limitation. However, some recent improvements, such as the advancement of digital processing-based spectrometers, along with better detector designs in XRF instrumentation, have increased instrumental sensitivity and improved both the precision and productivity of XRF. These improvements have increased interest in adopting XRF spectroscopy in environmental science for analyzing various plant materials. The use of different quantification strategies employing distinct configurations of XRF instrumentation for the analysis of various vegetation matrices has been discussed.

Identification of Nematode Species in Okra and Papaya

We have collected healthy and nematode-infested okra root samples, which are shown in Figures 2a and 2b, from field sites of Uttar Pradesh, India. We have also collected nematode-infested and healthy papaya root samples, as depicted in Figure 2c. After collection, the samples were washed, and after drying the samples, they were milled into a fine powder for spectroscopic studies.

FIGURE 2: (a–d) Photographs of nematode-infected okra and papaya roots, and rice grains infected with false smut disease.

Cobb’s sieving and decanting methods were used to draw out the body parts of male, female, and juvenile nematodes to identify the species of nematodes in the diseased okra and papaya plant root samples. We adopted the procedure for species identification described by Goodey (1963) (5), and the species was identified on the basis of the characteristics observed in the perineal regions of the female nematodes by employing the method provided by Eisenback and others (1985) (6). Our examinations revealed that the species of root-knot nematode pathogens in the diseased okra and papaya roots was Meloidogyne incognita. Details regarding the sample preparation and identification of nematode species have been described by Sharma and others (7,8).

Collection and Isolation of Rice Samples (Healthy and Infected with False Smut)

A survey was conducted in rice fields suspected of false smut infestation in Uttar Pradesh, India, during the Kharib season of 2018–2020. Healthy rice grains and rice grains infested with false smut disease were collected (Figure 2d). The rice grain samples were carefully separated along with smutty balls from rice spikelets and milled into a fine powder form. The upper surface of smutty balls was sterilized by dipping them in a solution of 1% sodium hypochlorite for approximately 1 min and then cleaning with 70% ethanol solution for about 1 min. More details regarding the isolation of false smut disease pathogens from rice grains has been described by Sharma and others (9).

Study of Root-Knot Nematode–Infected Okra Plant Roots

In the present study, we employed wavelength dispersive X-ray fluorescence (WDXRF) spectroscopy to examine in healthy and nematode-diseased okra root samples. We detected many elements, such as aluminum, calcium, copper, chromium, chlorine, iron, manganese, magnesium, nickel, phosphorus, potassium, rubidium, sodium, silicon, strontium, sulfur, titanium, zinc, and zirconium. We noticed significant differences in the elemental composition of healthy and diseased samples. Figure 3 shows WDXRF spectra of healthy and nematode-infested okra roots in the energy range of 5–10 keV, which shows the relative abundance of the elements chromium, manganese, iron, nickel, zinc, and copper.

FIGURE 3: WDXRF spectra of healthy and nematode-infested okra roots in the energy range of 5–10 keV, which shows the relative abundance of the elements chromium, manganese, iron, nickel, zinc, and copper. Data were taken from reference (7).

Several mineral elements—particularly calcium, chlorine, magnesium, potassium, sodium, and sulfur—were found to have higher concentrations in nematode-infested okra plant samples compared to healthy root samples. Other elements, including copper, phosphorus, manganese, silicon, and zinc, were found to be in lower concentrations in nematode-infected root samples as compared to healthy okra root samples. Some toxic elements, such as aluminum and chromium, were observed in lower concentrations in the infested root samples. No significant differences in the concentration of elements like bromine, rubidium, nickel, and zirconium were observed. Some traces of silver were found only in nematode-infected okra root samples, whereas traces of palladium were found only in nematode-infested root samples.

Our experimental findings were supported by the literature and other published reports. The observation of lower concentrations of iron, phosphorus, and zinc in nematode-infected okra root samples aligns with results reported by Farahat and others (10). Lower concentrations of iron, phosphorus, and zinc also have been observed in the diseased tissues of nematode-infected citrus, eggplant, jasmine, cowpea, and papaya plants (10). Sharma and others have also witnessed the decreasing concentration of phosphorus in nematode-infested okra root samples as compared to root samples from healthy okra plants (11). We also observed a higher concentration of sodium and a lower concentration of phosphorus in the nematode-infested okra root samples, which also aligns with results reported by Sharma and others (11).

Some nonessential elements, such as silver and palladium, were detected only in infected root samples, which indicates that their presence may be associated with the formation and development of nematodic pathogens on okra roots. Elements like strontium and titanium were also observed in increased concentrations in nematode-infested okra root samples. Heavy elements such as aluminum, chromium, and titanium were also observed in higher concentrations in nematode-diseased root samples of okra plants, and appears to be related to the formation of galls on the surface of roots with the invasion of pathogens. The higher concentration of aluminum can be considered a threat to agricultural crops because aluminum obstructs root growth and disturbs nutritional balance, encouraging the induction of oxidative stress. This stress leads to peroxidation reactions in the cytoplasmic membrane and ultimately leads to cell death (12). The physiological and biochemical functions of chromium in plants is not particularly clear (13). It has been observed that excessive levels of chromium can encourage several detrimental biochemical, morphological, and physiological effects on plant health (13,14). Nevertheless, the overall toxicity of chromium in plants is well documented (13). All these elemental changes are capable of posing serious and toxic effects in plants such as hindering growth mechanisms, disturbing photosynthesis, translocating mineral nutrients, disrupting the water intake capacity, and ultimately declining the overall quality of the okra plant.

Study of Root-Knot Nematode–Infected Papaya Plant Roots

We have also studied root-knot nematode-infected papaya plant root samples employing WDXRF to obtain the elemental variations between healthy and diseased papaya root samples. Using WDXRF, numerous elements, such as aluminum, chlorine, copper, chromium, calcium, magnesium, manganese, iron, potassium, sodium, phosphorus, nickel, silicon, rubidium, sulfur, and zinc were detected in root samples of healthy and diseased papaya plants (8). Figures 4a and 4b show the overlapping WDXRF spectra of healthy and diseased papaya root samples within different energy ranges, indicating the presence of elements such as aluminum, calcium, and potassium. The WDXRF spectra of papaya root samples showed that concentration of mineral elements changed with nematode infestation. It has been documented that the induction of antioxidants, creation of mechanical obstructions, and triggering of defense systems in plant bodies are all associated with good accessibility of mineral nutrients in plants (15). It was observed that the concentrations of one major nutrient, calcium, increased from 2.4 to 3.14% from healthy to diseased root samples, whereas another major element, magnesium, was found to increase from 0.39 in healthy root samples to 0.46% in diseased samples.

FIGURE 4: (a,b) WDXRF spectra of healthy (black) and nematode (green) infected papaya root samples. Data were taken from reference (8).

The concentration of silicon was found to be elevated from 0.23 to 0.53% from uninfected to nematode-infected papaya root samples. Sharma and others also observed the same elevated concentration patterns of calcium, magnesium, and silicon while performing elemental and molecular studies of nematode-diseased okra root samples (7). It has been observed that the elements calcium, magnesium, and silicon are the major nutrients that are beneficial in maintaining the outer coating of cell membranes and thereby helping plant cells defend against pathogen invasions. The increasing concentrations of calcium, magnesium, and silicon seen in our findings can be correlated with the induction and activation of defense systems in response to the attack of pathogens. In addition to these elements, we also found increasing concentrations of iron, aluminum, and titanium in papaya plants with the arrival of nematodic infection. The particular role of aluminum and chromium in the physiological and biochemical behavior of plants has not been determined yet.

Macroelements, such as potassium and phosphorus, are essential and play various roles, like activating enzymatic systems, inducing protein synthesis, managing photosynthesis processes, moving stomata, maintaining balance between cations and anions, and transferring energy (8). It has been observed from WDXRF analysis of healthy and diseased papaya root samples that the concentrations of these two macroelements decreased with the arrival of nematodes and fungal infections on papaya plants. It is well reported that potassium and phosphorus encourage the thickening of cell walls and thereby induce barriers that hinder the further movement of the attacking pathogens inside the plant body (8).

Decreasing concentrations of some other elements, such as copper, manganese, sodium, and zinc, were observed in the papaya root samples with the arrival of a nematode attack. Similar results were also reported by Sharma and others. Traces of the elements zirconium and molybdenum were found in the diseased papaya root samples only, also similar to observations made by Sharma and others (7).

The relative concentrations of the elements calcium, magnesium, silicon, potassium, sodium, and iron, are shown in Figure 5. Changes in the concentrations of several of these elements can lead to serious consequences for the health and viability of papaya plants.

FIGURE 5: Relative concentrations of elements in papaya root samples and comparison with LIBS data. Data were taken from reference (8). (a) WDXRF data, and the (b) LIBS data.

We have also validated our experimental findings using laser-induced breakdown spectroscopy (LIBS), as shown in Figure 5. For a LIBS method that is free from self-absorption, it has been observed that the intensity of the elemental characteristic line is more closely related to the concentrations of the sample analytes (8). To confirm that there is no self-absorption in the LIBS method, we have verified all the conditions, such as the existence of stoichiometric ablation, local thermal equilibrium, and optical thickness of the plasma. Furthermore, we have calculated the peak area intensity ratios of certain elements like calcium (393.36 nm), potassium (766.48 nm), magnesium (279.55 nm), sodium (588.99 nm), iron (238.40 nm), and silicon (288.15 nm) from the LIBS results of papaya plant samples. These calculated values were further taken as the concentrations of these elements and directly compared with the concentration values of the WDXRF spectra of papaya plants. Given that LIBS and WDXRF follow different criteria, to compare the results of the techniques, we focused only on the trends we observed for each element in the papaya plant samples, which are clearly indicated in Figure 5.

Figures 5a and 5b show bar graphs of the results obtained using LIBS and WDXRF and reveals the patterns of the concentrations of major elements such as calcium, sodium, iron, magnesium, potassium, and silicon in the diseased and healthy papaya root samples. Because the same trends of the element concentrations were observed by both techniques for the analysis of papaya plant samples, we believe that both techniques can be considered proficient methods for assessing the composition of mineral elements in healthy and diseased plant samples, both qualitatively and quantitatively.

Study of Rice Crop Infected by False Smut Disease

WDXRF spectroscopy was also employed for the spectroscopic investigation of rice grains from rice crops infected with false smut disease. The WDXRF spectra of healthy and diseased rice grains were recorded within different energy ranges. Changes in the elemental composition of the rice grains associated with black and yellow smutty fungal spores on the upper and lower surface of the rice spikelets, were investigated. For the sake of simplicity, we have encoded our samples R1, R2, and R3 on the basis of severity of false smut disease, where R1 stands for uninfected rice grain samples, R2 stands for rice grain samples with low levels of infection, and R3 for highly infested rice grain samples.

Using WDXRF spectroscopy, we have quantified the presence of numerous essential and non-essential elements in rice samples, including calcium, aluminum, copper, iron, chlorine, magnesium, manganese, nickel, phosphorus, chromium, potassium, rubidium, silicon, sulfur, and zinc. Figures 6a and 6b show the overlapping WDXRF spectra for the different rice grain samples, indicating the relative presence of phosphorus, silicon, sulfur, chromium, manganese, iron, nickel, copper, and zinc in the various rice grain samples (R1, R2, and R3). We also verified our results using LIBS. The detailed results of similar studies have been discussed by Sharma and others (9).

FIGURE 6: (a,b) WDXRF spectra for elements in healthy rice grains and in rice grains infected with false smut. Data were taken from reference (9).

The trends of relative concentrations of mineral nutrients observed using LIBS and WDXRF were similar. Using LIBS and WDXRF, we have observed the pattern for copper, silicon, and calcium as R1 > R2 > R3, whereas for chromium, iron, and magnesium, the trends was R2 > R1 > R3. Some mineral elements, such as potassium and manganese, followed patterns of R3 > R2 > R1 and R2 > R3 > R1. From these studies, it was concluded that the two techniques are complementary to each other and can be used collectively for investigating elemental changes that may take place in the composition of the plant samples with the association of various plant diseases.

As mentioned previously, it is documented in the literature that the induction of some mechanical obstructions, production of anti-oxidant compounds, and triggering of defense systems in the plant body all are correlated with good accessibility of the important mineral nutrients in the plant body (9). In our study, we have observed that some major elements, such as potassium, phosphorus, and sulfur, were present in higher concentrations in the diseased rice grain samples, and it is feasible to relate these increases with the production, induction, and activation of various defense systems that hinder the further movement of the pathogens into the plants body. Sieverding and others have also reported increased concentrations of potassium and phosphorus in corn crop plants following inoculation with 

 (16). The concentration values of the nutrient element sulfur increased from 0.14 in uninfected rice grains to 0.2% in diseased rice grain samples.

We also noticed significant increases in the concentrations of chlorine and manganese in diseased rice grain samples. The increased level of chlorine can be related with the initiation and activation of defense responses against fungal spores (15). Identical increasing trends were also seen and reported by other researchers (7,17). In one study, where an elevated concentration of manganese was observed in the barley plant samples, the author claimed that such elevation is because of the stimulation of manganese content with the association of microbes present in the rhizosphere of soil (18). The same patterns corresponding to elements such as chlorine, manganese, potassium, phosphorus, nickel, and sulfur has been seen and reported by Singh and others in studies of nematode-infested wheat grains by WDXRF spectroscopy (17).

In our studies, we also observed lower concentrations of aluminum, calcium, copper, iron, magnesium, silicon, and zinc with the infestation of black and yellow smutty fungal spores in rice. The decreased level of magnesium was also seen and reported by Bateman and others while doing investigations of beans from plants infected with the fungus 

 (19). Because major elements such as calcium and magnesium are related with the maintenance of outer cell walls, the decreasing levels of these elements may be associated with the weakening and diminishing of cell walls, leading to escape of sugars and amino acids from plant tissues and thereby attracting the attention of several fungal species. Imbalances in the contents of the macroelements such as calcium, potassium, and magnesium, were also reported with the occurrence of green stem and foliar retention (GSFR) disease on the plant samples (9).

Rice plants are well-known for their capacity to accumulate high levels of silicon from the soil (20). In our findings, we noticed a decrease in the content of silicon with the association of smutty balls in the rice crop plant. The content of silicon falls from 1.27% in uninfected rice grains to 0.45% in diseased rice grain samples with the occurrence of fungal disease. The role of silicon is similar to that of calcium and magnesium: It is known for maintaining the strength of the outer cell walls, so a decreased level of silicon indicates the diminishing of the outer layer of cell walls (21).

We also saw lower concentrations of aluminum, copper, iron, and zinc in diseased rice grain samples with the arrival of fungal diseases on rice crop plants. The particular role of aluminum and chromium elements in the physiological and biological behavior of plants has not been determined yet. In our findings, we have observed that the level of aluminum decreases from 0.03 to 0.01% with the occurrence of fungal disease in rice crop plants.

The element chromium is known for its toxicity and causes various detrimental effects on the physiological behavior of a plant system, such as disturbing the uptake capacity of mineral nutrients and water intake, inducing oxidative stresses, interfering the photosynthesis mechanism, and causing plant cell death (9). These toxic effects of chromium begin with the association of 0.0005% of chromium in the agronomic plants (9). The concentration of chromium in our results rose from 0.0011 in uninfected rice grains to 0.0046% in rice grain samples infected with fungal disease. Similar results for chromium were observed by Singh and others (17) in spectroscopic investigations of nematode- and fungal-infested wheat seeds and by Sharma and others (7) in nematode- and fungal-infested okra root samples.

It is well-documented in the literature that the pathogens started developing strategies to minimize its defense systems and make them totally depriving of basic nutrients after intruding the host body whereas the host body in response makes some changes in its internal composition to restrict further movement of the pathogens into the plant body (9). Thus, the decreasing and increasing contents of some nutrient elements with the occurrence of smutty fungal spores on the surface of rice spikelets due to the arrival of false smut disease can be considered the consequences and responses of the host body with the attack of pathogens.

In conclusion, we present a summary of the plant species, disease, and elements detected in healthy and diseased plant samples in Table I. Elements whose concentrations increased and decreased because of the disease are listed in Table I. Table I indicates the observable changes in the concentrations of elements, related to the diseases that occurred in the plant samples.

In the present work, we explored potential applications of WDXRF for analyzing important agricultural crops, which provided valuable information regarding their elemental composition. This information is then used to characterize their behavior after infestation by plant diseases such as nematodes and false smut disease.

However, elemental imaging techniques, such as scanning electron microscopy (SEM) with energy dispersive X-ray analysis (EDX), field emission (FE)-SEM, and micro-XRF, would provide additional information regarding the role of heavy and toxic elements in these plant diseases. These methods would enable a useful visualization and mapping of the distribution of organic matter as well as the changes in the mineral elements on a micrometer scale. Also, more exhaustive work on the multivariate analysis of WDXRF data will provide more information related to these kinds of diseases (nematodes, false smut and other bacterial and fungal diseases) in agricultural crops.

Ms. Neha Sharma (Senior Research Fellow, SRF) is thankful to DST, Government of India for INSPIRE Fellowship (IF160893). Author Vivek K. Singh is thankful to Shri Mata Vaishno Devi University, India, for all kinds of support to carry out this research.

Encyclopaedia of Life Support Systems (EOLSS)

(2) L. Trevizan, D. Santos, R. Samad, N. Vieira, C. Nomura, L. Nunes, L. Rufini, and F. Krug, 

(3) G. Dalcorso, A.Manara, S. Piasentin, and A. Furini, 

(4) E. Margui, M. Hidalgo, and I. Queralt, 

(5) J.B. Godey, Laboratory Methods for Work with Soil and Plant Nematodes (Technical Bulletin Ministry of Agriculture, London, United Kingdom, 1963). 

(7) N. Sharma, Y. Khajuria, J. Sharma, D.K. Tripathi, D.K. Chauhan, V.K. Singh, V. Kumar, and V.K. Singh, 

(8) N. Sharma, Y. Khajuria, V.K. Singh, S. Kumar, Y. Lee, P.K. Rai, and V.K. Singh, 

(9) N. Sharma, Kamni, V.K. Singh, S. Kumar, Y. Lee, P.K. Rai, and V.K. Singh, 

(10) A.A. Farahat, A. Al-Sayed, and N.A. Mahfoud, 

(12) H. Brhane, E. Fikru, T. Haileselassie, and K. Tesfaye, 

(13) L. Reale, F. Ferranti, S. Mantilacci, M. Corboli, S. Aversa, F. Landucci, C. Baldisserotto, L. Ferroni, S. Pancaldi, and R. Venanzoni, 

(16) E. Sieverding, G.A. Silva, R. Berndt, and F. Oehl, 

(17) V.K. Singh, A. Devi, S. Pathania, V. Kumar, D.K. Tripathi, S. Sharma, D.K. Chauhan, et al, 

(20) E. Takahashi, J.F. Ma, and Y. Miyake, 

(21) D. Bhaduri, R. Rakshit, and K. Chakraborty, 

 are with the School of Physics at Shri Mata Vaishno Devi University, in Katra, India. 

 is with the Department of Plant Pathology in the College of Agriculture at Banda University of Agriculture and Technology, in Banda, Uttar Pradesh, India. Direct correspondence to: 

Articles

In these studies, wavelength dispersive X-ray fluorescence (WDXRF) was used to examine differences in the elemental composition of agricultural samples, comparing healthy and diseased samples of okra, papaya, and rice. Both the mineral nutrient profiles (macro and micronutrients) and toxic metals were examined, revealing common patterns.

Application of Wavelength Dispersive X-ray Fluorescence to Agricultural Disease Research

n this study, we analyzed a tooth sample of a renal patient using wavelength-dispersive X-ray fluorescence (WDXRF) spectrometry and Fourier transform infrared (FT-IR) spectrometry to quantify major and trace elements, and heavy and toxic elements in particular. The elements detected and quantified in the tooth sample were calcium (Ca), phosphorus (P), carbon (C), oxygen (O), magnesium (Mg), sodium (Na), chlorine (Cl), sulfur (S), potassium (K), silicon (Si), iron (Fe), aluminum (Al), zinc (Zn), strontium (Sr), chromium (Cr), nickel (Ni), copper (Cu), and zirconium (Zr). FT-IR spectrometry has been used to extract relevant information about the molecular contents of the tooth sample. We have compared our results with those obtained in the laboratory for the healthy subjects, and also with the values reported in the literature as obtained using XRF spectrometry only. Elements found in the tooth sample were correlated with the chronic kidney disease (CKD) of the patients. An outline of the XRF apparatus and applications of XRF as a tool for analyzing to dental specimens are also briefly highlighted.

Vivek K. Singh, Shikha Sharma, Mahima Sharma, Neha Sharma, Jitendra Sharma, and Pradeep K. Rai

	
	Calcified tissues, such as bones and teeth, contain biological signatures from their living phase. The habitat and nutritional and environmental conditions of people can be determined by monitoring the trace elements present in these samples (1). This is not unexpected, as teeth have both an organic and inorganic phase. Teeth and bones consist of an inorganic calcium phosphate mineral approximated by hydroxylapatite and matrix proteins with a small amount of proteolglycans and lipids (2). In contrast, the inorganic phase is composed of well-packed nanocrystals of calcium apatite, together with trace elements (3). The trace elements in the tooth can vary, depending on the source of food and water, as well as from soil and dermal absorption (1–4). Accurate determination of trace elements in calcified tissues still remains a challenge for biomedical researchers. X-ray fluorescence (XRF) spectrometry offers a reliable approach to provide rapid multi-elemental analysis of biological samples in µg/g (ppm) range, and it is a non-destructive technique that allows samples to be preserved for further experimentation (5). Instrumentation, such as wavelength-dispersive XRF (WDXRF), can now be effectively used to accurately measure trace elements in the human tooth. Such information not only provides a useful assessment of the diet, but reflects specific environmental and disease conditions as well.

	Recent biochemical studies provide insight into the factors controlling the formation and growth of bioapatite crystals, and how alterations in the mineralization process can lead to diseases such as osteoporosis. The relationship between chronic kidney disease (CKD), specifically hypercalciuric nephrolithiasis, osteoporosis, and bone mineral density (BMD), is well established. A large number of epidemiologic studies linked to evaluating factors associated with BMD in men have amply demonstrated that history of renal disease is indeed associated with lower BMD (6). The kidneys play an important role in maintaining healthy bone mass and structure by balancing calcium (Ca) and phosphorus (P) levels in the blood. Mineral and bone disorders in CKD occur when damaged kidneys and abnormal hormone levels cause Ca and P levels in a patient’s blood to be out of balance. CKD causes mineral and bone disorders, and thus kidneys stop activating calcitriol. The low levels of calcitriol in the body in turn create an imbalance of Ca in the blood by not removing the P in the blood proportionately, so the P level rises in the blood. The extra P pulls Ca out of the bones, causing them to weaken. Consequently, bone losses from the jaw occur in the CKD patients. Such weaker bones can cause teeth to become loose, and eventually fall out.

	Therefore, in this paper, we present results from our investigation of major (Ca, P, magnesium [Mg], sodium [Na], chlorine [Cl], sulfur [S], potassium [K], silicon [Si], iron [Fe], aluminum [Al], zinc [Zn], strontium [Sr}, chromium [Cr], nickel [Ni], copper [Cu], and zirconium [Zr]), trace elements, and toxic metals using WDXRF spectrometry in a tooth sample obtained from a CKD patient. We have compared our results with literature reported values (using XRF spectrometry only) and laboratory values for healthy subjects. Fourier transform infrared (FT-IR) spectrometry has also been used to investigate the phosphate, carbonate, and amide contents of teeth samples. This paper presents a very crucial application of WDXRF spectrometry to quantify heavy and toxic elements of calcified tissue materials like tooth samples from renal patients with CKD.

	The tooth sample from the CKD patient was kindly provided by the Department of Nephrology at Opal Hospital in Varanasi, India. In the present work, the studied tooth sample was one that had become loose, and had eventually fallen out of the jaw of a CKD patient. The received tooth sample was dried and stored in a sealed pot after washing in deionized water to remove all traces of possible contaminants. The as-received tooth sample was examined visually, to check for caries. The tooth sample was not affected by caries, and therefore the present study was not influenced by caries formation. The tooth was then powdered using a mortar and pestle, and the powdered tooth sample was used subsequently for experimental measurements using FT-IR and WDXRF spectrometry.

	The ground tooth sample was used to record the FT-IR spectrum in a transmittance mode setting for the spectral region of 4000-400 cm

 on an IRTracer-100 Fourier transform infrared spectrophotometer (Shimadzu), using a single-reflection attenuated total reflection (ATR) accessory. In this spectrophotometer, the FT-IR spectrum is recorded in a very simple manner, as only few milligram (mg) of sample (solid or liquid ) are required to place on the surface of the ATR prism. However, solid samples must be held on the surface of the prism using the provided pressure clamp. The spectra can be recorded either in absorption mode or in transmission mode.

	XRF analysis provides elemental mapping and imaging information using emitted characteristic X-rays from the sample. Figure 1 shows the mechanism of characteristic X-ray generation. With the bombardment of high-energy electrons or high-energy X-rays, a bound electron is struck out of the target atom. After the electron is ejected, an outer shell electron falls into the vacant inner shell, resulting in the emission of characteristic X-rays with an energy equal to the difference of energy between the outer and inner shell energy levels. These X-rays generated through the bombardment of high energy X-ray irradiation are termed

. Each element with inherently different energy levels (for the set of electrons it possesses) emits X-rays of energies that uniquely identify this characteristic element. Therefore, such characteristic X-rays can easily be exploited to perform elemental analysis of a sample. Further details of the theory and applications of XRF spectrometry can be found in reference sources (7–11).

	High performance WDXRF spectrometry is now being used for the determination of traces in plant materials, biological samples, and geological samples. To fulfill today’s requirements for quality data, modern instruments must provide high elemental sensitivities to achieve low detection limits and optimal spectral resolution to minimize line overlays. In this work, we have used a WDXRF spectrometer S8 Tiger (Bruker) for the quantitative measurements of major, trace, and heavy elements in the sample. It provided the optimum quantitative results in terms of detection limits, resolution, and reliability for each element with the best excitation and highest intensity over the entire elemental range.

	In this WDXRF spectrometer, an end-window X-ray tube with 

Rh anode is adjusted to a voltage of 60 kV and a current of 170 mA, correlating to a maximum power supply of 4kW to generate the primary beam. To ensure more accurate and reproducible results, the tooth sample was analyzed three times. For the detection of lighter elements, a flow proportional counter is used, and, subsequently, a scintillation counter detector is used to detect heavier elements. The acquisition time taken to capture a single spectrum of the sample was 20−25 min. The analyzer crystal LiF(220) ensures that in combination with the 0.23° collimator, the best separation is achieved for adjacent elements. The mask size was 23 mm, and the spectrum was recorded in vacuum. Technical details of the spectrometer used in the present study can be found elsewhere (12). In the present work, while analyzing data, the maximum relative standard deviation (RSD) obtained was 5%. To measure the concentration of trace and heavy elements, the S8 Tiger WDXRF spectrometer uses a standardless semi-quantitative Spectraplus software (Quant Express) package. The technical details of this software can be found elsewhere (12). The unique feature of this software is that it corrects all the matrix effects based on theoretically fundamental physical parameters, such as absorption coefficients and secondary fluorescence enhancement, automatically. In this software, the elemental concentration has been determined using Sherman’s equation (13):

 is the measured intensity of the corresponding line; 

 are the concentrations of the other elements 

 are the coefficients of the calibration regression line, respectively, namely offset and slope. The advantage of this software is that it does not need any standard reference materials to check its reliability and reproducibility with respect to the given samples.

	Because of the limited amount of the tooth sample, we have used the sandwich method to create a pellet. The powdered tooth samples are pressed onto approximately two spatulas full of boric acid using a constant pressure of 15 tons for 15 s on the stainless steel die head using a hydraulic press to prepare a smooth and uniform surface. This method is generally used in cases of limited sample size, and, in such cases, the use of a non backscattering boric acid matrix is recommended (7–11).

Analysis of Tooth Sample Using FT-IR Spectrometry

	Unless otherwise noted, the literature citations for band assignments are given in references (14,15). The FT-IR spectra of the tooth sample are shown in Figures 2 and 3, and the functional groups found in the sample are indicated in their respective wide scan FT-IR spectra (Figures 2 and 3). A typical -OH stretching band is clearly visible at 3300 cm

. The characteristics peaks of phosphates appear at 579, 590, 608, and 614 cm

 asymmetric bending mode of ), 1023, 1043, 1052, and 1069 cm

 asymmetric stretching mode of ), 431, and 446 cm

 symmetric stretching mode of ). Phosphates in the sample are identified by the characteristic absorption band at 1035 cm

 asymmetric stretching of . Other phosphate bands (relatively broader) appeared around at 985 and 925 cm

 stretching in , is assigned to type B carbonate
	( ions substituting  sites), located at 870 cm

 mode presented two bands, one at 1412 cm

, respectively, while type B carbonate ν

 (shoulder peak) (8). Type A carbonate (substituting  sites) in the ν

	The four primary amide bands are amide I (1700−1600 cm

 represents amide III
	(N–H stretching vibration). The amide I band is representative of the secondary structure of proteins. It can be decomposed into three main components; the most intense being the central one, at about 1660 cm

, which has low- and high-frequency shoulders. Usually a shoulder peak is observed near 1620 cm

, which is attributed to the amide I feature of dentin and hydrated gel-like collagen. In the present study, the amide I vibrations arising from C=O stretching were centered in the broader 1627 cm

 band, with shoulders at 1604 and 1665 cm

, respectively. The amide A region, where the N–H stretching vibrations of the amide normally appear, had its major intensity peak near 3300 cm

 (overlapped with an OH stretching broadband around 3300 cm

). The amide B region, arising from C–H stretching, exhibited a band with higher intensities at 2857 and 2927 cm

, respectively. Absorption peaks centered at 1242 cm

 have been characterized as amide III (N–H stretching vibrations).

Analysis of Tooth Sample Using WDXRF Spectrometry

	The concentration of different elements present in the tooth sample was determined using WDXRF spectrometry measurements, and the values obtained are presented in Table I. The major and trace elements detected and quantified in the sample were calcium (Ca), phosphorus (P), carbon (C), oxygen (O), magnesium (Mg), sodium (Na), chlorine (Cl), sulfur (S), potassium (K), silicon (Si), iron (Fe), aluminum (Al), zinc (Zn), strontium (Sr), chromium (Cr), nickel (Ni), copper (Cu), and zirconium (Zr). Figure 4 depicts a typical WDXRF spectrum of the tooth sample obtained from the WDXRF spectrometer indicating the different elements present in it. In Table I, we have also summarized the concentration of major and trace elements found in the sample and compared them with those reported in the literature using only XRF techniques (16–21). Similarly, Table II presents the concentration of some major elements, including Ca, P, Mg, Na, K, and Cl, found in the studied sample, along with the average values for sound human enamel and dentin as reported by different laboratories (22–26). Here, to compare with our data, the concentration values from the healthy teeth were considered in the same way as we have analyzed the tooth sample from CKD patients. For the present study, we have analyzed the whole tooth, including enamel and dentine, by making them into a powder. As a constraint (refer to Table II), we are bound to compare our results with the literature-reported values of healthy subjects only, and not with the healthy teeth of the same CKD patient because we are unable to collect healthy teeth from the same patient.

	Organic matrix elements detected in the tooth sample were carbon (C) and oxygen (O). The elements Ca (14.73%), and P (7.98%) were the most abundant elements in the studied sample, as substantiated by other reports as well (16–26). It is clear from Table II that the concentrations of elements Ca, P, Mg, K, and Cl are lower in the tooth sample of the CKD patient than that from healthy teeth. Figure 5 clearly shows the relative concentration of such elements in the studied tooth sample. No such variation was observed for Na. The Ca to P ratio was also not consistent with the literature reported value. We noted that CKD apparently caused the imbalance of P in the blood, which in turn affects the Ca in tooth and bone, which is considered as being a major cause of imbalance of Ca in tooth and bone. Reduced amounts of Ca, P, and other major elements (necessary for healthy teeth) were indicated in the tooth sample and may have been caused by CKD and its consequences on the patient.

	Most of the elements detected in the tooth were those that accumulated within the structure of hydroxyapatite over time. Numerous substitution metals can be found in hydroxyapatite crystals; metal cations such as K

, whereas anionic complexes, including ,  or , can provide a substitute for , and anions such as Cl

 in the crystal structure (26–29). Therefore, it is not surprising to find these elements in the tooth sample we studied. However, our main objective was to present a comparative study (comparing to a healthy subject) to investigate the accumulation of elements in tooth samples of renal patients.

	In Table I, we have summarized the concentrations of major and other heavy and toxic elements found in the tooth sample of the present study along with the literature reported values (16–21). We have considered the recent studies of tooth samples using XRF spectrometry alone. Figures 6–11 show the relative concentrations of different elements and their variations. The Ca to P ratio (Ca/P) is an indicator of the relative strength of bones or teeth (30,31). From the Ca/P ratio plotted in Figure 6, one can easily see that the Ca and P values measured from the sample are relatively less as compared to the values reported by others like Buddhachat and associates (16), Oprea and colleagues (17), Baranowska and co-workers (18), Aadim and associates (19), Teruel and colleagues (20), and Bielecka and co-workers (14). Also, the Ca/P ratio reported by Buddhachat and associates (9), Oprea and colleagues. (10), Baranowska and co-workers. (18), Aadim and associates (19), and Teruel and colleagues (20) lie in the range of 1.94 to 2.44, which is also in good agreement with the reported values (average value ~2.07) for sound enamel and dentin, with the exception of Bielecka and co-workers (21) (value ~1.77). In the present study, the value obtained was ~1.84, which indicates different Ca and P levels due to the CKD affected tooth. The major elements Mg, Na, and Cl were also found to be lower in the tooth sample as compared to the reported values (16–21), which can be seen in Figures 7 and 8.

	In addition, the concentration of essential elements such as S, Si, and Zn was observed to be lower (as can be seen in Figure 9) than the literature reported values (16–21). Values obtained for potassium (K) were a little higher (Figure 8) than those in the literature. The other heavy and trace elements such as Fe, Al, Sr, Ni, Cu, and Zr were found in a different concentration range, as shown in Figures 8–11. The overall relative concentrations in log percentage value of major, trace, heavy, and toxic elements found in the tooth sample in the present study and reported values are plotted for comparison. The relative difference in the concentration of elements, particularly Fe, Al, Sr, Ni, Cu, and Zr, may be due to the different environmental and geographical regions to which the patient belongs, and also the patient’s dietary habits, which is a major factor that can influence the concentration of such elements in teeth. Refer to references (16–21) for these elemental values.

	Recently, Boskey (32) has discussed a variety of human diseases in which altered mineral properties occur in bones and teeth in relation to age and sex-matched healthy individuals, presenting some examples of the mineral changes that include frequently encountered diseases, such as osteoporosis and osteomalacia, and less-common diseases such as osteopetrosis, osteonecrosis, and osteogenesis imperfecta and odontogenesis imperfecta. Some of these diseases are due to genetic abnormalities, but they may also be attributed, to a varying degree, to environmental factors such as diet, exposure to sunlight, and exercise (33). Renal osteodystrophy was reported as a consequence of kidney malfunction, which leads to osteoporotic bone and decreased mineral contents (32−34). The decreased contents (as compared to healthy subjects) of essential elements, particularly Ca, P, Mg, Na, and Cl, in the tooth sample may also be attributed to the chronic kidney disease and hence may be related to renal osteodystrophy. The presence of other nonessential and toxic elements indicates their role in CKD and tooth mineralization. However, more elaborate experiments on multiple samples from different patients and their extensive studies will be needed.

	The present study presents an interesting aspect for further studies of tooth samples of renal patients. In this case, we were only able to analyze the tooth sample from one CKD patient, as such tooth samples from renal patients (of different history) scarcely become available. We, therefore, have presented a case study only, on the elemental composition of a tooth sample from a renal patient. However, to extract detailed scientific data, more extensive studies will be needed to draw definite conclusions on the effects of CKD in calcified tissue materials like teeth and bones.

	New spectroscopic and microscopic techniques are emerging every day, providing scientists with useful tools for characterizing even minute changes or transformations in crystal properties from diseases, providing potentially fruitful areas of collaboration between physicists and biologists and offering hope for the development of novel therapies. In the present study, we have successfully utilized WDXRF spectrometry for the detection and quantification of the elemental composition of a tooth sample from a renal patient, which indicates the potential usefulness of this technique toward the analysis of calcified tissue materials like bones and teeth. The elemental contents were compared with the literature values for a more fruitful discussion. The data demonstrated that the distribution of elements can be used to explain biological processes related to CKD. We have also utilized FT-IR as a powerful tool for detecting organic and inorganic constituents of biomaterials and successfully characterized phosphates, type A and B carbonates, amide, and water content in the tooth sample of the CKD patient. Therefore, our studies on the tooth sample demonstrate that FT-IR is a robust tool for detecting organic and inorganic constituents of biomaterials. The presence of variable contents of essential and nonessential elements indicates their role in CKD and renal osteodystrophy. However, more extensive spectroscopic investigations on tooth samples are required for more fruitful results using XRF spectrometry. 

	Both Ms. Shikha Sharma and Ms. Mahima Sharma both contributed equally in carrying out the experiments and drafting of the manuscript. We are thankful to the Sophisticated Analytical Instrumentation Facility (SAIF), at Panjab University, in Chandigarh, for providing WDXRF experimental facilities. Our special thanks go to Mr. Tejbir Singh at the WDXRF Lab SAIF, for his valuable suggestions and discussions related to WDXRF spectrometry and instrumentation. The authors are also thankful to staff members at the Department of Nephrology at Opal Hospital, in Varanasi, India, for their constant and timely support in planning the experiments on a sample of choice.
	
	

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In this study, WDXRF and FT-IR are used to analyze a tooth sample of a renal patient, and to compare the results to healthy patients. The quantities of multiple elements are reported using the XRF technique, and FT-IR spectroscopy is used to extract relevant information about the molecular contents of the sample with the important absorption bands identified.

Neha Sharma

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