Distribution of phosphorus fractions and their relationships with physiochemical properties in the Agricultural soils of the Yamuna River region

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Little is known about the concentrations of phosphorus fractions in the phosphorus-deficient area of the Yamuna River bank in Prayagraj. To overcome this gap, we suggest the exploitation of soil phosphorus fractions from soil samples in the study area. Methods We analysed 24 soil samples from four different depths at six different sites in agricultural fields around the Yamuna River. The samples were analysed, and different phosphorus fractions were sequentially extracted. UV spectrometry was subsequently used to analyse the individual P fractions. Results We found that P-deficient soils were neutral in pH and low in salinity. Among the P fractions, calcium-P was the most predominant, followed by Fe-P, S-P, Occl-P, Red-P, and Al-P. Overall, the available P, organic P, and total P decreased with increasing depth, whereas calcium P was significantly positively correlated with organic carbon (r = 0.55*) and available nitrogen (r = 0.55*) and significantly negatively correlated with clay (r = -0.32*), pH (r = -0.22*), and EC (r = -0.23*). However, the occurrence of P is a major contributing factor to the availability of P in soils. Conclusion Our regression equations showed that soil pH was the main soil property influencing the different P fractions. Applying organic P fertilizers can improve the quantity of P in these soils, and if enhanced analytical techniques are applied to soil samples, it is possible to gain more detailed insights into the dynamics of phosphorus fractions. Phosphorus fractions Yamuna region P biogeochemistry Organic phosphorus Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Phosphorus is a crucial nutrient for plant growth and soil fertility and plays a vital role in agricultural productivity ( Tometin et al. 2023 ). To understand the distribution and dynamics of phosphorus fractions in the phosphorus-deficient area of the Yamuna Riverbank in Prayagraj, this study aimed to determine the concentrations of different phosphorus fractions in the phosphorus-deficient area of the Yamuna Riverbank in Prayagraj and conducted a comprehensive analysis of soil samples taken from agricultural fields surrounding the river. Sequential extraction methods and UV spectrometry analysis were employed to determine the concentrations of various phosphorus fractions in the soil samples. The results of the analysis revealed that the predominant phosphorus fraction in the soil was calcium-P, followed by Fe-P, S-P, Occl-P, Red-P, and Al-P. Another study revealed that available P, organic P, and total P decreased with increasing soil depth (Bogrekci & Lee, 2005 ). These findings suggest that soil pH plays a significant role in the distribution of different phosphorus fractions. Furthermore, researchers found significant positive correlations between calcium-P, organic carbon, and available nitrogen, indicating the influence of these factors on the distribution of phosphorus fractions in the soil. In conclusion, this study highlights the importance of understanding the distribution and dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj. By determining the concentrations of different phosphorus fractions in these soils, researchers can gain valuable insights into the biogeochemistry of phosphorus and identify methods to improve phosphorus availability and fertility (Shaheen et al. 2007 ). Inorganic phosphorus occurs in soil as a combination of iron (Fe), aluminium (Al), calcium (Ca), and other insoluble elements. Both organic and inorganic phosphorus can be found in the soil. Inorganic P comprises up to 80% of the total P in the surface layer, which makes it the most common type of soil P (Tomar 2003 ). The availability of inorganic P to plants can be restricted by the production of calcium phosphate, which is sparingly soluble in alkaline and calcareous soils; adsorption onto Fe and Al oxides in acidic soils; and the formation of Fe and Al phosphate complexes with humic acids. (Gerke1992). Therefore, they are not available for uptake by plants or microbes. The P fraction is mostly attached to Fe and Al to form variscite and stargate minerals in acidic soils and to Ca to form apatite in neutral to alkaline soils. Organic P compounds are mostly esters of orthophosphoric acid and have been found primarily as phospholipids and nucleic acids (Havlia et al.2004). The objective of this study was to improve the understanding of how phosphorus is transformed in soil and how to manipulate applied P fertilizers to increase their effectiveness, both of which are made possible by the distribution patterns of the various inorganic P components. Due to the variability in soil responses, phosphorus fractions other than rapidly soluble P are not readily available to plants. To evaluate the mineral nutrition of plants, knowledge of phosphorus forms, cropping history, and soil properties is essential. Therefore, the present study was designed to investigate the various phosphorus fractions in Prayagraj and their relationships with soil properties. By enhancing analytical techniques and conducting comprehensive soil analyses, researchers can obtain more detailed insights into the dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj. These insights can be used to develop targeted strategies for improving phosphorus availability and soil fertility in these areas, ultimately leading to increased agricultural productivity. Understanding the distribution and dynamics of phosphorus fractions in P-deficient areas, such as the Yamuna Riverbank in Prayagraj, is critical for effective soil management and agricultural productivity. Understanding the distribution and dynamics of phosphorus fractions in P-deficient areas, such as the Yamuna Riverbank in Prayagraj, is essential for developing sustainable agricultural practices and mitigating nutrient pollution in rivers. In conclusion, studying the distribution and dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj is crucial for devising effective strategies to improve soil fertility and agricultural productivity while minimizing environmental impacts. Understanding the distribution and dynamics of phosphorus fractions in P-deficient areas, such as the Yamuna Riverbank in Prayagraj, is essential for developing targeted interventions to increase phosphorus availability and soil fertility, thereby promoting sustainable agricultural practices and reducing nutrient pollution in rivers. In summary, this study highlights the importance of understanding the distribution and dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj for effective soil management, sustainable agriculture, and nutrient pollution reduction in rivers. 2. Materials and Methods 2.1 Study Area The study area of interest for this research was the Yamuna River Bank in Prayagraj, a phosphorus-deficient region in India. The study area chosen for this research was the Yamuna River bank in Prayagraj, which is known for its phosphorus-deficient soil conditions and its impact on phosphorus distribution. The study area selected for this research was the Yamuna Riverbank in Prayagraj, which is characterized by phosphorus-deficient soil conditions and is representative of similar phosphorus-deficient areas in India. The study area was located on the bank of the Yamuna River in Prayagraj, Uttar Pradesh. The study area's geographic coordinates were latitude 25.4358° N and longitude 81.8463° E. The maximum temperature ranged from 40°C (104°F) to 45°C (113°F), and the annual rainfall totals were greater than 934 mm. Prayagraj has the same humid subtropical climate as other towns on the plains of northern India and is regulated by the southwest monsoon. This area has a semiarid to subhumid climate. The Indo-Gangetic plain Prayagraj soils are alluvial and mostly comprise inceptisols. Sandy soils range from sandy loams to sandy clay loams. Wheat and rice are the primary crops grown in this area, and several other crops, such as Arhar, Urad, and Chana, have also been grown for pulse treatment. 2.2 Field studies Field studies were conducted on the Yamuna River bank in Prayagraj to investigate the distribution and dynamics of phosphorus fractions in the soil ( SHESHU et al. 2022 ). The field studies involved the collection of twenty-four soil samples from six different locations and depths along the Yamuna Riverbank in Prayagraj, Uttar Pradesh, Brazil. These samples were then air-dried, sieved, and subjected to various physicochemical property tests to determine the phosphorus distribution and dynamics in the soil. The investigation included the determination of available phosphate using the approach of Olsen NaHCO3 et al. and the fractionation of inorganic phosphorus employing the Chang and Jackson technique, as modified by Peterson and Corey. Furthermore, experiments were conducted by treating soil samples with different extractant solutions before performing a series of tests. 2.3 Methodology The methodology employed in this study involves several key steps. The soil samples used in the present study were collected from different locations and depths along the Yamuna Riverbank in Prayagraj, Uttar Pradesh, India. The soil samples were air-dried and sieved to 2 mm before undergoing various physicochemical tests. The NaHCO 3 Olsen extractant was used to determine the available phosphate concentration in the soil samples, while the Chang and Jackson technique, modified by Peterson and Corey, was employed to fractionate the inorganic phosphorus (Panghaal & Mittal, 2017). This study was conducted in Prayagraj, Uttar Pradesh, to improve the understanding of phosphorus transformation in soil and how to optimize the effectiveness of applied P fertilizers. Using the sequential extraction procedure described by Hedley et al., this study aimed to determine the content of total and available phosphorus, as well as its speciation in the surface horizons of agricultural soils (Jakubus, 2015 ). This study also aimed to investigate the influence of soil factors on phosphorus forms to gain insights into P availability dynamics. We used NaHCO 3 as an Olsen extractant to determine the available phosphate in the soil samples. They employed the Chang and Jackson technique, modified by Peterson and Corey, to fractionate the inorganic phosphorus (SHESHU et al. 2022 ). The treated soils were treated with each extractant solution prior to conducting a series of tests. The aim of this study was to assess soil health and phosphorus fertilization practices in the study area. This study aimed to assess soil health and phosphorus fertilization practices in the Prayagraj district of Uttar Pradesh, India. Based on the methodology used in this study, we aimed to understand phosphorus transformation in the soil of Prayagraj and to optimize the effectiveness of applied phosphorus fertilizers. The results from field studies conducted in Prayagraj, Uttar Pradesh, revealed important information about soil health and phosphorus fertilization practices in the study area. These findings contribute to the understanding of phosphorus dynamics in soil and provide insights into how to improve the efficiency of phosphorus fertilizer management in agricultural practices. This study can also help to improve the understanding of phosphorus transformation in soil and how to optimize the effectiveness of applied P fertilizers. The collected samples were air-dried, crushed using a wooden mallet, and sieved to remove coarse fragments (> 2 mm). The soil pH was measured in a 1:2 soil:water suspension using a glass electrode pH meter, and the salt content was determined by measuring the electrical conductivity (EC) of a 1:2.5 soil:water extract (Jackson 1973). The organic carbon in the soil was determined using the wet oxidation method described by Walkley and Black ( 1934 ). The particle size distribution was determined using a Bouyoucous hydrometer (Bouyoucous 1962 ). A graduated measuring cylinder was used to estimate the bulk density, particle density, porosity, and water-holding capacity (Muthuvel et al. 2019). Specific gravity was determined using the relative density of bottles by Black ( 1965 ). Available nitrogen was determined according to the method described by Subbiah and Asija (1956). Available phosphorus was determined by the Olsen1954 method. Available potassium was extracted with 1 N NH 4 OAc and subsequently measured by flame photometry (Jackson1973). The ethylenediaminetetraacetic acid (EDTA) titration method (Jackson 1973) was used for exchangeable Ca and Mg. The percentage of free iron oxide (Fe 2 O 3 ) was determined using atomic absorption spectroscopy. The total sesquioxide (R 2 O 3 ) and free aluminum oxide (Al 2 O 3 ) contents of the soil were determined by (Piper1950) using HCl extraction and subsequent precipitation with NH4OH. The sequential extraction of inorganic soil phosphorus fractions was performed as described previously (Chang and Jackson 1957 ), with modifications (Peterson and Corey1966), as shown in Fig. 2 . Soil samples were treated with a 1.0 N NH 4 Cl solution to extract loosely and easily soluble P (Saloid-P). The NH 4 -soil was successively extracted with neutral 0.5 N NH 4 F, 0.1 N NaOH and 0.5 N H 2 SO 4 for Al-P, Fe-P, and Ca-P, respectively. The extracted soil sample of Ca-P was subjected to dithionate-citrate reduction to determine the reductant soluble P (Red-P) and subsequently extracted with NaOH (0.1 N) to determine the occluded P. The total P in the soil was determined using the nitric acid and perchloric acid digestion method, as suggested by Hesse ( 1971 ). Organic P was determined as the difference between total P and inorganic P. 2.4 Data analysis The data recorded for the different parameters were analysed using an analysis of variance (ANOVA) technique for a customized block design with two factors and summary statistics. The mean effects were compared using the critical difference (CD) test at P < 0.05 and standard statistical methods (Fisher R.A. 1925 ). Pearson’s correlation coefficient (r) analysis between the soil properties and P fractions was also conducted (Soper et al. 1917). $$r= \frac{\sum \left({x}_{i}-\stackrel{-}{x}\right)\left({y}_{i}-\stackrel{-}{y}\right)}{\sqrt{\sum {\left({x}_{i}-\stackrel{-}{x}\right)}^{2}\varSigma {\left({y}_{i}-\stackrel{-}{y}\right)}^{2}}}$$ where r = correlation coefficient, xi = values of the x variable in a sample, x is the mean of the values of variables, yi is the value of the x-variable in a sample, and y is the mean of the values of y variables. 3. Results and Discussion The results and discussion of the study focused on the total and available phosphorus content in the surface horizons of agricultural soils (Jakubus, 2015 ). We used the sequential extraction procedure described by Hedley et al. to fractionate inorganic phosphorus and determine its speciation (Saleem et al. 2017 ). We also investigated the influence of soil factors on phosphorus forms to understand the dynamics of P availability. The study showed that agricultural soils had varying levels of total and available phosphorus, indicating differences in soil fertility. These differences could be attributed to various soil factors, such as pH, organic matter content, and nutrient management practices. Overall, the study provides insights into the dynamics of phosphorus availability in the soil and highlights the importance of considering soil factors in phosphorus fertilization practices to optimize nutrient availability and improve soil health. The findings of this study suggest that proper management of phosphorus fertilizers, taking into account soil factors and nutrient management practices, can significantly improve soil health and ensure efficient phosphorus fertilization in grassland soils. By understanding phosphorus dynamics in the soil and optimizing the effectiveness of applied phosphorus fertilizers, agricultural practices in the Prayagraj district of Uttar Pradesh can be optimized to achieve sustainable agricultural development and enhance crop yield. By adopting integrated nutrient management approaches and preserving the natural soil microbiome, farmers in Prayagraj can promote sustainable agriculture while effectively managing phosphorus fertilizers. 3.1 Characterization of the physicochemical properties of the soil The physicochemical properties of the soils collected from Inceptisols are presented in Table 1 . The soil profiles contained a high clay content compared with the sand and silt contents; the mean sand content ranged from 71.81%, the silt content ranged from 11%, and the clay content ranged from 16.75% for all the samples. The sandy loam texture was used for all the soil profiles, and the clay and sand contents varied from the topsoil to the subsoil. The bulk density of the profile ranges from 1.00 to 1.25 Mg m 3 , the particle density varies from 2-2.8 Mg m 3 , the percent pore space varies from 10–17%, and the solid space ranges from 83–90%. The water-holding capacity of the soil profiles ranges from 47–71%, and the specific gravity varies from 11–28 gcm 3 . The soil samples were neutral in nature, with a medium exchangeable Ca content ranging from 15 to 40 Cmol/kg − 1 soil. The reaction was neutral to alkaline, as reflected by the pH values ranging from 6.8–7.9. With an average annual rainfall range of approximately 1042 mm in the Prayagraj district, all soluble salts may have leached out from the profile. This was reflected in the very low-salinity soils in this region. The EC values ranged from 0.12 to 0.69 dSm-1. These soils are non-saline in nature, which might be due to the availability of sufficient rainfall to leach out soluble salts from the root zone or down to the profile (Arbind et al.2022). The organic carbon content of the soil ranges from 0.15 to 1.59%, with a mean of 0.69%. The organic carbon content of the topsoil was slightly greater than that of the subsoil. The medium to high OC content in these soils can probably be explained by the fact that most inceptisols are rich in organic matter. The available nitrogen content in the soil ranged from 31 to 333 kg ha − 1 from the topsoil to the subsoil. The available phosphorus content in the soil was low and decreased significantly with depth, ranging from 11–21 to kg ha − 1 . Available potassium varies from 51–112 kg ha − 1 . Table 1 Physiochemical properties of the soil samples. %Sand %Silt %Clay BD PD PS SS WHC SG pH EC OC Ca 2+ Mg 2+ N P K Fe 2 O 3 Al 2 O 3 R 2 O 3 % Mgcm − 3 % % gcm − 3 1:2 dSm − 1 % C mol/kg − 1 kg ha − 1 % Min 64.10 4.00 12.28 1.00 2.00 10.00 83.00 47.00 11.00 6.80 0.12 0.15 15.00 4.20 31.00 11.00 51.00 0.08 1.00 1.11 Max 80.16 17.85 26.23 1.25 2.80 17.00 90.00 71.00 28.00 7.90 0.69 1.59 40.00 51.40 333.00 21.00 112.00 0.13 2.40 2.48 Mean 71.81 11.08 16.75 1.11 2.34 13.48 86.46 57.63 19.04 7.40 0.34 0.69 26.24 13.55 144.71 13.54 82.71 0.10 1.53 1.63 Std. error 0.82 0.99 0.74 0.02 0.05 0.41 0.40 1.44 0.98 0.07 0.04 0.07 1.18 2.07 14.79 0.40 3.29 0.00 0.09 0.09 Stand. dev 4.01 4.87 3.64 0.09 0.22 2.00 1.98 7.07 4.81 0.34 0.19 0.35 5.80 10.16 72.44 1.98 16.10 0.02 0.45 0.45 Variance 16.08 23.68 13.27 0.01 0.05 3.99 3.91 49.98 23.17 0.12 0.04 0.12 33.67 103.17 5247.35 3.91 259.17 0.00 0.21 0.20 The abbreviations in the table are BD, bulk density; PD, particle density; PS, pore space; SS, solid space; WHC, water-holding capacity; SG, specific gravity; pH, hydrogen power; EC, electrical conductivity; OC, organic carbon; N, nitrogen; P, phosphorus; K, potassium; Fe2O3, iron oxide; Al2O3, aluminum oxide; and R2O3, total sesquioxide. 3.2 Soil phosphorus fractions The results for the soil phosphorus fractions are presented in Table 2 , and the correlation coefficients among the P fractions and soil properties are presented in the figure. Table 2 Distribution of phosphorus fractions in soils. S-P Al-P Fe-P Occl-P Red-P Ca-P Mineral P Total-P Organic-P Min 0.86 0.86 4.82 1.26 1.12 10.65 20.25 52.15 7.52 Max 7.06 2.24 8.24 5.70 2.81 35.09 54.50 97.19 53.25 % of total 4.14 2.15 10.45 3.98 3.01 31.57 55.30 - 44.70 Mean 2.53 1.36 6.54 2.56 1.87 19.73 34.58 62.82 28.24 Std. error 0.42 0.09 0.22 0.23 0.10 1.12 1.61 1.83 1.90 Stand. dev 2.08 0.44 1.09 1.13 0.47 5.48 7.90 8.99 9.30 Variance 4.31 0.19 1.20 1.27 0.22 29.98 62.38 80.75 86.40 Table 3 Depthwise distribution of phosphorus fractions in soils. S- P Al-P Fe-P Occl-P Red-P Ca-P Mineral P Total-P Organic-P 0–15 3.1 6.5 2.8 3.9 2.2 25.9 44.1 72.4 28.3 15–30 2.7 1.4 7.0 2.6 1.8 19.9 35.4 61.4 26.0 30–45 2.3 1.2 6.2 2.2 1.4 17.3 31.0 60.3 29.3 45–60 2.0 1.0 5.7 1.5 1.8 15.9 27.8 57.2 29.4 Min 2.0 1.0 5.7 1.6 1.4 15.9 27.8 57.2 26.0 Max 3.1 1.8 7.3 3.9 2.2 25.9 44.1 72.4 29.4 Mean 2.5 1.4 6.5 2.6 1.8 19.7 34.6 62.8 28.2 Std. error 0.2 0.2 0.4 0.5 0.2 2.2 3.5 3.3 0.8 Variance 0.2 0.1 0.5 1.0 0.1 19.5 50.1 44.2 2.5 3.3 Saloid-P (S-P) Saloid-P and S-P are influenced by various soil characteristics, such as the silt content, pore space, sand content, clay content, bulk density, solid space, water holding capacity, specific gravity, pH, exchangeable magnesium, and free iron oxide. Overall, saloid-P is a critical phosphorus fraction in the soil that is influenced by various soil characteristics and plays a significant role in nutrient availability and optimal plant growth. Saloid-P, or S-P, is a key phosphorus fraction in the soil that is influenced by various soil characteristics, such as the silt content and pore space. Overall, saloid-P is an important factor for nutrient availability and optimal plant growth. Saloid-P, also known as S-P, is a crucial fraction of P in the soil. The soil P content ranged from 2.0 to 3.0 mg/L and was 4.13%. Sal-P was significantly positively correlated with the silt content (r = 0.61*) and pore space (r = 0.55*). It was significantly negatively correlated with sand (r = -0.41* ), clay (r = -0.32*), bulk density (r = -0.33* ), solid space (r = -0.53*), water holding capacity (r = -0.39* ), specific gravity (r = -0.41* ), and pH (r = -0.47* ) and could be carried out by the transformation of loosely bound surface-adsorbed P into a less soluble form of P(Sacheti and Saxena 1973 ). Similar results were observed for clayey soils. exchangeable magnesium (r = -0.37*) and free iron oxide (r = -0.528*). There was a significant positive correlation between Ca-P (r = 0.56*) and inorganic P (r = 0.60*) due to strong weathering and a negative correlation between Fe-P (r = -0.42*) and organic P (r = -0.63*). This difference might be due to the neutral pH. Saloid P is loosely or weakly correlated with Fe-P, Red-P and Organic P, demonstrating that a profound correlation with the distribution of Saloid-P was detected, similar to the findings of Vishwanath and Doddamani 1991. To further understand the dynamics of phosphorus distribution in soil, it is important to consider the various phosphorus fractions and their relationships with soil characteristics. The negative correlation between Fe-P and organic P may be influenced by the neutral pH of the soil. In addition, the relationships between saloid-P and other phosphorus fractions, such as Fe-P and Red-P, indicate complex interactions and distributions of phosphorus in the soil. Interestingly, similar findings were reported by Vishwanath and Doddamani, highlighting the significance of saloid-P for soil fertility. 3.4 Aluminium-P (Al-P) The Al-P content in these soil profiles ranged from 1.61 to 1.83 mg/L, and the mean value of Al-P was 1.35 mg/L. Al-P comprised 2.15% of the total P, and a very low content of total P in the soils is an indication of strong weathering and well-drained humid tropics (Sarkar et al.2014). Among the fractions, Al-P was significantly positively correlated with Occl-P (r = 0.43*), Ca-P (r = 0.60*), mineral or inorganic P (r = 0.67*), and total P (r = 0.47*) and negatively correlated with organic P (r = -0.11*), while Al-P was positively correlated with pore space (r = 0.33*), aluminium oxide (r = 0.89*), and total sesquioxide (r = 0.89*). It was significantly negatively correlated with the clay content (r = -0.16*), solid space (r = -0.30*), pH (r = -0.40*), and exchangeable Mg (r = -0.21*). 3.5 Iron-P (Fe-P) The Fe-P content of the soil is one of the most important P fractions influencing its availability in the soil. among inorganic fractions. Fe-bound P was the second largest pool. This was expected because the soils were dominated by Fe sesquioxides (Arbind et al., 2020). The Fe-P in the soils ranged from 5.61 to 7.29 mg/L, with a mean value of 6.53 mg/L. Fe-P comprised 10.44% of the total P. A significant positive correlation was observed between Fe-P and the sand percentage (r = 0.64*), water-holding capacity (r = 0.86*), and free iron oxide (r = 0.56*). It was significantly negatively correlated with silt (r = -0.65*) and particle density (r = -0.42*), and Fe-P was positively correlated with Occl-P (r = 0.62*), Red-P (r = 0.64*), and total P (r = 0.54*); similar findings were found with Prahalad et al. 2014 and Organic P (r = 0.29*) due to mineralization and an increase in biological activity in soil. Similar findings were found by Sacheti and Saxsena (1973), Watham et al. ( 2018 ), Arbind et al. (2020) and Bhavsar et al. ( 2018 ). 3.6 Occluded-P (Occl-P) The Occl-P in the soil P fractions ranged a medium level and it varies from 1.54 to 3.89 mg/L, with a mean value of 2.55 mg/Land it representing 3.98% of the Total-P. Significant positive correlations between Occl-P and sand (r = 0.35*), water holding capacity (r = 0.54*), available phosphorus (r = 0.76*), available potassium (r = 0.42*), free iron oxide (r = 0.49*), aluminum oxide (r = 0.51*), and Total Sesquioxide (r = 0.53*) were observed and were negatively correlated with silt (r = -0. 35*), Occl-P was positively correlated with total P (r = 0.80*) and inorganic P (r = 0.55*). Ca-P (r = 0.42*) and Organic P (r = 0.31*). Similar findings have been reported by Bhavsar et al. ( 2018 ) and Arbind et al. (2020). 3.7 Red-P The soluble P reductant in the soil is adsorbed by the oxides or hydroxides of Fe and Al. The Red-P in the studied soils ranged from 1.6 to 2.1 mg/L, with a mean value of 1.86 mg/L occupying 3.0% of the total P. Red-P was significantly positively correlated with the water holding capacity (r = 0.56) and EC (r = 0.45). It was significantly negatively correlated with silt content (r = -0.21*), particle density (r = -0.33*), and pore space (r = -0.31*). Red-P was significantly positively correlated with inorganic P (r = 0.27*); similar findings were found by Bhavsar et al.2018, Prasad et al. 1986, and Arbind et al.2020. This fraction was the second least abundant fraction. A low Red-P value was observed in soils with a relatively high pH and sand content. This difference might be due to the increase in the iron- and aluminium-bound P contents and in the content of calcium-bound P, similar to the findings of (Viswanatha and Doddamani 1991, Sharma and Tripathi 1992 and Trivedi et al. 2010 ). 3.8 Calcium-P (Ca-P) The amount of Ca-P in the soils ranged from 15 to 25 mg/L, with a mean value of 19.72, accounting for 31.57% of the total P and resulting in the highest fraction among all the fractions. This may be because of the average range of Ca2 + ions in the soil. Ca-P was significantly positively correlated with pore space (r = 0.39*), organic carbon (r = 0.55*), available nitrogen (r = 0.55*), available potassium (r = 0.35*), aluminum oxide (r = 0.60*), and total sesquioxide (r = 59*). Ca-P was significantly negatively correlated with clay (r = -0.32*), solid space (r = -0.403*), pH (r = -0.226*), EC (r = -0.232*), exchangeable magnesium (r = -0.388*), and free iron oxide (r = -0.22*); significantly positively correlated with mineral P (r = 0.96*); and negatively correlated with organic P (r = -0.53*), similar to the findings of Bhavsar et al.2018 and Arbind et al. (2020). Calcium-bound P is typically the dominant inorganic soil P fraction. The close association between Ca-P and inorganic P was due to the dominance of Ca-P in soils (Bhavsar et al.2018), while the pH varied from 7.2 to 7.4. Within this range, calcium-bound P is often the dominant inorganic soil P fraction, and the calcareous character of most of these soils may be attributed to the large proportion of calcium-bound P. 3.9 Inorganic-P Inorganic P exists as an orthophosphoric acid salt. In general, inorganic P is the predominant form of soil P, constituting 20–80% of the total P in the surface layer (Tomar 2003 ). Inorganic P included all the fractions of P, that is, S-P, Al-P, Fe-P, Occl-P, Red-P, and Ca-P; the values ranged from 27 to 44 mg/L; and there was a significant decrease in the levels of P from the surface layer to the subsurface layers in all the profiles. Inorganic P was significantly positively correlated with EC (r = 0.491*), available nitrogen (r = 0.48*), available phosphorus (r = 0.33*), available potassium (r = 0.35*), aluminum oxide (r = 0.67*), and total sesquioxides (r = 0.66*). It was significantly negatively correlated with the clay content (r = -0.30*), solid space (r = -0.35*), and pH (r = -0.32*). Among the fractions, inorganic or mineral P was significantly and positively correlated with saloid P (r = 0.60*), Al-P (r = 0.67*), Occl-P (r = 0.55*), and Ca-P (r = 0.96*), as they are the major contributors to the inorganic form of P. 3.10 Organic-P The total organic P concentrations ranged from 25 to 28 mg/L, and it has been shown that there was a significant decrease in and irregular arrangement of organic P in a few of the profiles. This arrangement, compared to that of inorganic P, is due to the availability of Fe and Al oxides, which are available in inorganic P (Arbind et al.2020). Organic P was significantly and positively correlated with clay content (r = 0.42*), bulk density (r = 0.52*), solid space (r = 0.41*), available phosphorus (r = 0.66*), and free iron oxide (r = 0.49*). It was significantly negatively correlated with silt (r = -0.45*) and pore space (r = -0.410*), showing that more soils containing more silt had less organic P; similar results were found by Arbind et al. (2020) and available nitrogen (r = -0.34*). Organic P was positively correlated with Occl-P (r = 0.31*) and Total-P (r = 0.62*) The association of organic-P and Total-P highly correlated was reported by (Dongle 1993). Organic P was negatively correlated with saloid P (r = -0.63*), Ca-P (r = -0.53*), and inorganic P (r = -0.46*). 3.11 Total-P The average total P values ranged from 57 to 72 mg/L. A significant decrease in the P concentration from the surface layer to the subsurface layers was observed in all the profiles, possibly due to the continuous application of manures and P fertilizers to the top layers; similar results were found by Arbind et al.2020 and Dongale 1993 . Total P was significantly positively correlated with bulk density (r = 0.47*), water-holding capacity (r = 0.57*), available phosphorus (r = 0.97*), available potassium (r = 0.39*), and free iron oxide (r = 0.38*). Aluminum oxide (r = 0.47*) and total oxides (r = 0.48*) were observed. It was significantly negatively correlated with silt (r = -0.29*) and exchangeable Mg (r = -0.23*). Total P was positively correlated with Al-P (r = 0.478*), Fe-P (r = 0.546*), Occl-P (r = 0.806*), Ca-P (r = 0.300*), and the mineral P (r = 0.399*). According to the results for soils in Prayagraj, which are neutral to alkaline, all the soil samples were under permissible limits, with the nonsaline condition of electrical conductivity being suitable for crops. Of the soil samples, 58.3% had medium-high organic carbon contents due to low and high temperatures and less decomposition of organic matter in the soil; more than 50% of the samples had low and medium ranges of nitrogen and phosphorus and a high range of potassium; more than 52% of the samples had a high range of exchangeable calcium ions; and 70% of the soil samples had low levels of magnesium. The total sesquioxide hydroxides of iron and aluminium ranged from low to medium for free iron oxide, and the overall saloid-P values ranged from an average of 2.53 mg/L (4.13%), whereas the average Al-P of the samples ranged from 1.35 mg/L (2.15%), the lowest among all the fractions. The Fe-P values ranged from second highest at 6.53 mg/L (10.44%). The Occl-P values ranged from 2.55 mg/L (3.9%), which was within a medium range compared to all the other fractions. Red-P ranged from 1.86 mg/L (3%). The Ca-P values ranged from 19.72 mg/L (31.27%), with the highest values among all the fractions. The total P concentration ranged from 34.58 mg/L, while the inorganic P concentration ranged from 62.84 mg/L, while the total organic P concentration ranged from 28.24 mg/L (44.70%). 4. Conclusion Various phosphorus fractions (S-P, Al-P, Fe-P, Red-P, Occl-P, and Ca-P) contributed to the available and total P. Ca-P was found to be the most dominant in the inceptisols, and the content of the fraction sequence was Ca-P > Fe-P > S-P > Occl-P > Red-P > Al-P. Overall, the results indicate that organic P, available P, inorganic P, total P, and Occl-p are the main contributors to the decrease in available P with increased soil depth. Similar results were observed for the ultisols, for which the available P concentration was low, and the quantity and frequency of fertilizer additions and crop growth periods influenced the P fractions in the soil. The soil analysis results were interpreted using the literature, which helps farmers improve soil health and use proper fertilizers that supply deficient nutrients to crops. Further research is needed to develop bio interventions to convert mobile P into plant-available P, reduce the dosage of P fertilizer, and improve the application of organic P in the soil. Declarations Funding: None Conflicts of interest: The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this study. Ethical Approval: The authors declare no conflicts of interest. Ethical approval for this study was not required by our institute. Author Contribution M.S. Desigined and prepared the experiements and wrote the manuscriptA.H. Approved the study and Supervision T.T. and A.A.D. guidance throughout the study and supervision A.B. and R.S.K. prepared datasets and carriedout the experiements References Arbind Kumar Gupta, Luxmi Kant Tripathi and Prasanta Kumar Patra (2022). Distribution of phosphorus fractions in different soil orders of the Indo-Gangetic Plains in India. Annals of Plant and Soil Research 24(2):221-225. Arbind Kumar Gupta, Prashanta Kumar Patra and Luxmi Kant Tripathi (2020). Distribution and Classification of Phosphorus Fractions and their Relationships with Soil Properties in Ultisols of Meghalaya. Journal of the Indian Society of Soil Science 68, (4), 400-407. Bhavsar. M.S., Ghagare, R.B. and Shinde, S.N. (2018) Study of different phosphorus fractions and their relationship with soil properties in agricultural botany research farm, Nagpur, India. International Journal of Current Microbiology Applied Science 7, 1130-1137. Black, C.A (1965) Methods of Soil Analysis, American Society of Agronomy , Madison, Wisconsin, USA. Bogrekci, I., & Lee, W S. (2005, January 1). Spectral measurement of common soil phosphates. https://doi.org/10.13031/2013.20076 Bouyoucous, G.T. (1962) Improved hydrometer method for making particle size analysis of soils, Agronomy Journal 54, 464-465. Chang, S.C., and Jackson, M.L. (1957) Fraction of Soil Phosphorus. Soil Science 84, 133-134. Dongale, J.H. (1993) Depth wise distribution of different forms of phosphorus in lateritic soils of coastal region Journal of the Indian Society of Soil Science 41, 62-66. Fisher, R. A. (1925), Statistical Methods for Research Workers, Edinburgh: Oliver and Boyd. Gerke, J. (1992) Orthophosphate and organic phosphate in the soil solution of four sandy soils in relation to pH: Evidence for humic-Fe (Al) phosphate complexes. Communications in Soil Science and Plant Analysis 23: 601-612. H. E. Soper, a. W. Young, b. M. Cave, a. Lee, k. Pearson (1917) studied the distribution of the correlation coefficient for small samples. Appendix ii to papers of “student’ and R A. Fisher. A cooperative study, Biometrika , 11 (4), 328–413, Havlin, J. L., Beaton, J. D. Tisdale, S. L., and Nelson, W. L. (2004) Soil Fertility and Fertilizers: An Introduction to Nutrient Management, Sixth Edition., Pearson EdU. Pvt. Ltd., New Delhi. Hesse, R.R., (1971), Textbook of soil Chemical Analysis . John Murray and Co., London. Jackson M.L. Soil Chemical Analysis (1973) Prentice Hall of India (Pvt.) Ltd., New Delhi. Jakubus, M. (2015). Phosphorus forms in some grassland soils in Wielkopolska region: characterization and availability for plants. https://doi.org/10.17306/j.npt.2015.2.16 Kaistha B.P., Sharma P.C, Dubey Y.P.. (1999) Effect of manure and Phosphorus on the inorganic Phosphorus fractions in mountain soil of Himalayas, Crop Research 18, 206-210. Muthuval, P., Udaysoorian, C., Natesan, R., and Ramaswami, P.P. (1992). Introduction to soil Analysis, Tamil Nadu Agricultural University, Coimbatore- 641002 Olsen, S. R., Cole, C. Watanabe V, Dean FS, et al.. (1954). Estimation of available phosphorus in soils by extraction with sodium bicarbonate Unites States Department Agriculture circular 939. Dheeraj Panghaal, P.S. Sangwan and Mittal, S.B. 2017. Effect of Tillage and Phosphorus Fertilization of Wheat on Inorganic Soil Phosphorus Fractions under Wheat-Sorghum Cropping System. International Journal Current Microbiology and Applied Sciences . 6(3): 283-291. https://doi.org/10.20546/ijcmas.2017.603.031 Peterson, G.W., and Corey, R.B. (1966) A modified Chang and Jackson procedure for routine fractionation of inorganic soil phosphate. Soil Science 30, 563-565. Piper, C.S. (1966) Soil and Plant analysis . IV edition. University of Acelcide Adeitada, Australia, 135-200. Prahalad devra, S.R. Yadav and I.J. Gulati (2014). Distribution of different phosphorus fractions and their relationships with soil properties in the western plain Rajasthan. Agropedology , 24 (01), 20-28. Prasad, S. N., Singh, S. N., Singh, R. C. (1966). Correlation between the forms of P and soil properties. Journal of Applied Biology , 4, 55-58. Sacheti, A.K., and Saxena, S.N. (1973). Relationship between soil characteristics and various inorganic phosphate fractions of soils in Rajasthan. Journal of the Indian Society of Soil Science 21, 143-149. Saleem, A., Irshad, M., Hassan, A., Mahmood, Q., & Eneji, A E. (2017, September 1). Extractability and bioavailability of phosphorus in soils amended with poultry manure composted with crop wastes. https://doi.org/10.4067/s0718-95162017000300005 Shaheen, S M., Tsadilas, C., & Stamatiadis, S. (2007). Inorganic phosphorus forms in some entisols and aridisols of Egypt. https://doi.org/10.1016/j.geoderma.2007.08.013 Sharma, P.K., and Tripathi, B.R. (1992). Fractions of phosphorus from acid hill soils of northwest India. Journal of the Indian Society of Soil Science 40, 59-65 Sheshu, M., Hasan, a., Thomas, T., David, A A., Barthwal, A., & Khatana, R N S. (2022) Nutrient indexing of olsen’s phosphorous with relationship between inorganic forms of phosphorous in the alluvial soils. https://doi.org/10.53550/ajmbes.2022.v24i03.010 Subbaiah, B. V., Asija, G. L. (1956) A rapid procedure for the estimation of available nitrogen in soils. Current Science , 25, 259-260. Tomar, N.K. (2003). Effect of soil properties on the kinetics of P in acidic soil. Journal of the Indian Society of Soil Science 51, 508-511. Tometin, L., Chouti, W K., Chitou, N E., Dakpo, M O., Dannon, M., Suanon, F., Yalo, N., Mama, D., & Bawa, L M. (2023, February 6). Phosphorus Fractionation in Sediment and Agricultural Soils Surrounding Lake Toho in the Rainy Season. https://doi.org/10.9734/ijecc/2023/v13i11617 Trivedi, S. K., and Tomar, R. A. S., Tomar, P. S., Gupta, Naresh. (2010). Vertical distribution of different forms of phosphorus in alluvial soils of the grid region of Madhya Pradesh. Journal of the Indian Society of Soil Science 58, 86-90. Viswanath & Doddamani (1991) Distribution of fractions in some varieties Journal of the Indian Society of Soil Science 39, 441-445. Walkley, A and Black, C.A. (1934) An examination of rapid method for determination soil organic matter, and proposal for modification of the chromic acid titration method, Soil Science 37, 29-38. Watham, L., Athokpam, H.S., Chongtham, N., Devi, N.K., Singh, N.B., Singh, N.G., Sharma, P.T., and Heisnam, P. (2018) Phosphorus status in the soils of Imphal West District, Manipur, India. International Journal of Current Microbiology and Applied Science 7, 3871-3877. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4270803","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":293665382,"identity":"41b886ef-6a6a-4bcf-a432-630acad2f0da","order_by":0,"name":"Mutyalu Sheshu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYNCCAgYGAwYGNgaGCiCHmbmBgHJmBrB6iJYzIAFGUrQwtoFECGjRnZF/TOKHwWF7c/b2Z49559VG87cDtfyo2IZTi9mNZDbJHoPDiTt7zpgb8247njvjMGMDY8+Z23i1SPAYHE4wuJHDJs277VhuA1ALM2Mbfi2Sf4AOM7j//Jk075xjufOJ0SINtIVxww0GM2nehprcDQS1nHlsbC1jkJ644UyOmeScYwdyNwK1HMTrl+OJD2++qbC2Nzh+/JnEm5q63HnnDx988KMCtxYgYJFA4hwGkwfwqQcC5g9InDoCikfBKBgFo2AkAgBlDltHkCXYPwAAAABJRU5ErkJggg==","orcid":"","institution":"Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology \u0026 Sciences","correspondingAuthor":true,"prefix":"","firstName":"Mutyalu","middleName":"","lastName":"Sheshu","suffix":""},{"id":293665384,"identity":"46952691-3f6b-46a8-8c90-af865cc5234c","order_by":1,"name":"Amreen Hasan","email":"","orcid":"","institution":"Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology \u0026 Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amreen","middleName":"","lastName":"Hasan","suffix":""},{"id":293665386,"identity":"e1dab85c-4d6c-4353-a556-699b8742808b","order_by":2,"name":"Tarence Thomas","email":"","orcid":"","institution":"Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology \u0026 Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tarence","middleName":"","lastName":"Thomas","suffix":""},{"id":293665388,"identity":"9de115a8-cf66-473e-be14-0d98a88e2816","order_by":3,"name":"Arun Alfred David","email":"","orcid":"","institution":"Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology \u0026 Sciences","correspondingAuthor":false,"prefix":"","firstName":"Arun","middleName":"Alfred","lastName":"David","suffix":""},{"id":293665390,"identity":"ce9a1617-24f9-4d5a-aade-4b5e88deaf29","order_by":4,"name":"Akshita Bradawl","email":"","orcid":"","institution":"Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology \u0026 Sciences","correspondingAuthor":false,"prefix":"","firstName":"Akshita","middleName":"","lastName":"Bradawl","suffix":""},{"id":293665392,"identity":"06323268-b335-4937-a39c-cdab00fd53b6","order_by":5,"name":"Raghu Nandan Singh Khatana","email":"","orcid":"","institution":"Naini Agricultural Institute, Sam Higginbottom University of Agriculture Technology \u0026 Sciences","correspondingAuthor":false,"prefix":"","firstName":"Raghu","middleName":"Nandan Singh","lastName":"Khatana","suffix":""}],"badges":[],"createdAt":"2024-04-15 15:57:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4270803/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4270803/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55329673,"identity":"55d651b9-15c9-44b3-a54d-50d60368ccf3","added_by":"auto","created_at":"2024-04-25 19:03:09","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":208161,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area showing the sampling sites.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/07de8a9a40ae2b27f4a967ae.jpeg"},{"id":55329676,"identity":"4600f7bd-8da5-4ac8-bc32-10087a67404a","added_by":"auto","created_at":"2024-04-25 19:03:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":203660,"visible":true,"origin":"","legend":"\u003cp\u003eSequential extraction of phosphorus fractions and laboratory experiments.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/0f78994fb1a6045494d23e10.png"},{"id":55329675,"identity":"caf35344-b8d6-4e15-b106-4c798609e1df","added_by":"auto","created_at":"2024-04-25 19:03:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":28031,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical representation of the correlation coefficient (r) among the phosphorus fractions of the Inceptisols\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/7d2046724b9b23a8d0d56b8f.png"},{"id":55329672,"identity":"43425693-bd48-4682-830e-3edc172c2130","added_by":"auto","created_at":"2024-04-25 19:03:08","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":100165,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends in the P fraction distribution average and depth increase; \u003c/strong\u003e\u0026nbsp;\u003csup\u003ea\u003c/sup\u003eAverage trend of the P fraction distribution in the samples. \u003csup\u003e\u003cstrong\u003eb\u003c/strong\u003e\u003c/sup\u003e\u003csup\u003e \u003c/sup\u003eDepth wise trend of the P fraction distribution at the sites.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/7dfaae3225726a0db2eb329f.jpeg"},{"id":55329674,"identity":"dba21fe8-2a72-4e67-82b9-61477846c557","added_by":"auto","created_at":"2024-04-25 19:03:09","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":217694,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation and linear regression of the average with the distribution of P fractions.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/3b724bca69fea2c82b7d09ea.png"},{"id":55329678,"identity":"97c2e895-2a2a-42f6-b4bc-7746af607b3a","added_by":"auto","created_at":"2024-04-25 19:03:09","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":632280,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation and linear regression of depth with the distribution of P fractions.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/e19b8a36676ef8a680d4824a.jpeg"},{"id":55329677,"identity":"07f0baba-854e-4b5d-aad4-967ad6cab99a","added_by":"auto","created_at":"2024-04-25 19:03:09","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":34571,"visible":true,"origin":"","legend":"\u003cp\u003eRegression between total P and inorganic P\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/03317184f56e8e74570a6039.png"},{"id":59717629,"identity":"50f61646-1a42-4d77-a19f-20b3c0cca2a1","added_by":"auto","created_at":"2024-07-05 08:38:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2051698,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4270803/v1/cacd786f-656c-42ce-ad2c-c3986347d653.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Distribution of phosphorus fractions and their relationships with physiochemical properties in the Agricultural soils of the Yamuna River region","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePhosphorus is a crucial nutrient for plant growth and soil fertility and plays a vital role in agricultural productivity \u003csup\u003e(\u003c/sup\u003eTometin et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To understand the distribution and dynamics of phosphorus fractions in the phosphorus-deficient area of the Yamuna Riverbank in Prayagraj, this study aimed to determine the concentrations of different phosphorus fractions in the phosphorus-deficient area of the Yamuna Riverbank in Prayagraj and conducted a comprehensive analysis of soil samples taken from agricultural fields surrounding the river. Sequential extraction methods and UV spectrometry analysis were employed to determine the concentrations of various phosphorus fractions in the soil samples. The results of the analysis revealed that the predominant phosphorus fraction in the soil was calcium-P, followed by Fe-P, S-P, Occl-P, Red-P, and Al-P. Another study revealed that available P, organic P, and total P decreased with increasing soil depth (Bogrekci \u0026amp; Lee, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). These findings suggest that soil pH plays a significant role in the distribution of different phosphorus fractions. Furthermore, researchers found significant positive correlations between calcium-P, organic carbon, and available nitrogen, indicating the influence of these factors on the distribution of phosphorus fractions in the soil. In conclusion, this study highlights the importance of understanding the distribution and dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj. By determining the concentrations of different phosphorus fractions in these soils, researchers can gain valuable insights into the biogeochemistry of phosphorus and identify methods to improve phosphorus availability and fertility (Shaheen et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInorganic phosphorus occurs in soil as a combination of iron (Fe), aluminium (Al), calcium (Ca), and other insoluble elements. Both organic and inorganic phosphorus can be found in the soil. Inorganic P comprises up to 80% of the total P in the surface layer, which makes it the most common type of soil P (Tomar \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The availability of inorganic P to plants can be restricted by the production of calcium phosphate, which is sparingly soluble in alkaline and calcareous soils; adsorption onto Fe and Al oxides in acidic soils; and the formation of Fe and Al phosphate complexes with humic acids. (Gerke1992). Therefore, they are not available for uptake by plants or microbes. The P fraction is mostly attached to Fe and Al to form variscite and stargate minerals in acidic soils and to Ca to form apatite in neutral to alkaline soils. Organic P compounds are mostly esters of orthophosphoric acid and have been found primarily as phospholipids and nucleic acids (Havlia et al.2004).\u003c/p\u003e \u003cp\u003eThe objective of this study was to improve the understanding of how phosphorus is transformed in soil and how to manipulate applied P fertilizers to increase their effectiveness, both of which are made possible by the distribution patterns of the various inorganic P components. Due to the variability in soil responses, phosphorus fractions other than rapidly soluble P are not readily available to plants. To evaluate the mineral nutrition of plants, knowledge of phosphorus forms, cropping history, and soil properties is essential. Therefore, the present study was designed to investigate the various phosphorus fractions in Prayagraj and their relationships with soil properties.\u003c/p\u003e \u003cp\u003eBy enhancing analytical techniques and conducting comprehensive soil analyses, researchers can obtain more detailed insights into the dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj. These insights can be used to develop targeted strategies for improving phosphorus availability and soil fertility in these areas, ultimately leading to increased agricultural productivity. Understanding the distribution and dynamics of phosphorus fractions in P-deficient areas, such as the Yamuna Riverbank in Prayagraj, is critical for effective soil management and agricultural productivity. Understanding the distribution and dynamics of phosphorus fractions in P-deficient areas, such as the Yamuna Riverbank in Prayagraj, is essential for developing sustainable agricultural practices and mitigating nutrient pollution in rivers. In conclusion, studying the distribution and dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj is crucial for devising effective strategies to improve soil fertility and agricultural productivity while minimizing environmental impacts. Understanding the distribution and dynamics of phosphorus fractions in P-deficient areas, such as the Yamuna Riverbank in Prayagraj, is essential for developing targeted interventions to increase phosphorus availability and soil fertility, thereby promoting sustainable agricultural practices and reducing nutrient pollution in rivers. In summary, this study highlights the importance of understanding the distribution and dynamics of phosphorus fractions in phosphorus-deficient areas such as the Yamuna Riverbank in Prayagraj for effective soil management, sustainable agriculture, and nutrient pollution reduction in rivers.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Area\u003c/h2\u003e \u003cp\u003eThe study area of interest for this research was the Yamuna River Bank in Prayagraj, a phosphorus-deficient region in India. The study area chosen for this research was the Yamuna River bank in Prayagraj, which is known for its phosphorus-deficient soil conditions and its impact on phosphorus distribution.\u003c/p\u003e \u003cp\u003eThe study area selected for this research was the Yamuna Riverbank in Prayagraj, which is characterized by phosphorus-deficient soil conditions and is representative of similar phosphorus-deficient areas in India. The study area was located on the bank of the Yamuna River in Prayagraj, Uttar Pradesh. The study area's geographic coordinates were latitude 25.4358\u0026deg; N and longitude 81.8463\u0026deg; E. The maximum temperature ranged from 40\u0026deg;C (104\u0026deg;F) to 45\u0026deg;C (113\u0026deg;F), and the annual rainfall totals were greater than 934 mm. Prayagraj has the same humid subtropical climate as other towns on the plains of northern India and is regulated by the southwest monsoon. This area has a semiarid to subhumid climate. The Indo-Gangetic plain Prayagraj soils are alluvial and mostly comprise inceptisols. Sandy soils range from sandy loams to sandy clay loams. Wheat and rice are the primary crops grown in this area, and several other crops, such as Arhar, Urad, and Chana, have also been grown for pulse treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Field studies\u003c/h2\u003e \u003cp\u003eField studies were conducted on the Yamuna River bank in Prayagraj to investigate the distribution and dynamics of phosphorus fractions in the soil \u003csup\u003e(\u003c/sup\u003eSHESHU et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The field studies involved the collection of twenty-four soil samples from six different locations and depths along the Yamuna Riverbank in Prayagraj, Uttar Pradesh, Brazil. These samples were then air-dried, sieved, and subjected to various physicochemical property tests to determine the phosphorus distribution and dynamics in the soil. The investigation included the determination of available phosphate using the approach of Olsen NaHCO3 et al. and the fractionation of inorganic phosphorus employing the Chang and Jackson technique, as modified by Peterson and Corey. Furthermore, experiments were conducted by treating soil samples with different extractant solutions before performing a series of tests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Methodology\u003c/h2\u003e \u003cp\u003eThe methodology employed in this study involves several key steps.\u003c/p\u003e \u003cp\u003eThe soil samples used in the present study were collected from different locations and depths along the Yamuna Riverbank in Prayagraj, Uttar Pradesh, India. The soil samples were air-dried and sieved to 2 mm before undergoing various physicochemical tests. The NaHCO\u003csub\u003e3\u003c/sub\u003e Olsen extractant was used to determine the available phosphate concentration in the soil samples, while the Chang and Jackson technique, modified by Peterson and Corey, was employed to fractionate the inorganic phosphorus (Panghaal \u0026amp; Mittal, 2017). This study was conducted in Prayagraj, Uttar Pradesh, to improve the understanding of phosphorus transformation in soil and how to optimize the effectiveness of applied P fertilizers. Using the sequential extraction procedure described by Hedley et al., this study aimed to determine the content of total and available phosphorus, as well as its speciation in the surface horizons of agricultural soils (Jakubus, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This study also aimed to investigate the influence of soil factors on phosphorus forms to gain insights into P availability dynamics.\u003c/p\u003e \u003cp\u003eWe used NaHCO\u003csub\u003e3\u003c/sub\u003e as an Olsen extractant to determine the available phosphate in the soil samples. They employed the Chang and Jackson technique, modified by Peterson and Corey, to fractionate the inorganic phosphorus (SHESHU et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The treated soils were treated with each extractant solution prior to conducting a series of tests. The aim of this study was to assess soil health and phosphorus fertilization practices in the study area. This study aimed to assess soil health and phosphorus fertilization practices in the Prayagraj district of Uttar Pradesh, India. Based on the methodology used in this study, we aimed to understand phosphorus transformation in the soil of Prayagraj and to optimize the effectiveness of applied phosphorus fertilizers. The results from field studies conducted in Prayagraj, Uttar Pradesh, revealed important information about soil health and phosphorus fertilization practices in the study area. These findings contribute to the understanding of phosphorus dynamics in soil and provide insights into how to improve the efficiency of phosphorus fertilizer management in agricultural practices. This study can also help to improve the understanding of phosphorus transformation in soil and how to optimize the effectiveness of applied P fertilizers.\u003c/p\u003e \u003cp\u003eThe collected samples were air-dried, crushed using a wooden mallet, and sieved to remove coarse fragments (\u0026gt;\u0026thinsp;2 mm). The soil pH was measured in a 1:2 soil:water suspension using a glass electrode pH meter, and the salt content was determined by measuring the electrical conductivity (EC) of a 1:2.5 soil:water extract (Jackson 1973). The organic carbon in the soil was determined using the wet oxidation method described by Walkley and Black (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e1934\u003c/span\u003e). The particle size distribution was determined using a Bouyoucous hydrometer (Bouyoucous \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1962\u003c/span\u003e). A graduated measuring cylinder was used to estimate the bulk density, particle density, porosity, and water-holding capacity (Muthuvel et al. 2019). Specific gravity was determined using the relative density of bottles by Black (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1965\u003c/span\u003e). Available nitrogen was determined according to the method described by Subbiah and Asija (1956). Available phosphorus was determined by the Olsen1954 method. Available potassium was extracted with 1 N NH\u003csub\u003e4\u003c/sub\u003eOAc and subsequently measured by flame photometry (Jackson1973). The ethylenediaminetetraacetic acid (EDTA) titration method (Jackson 1973) was used for exchangeable Ca and Mg. The percentage of free iron oxide (Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) was determined using atomic absorption spectroscopy. The total sesquioxide (R\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) and free aluminum oxide (Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) contents of the soil were determined by (Piper1950) using HCl extraction and subsequent precipitation with NH4OH.\u003c/p\u003e \u003cp\u003eThe sequential extraction of inorganic soil phosphorus fractions was performed as described previously (Chang and Jackson \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1957\u003c/span\u003e), with modifications (Peterson and Corey1966), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Soil samples were treated with a 1.0 N NH\u003csub\u003e4\u003c/sub\u003eCl solution to extract loosely and easily soluble P (Saloid-P). The NH\u003csub\u003e4\u003c/sub\u003e-soil was successively extracted with neutral 0.5 N NH\u003csub\u003e4\u003c/sub\u003eF, 0.1 N NaOH and 0.5 N H\u003csub\u003e2\u003c/sub\u003eSO\u003csub\u003e4\u003c/sub\u003e for Al-P, Fe-P, and Ca-P, respectively. The extracted soil sample of Ca-P was subjected to dithionate-citrate reduction to determine the reductant soluble P (Red-P) and subsequently extracted with NaOH (0.1 N) to determine the occluded P. The total P in the soil was determined using the nitric acid and perchloric acid digestion method, as suggested by Hesse (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1971\u003c/span\u003e). Organic P was determined as the difference between total P and inorganic P.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data analysis\u003c/h2\u003e \u003cp\u003eThe data recorded for the different parameters were analysed using an analysis of variance (ANOVA) technique for a customized block design with two factors and summary statistics. The mean effects were compared using the critical difference (CD) test at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and standard statistical methods (Fisher R.A. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1925\u003c/span\u003e). Pearson\u0026rsquo;s correlation coefficient (r) analysis between the soil properties and P fractions was also conducted (Soper et al. 1917).\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$r= \\frac{\\sum \\left({x}_{i}-\\stackrel{-}{x}\\right)\\left({y}_{i}-\\stackrel{-}{y}\\right)}{\\sqrt{\\sum {\\left({x}_{i}-\\stackrel{-}{x}\\right)}^{2}\\varSigma {\\left({y}_{i}-\\stackrel{-}{y}\\right)}^{2}}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere r\u0026thinsp;=\u0026thinsp;correlation coefficient, xi\u0026thinsp;=\u0026thinsp;values of the x variable in a sample, x is the mean of the values of variables, yi is the value of the x-variable in a sample, and y is the mean of the values of y variables.\u003c/p\u003e "},{"header":"3. Results and Discussion","content":"\u003cp\u003eThe results and discussion of the study focused on the total and available phosphorus content in the surface horizons of agricultural soils (Jakubus, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). We used the sequential extraction procedure described by Hedley et al. to fractionate inorganic phosphorus and determine its speciation (Saleem et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). We also investigated the influence of soil factors on phosphorus forms to understand the dynamics of P availability. The study showed that agricultural soils had varying levels of total and available phosphorus, indicating differences in soil fertility. These differences could be attributed to various soil factors, such as pH, organic matter content, and nutrient management practices.\u003c/p\u003e \u003cp\u003eOverall, the study provides insights into the dynamics of phosphorus availability in the soil and highlights the importance of considering soil factors in phosphorus fertilization practices to optimize nutrient availability and improve soil health.\u003c/p\u003e \u003cp\u003eThe findings of this study suggest that proper management of phosphorus fertilizers, taking into account soil factors and nutrient management practices, can significantly improve soil health and ensure efficient phosphorus fertilization in grassland soils. By understanding phosphorus dynamics in the soil and optimizing the effectiveness of applied phosphorus fertilizers, agricultural practices in the Prayagraj district of Uttar Pradesh can be optimized to achieve sustainable agricultural development and enhance crop yield. By adopting integrated nutrient management approaches and preserving the natural soil microbiome, farmers in Prayagraj can promote sustainable agriculture while effectively managing phosphorus fertilizers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Characterization of the physicochemical properties of the soil\u003c/h2\u003e \u003cp\u003eThe physicochemical properties of the soils collected from Inceptisols are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The soil profiles contained a high clay content compared with the sand and silt contents; the mean sand content ranged from 71.81%, the silt content ranged from 11%, and the clay content ranged from 16.75% for all the samples. The sandy loam texture was used for all the soil profiles, and the clay and sand contents varied from the topsoil to the subsoil. The bulk density of the profile ranges from 1.00 to 1.25 Mg m\u003csup\u003e3\u003c/sup\u003e, the particle density varies from 2-2.8 Mg m\u003csup\u003e3\u003c/sup\u003e, the percent pore space varies from 10\u0026ndash;17%, and the solid space ranges from 83\u0026ndash;90%. The water-holding capacity of the soil profiles ranges from 47\u0026ndash;71%, and the specific gravity varies from 11\u0026ndash;28 gcm\u003csup\u003e3\u003c/sup\u003e. The soil samples were neutral in nature, with a medium exchangeable Ca content ranging from 15 to 40 Cmol/kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e soil. The reaction was neutral to alkaline, as reflected by the pH values ranging from 6.8\u0026ndash;7.9. With an average annual rainfall range of approximately 1042 mm in the Prayagraj district, all soluble salts may have leached out from the profile. This was reflected in the very low-salinity soils in this region. The EC values ranged from 0.12 to 0.69 dSm-1. These soils are non-saline in nature, which might be due to the availability of sufficient rainfall to leach out soluble salts from the root zone or down to the profile (Arbind et al.2022). The organic carbon content of the soil ranges from 0.15 to 1.59%, with a mean of 0.69%. The organic carbon content of the topsoil was slightly greater than that of the subsoil. The medium to high OC content in these soils can probably be explained by the fact that most inceptisols are rich in organic matter. The available nitrogen content in the soil ranged from 31 to 333 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e from the topsoil to the subsoil. The available phosphorus content in the soil was low and decreased significantly with depth, ranging from 11\u0026ndash;21 to kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Available potassium varies from 51\u0026ndash;112 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysiochemical properties of the soil samples.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"22\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%Sand\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%Silt\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%Clay\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eOC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eCa\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eMg\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c18\"\u003e \u003cp\u003eK\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003eFe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c21\"\u003e \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c22\"\u003e \u003cp\u003eR\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eMgcm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003egcm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1:2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003edSm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c15\" namest=\"c14\"\u003e \u003cp\u003eC mol/kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c19\" namest=\"c16\"\u003e \u003cp\u003ekg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c22\" namest=\"c20\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e83.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e47.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e15.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e31.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e11.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e51.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMax\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e71.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e40.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e51.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e333.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e21.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e112.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e86.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e19.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e26.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e13.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e144.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e13.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e82.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStd. error\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e14.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e3.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStand. dev\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e5.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e10.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e72.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e16.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e33.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e103.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e5247.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e259.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c20\" namest=\"c19\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"22\"\u003eThe abbreviations in the table are BD, bulk density; PD, particle density; PS, pore space; SS, solid space; WHC, water-holding capacity; SG, specific gravity; pH, hydrogen power; EC, electrical conductivity; OC, organic carbon; N, nitrogen; P, phosphorus; K, potassium; Fe2O3, iron oxide; Al2O3, aluminum oxide; and R2O3, total sesquioxide.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Soil phosphorus fractions\u003c/h2\u003e \u003cp\u003eThe results for the soil phosphorus fractions are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and the correlation coefficients among the P fractions and soil properties are presented in the figure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of phosphorus fractions in soils.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAl-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOccl-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRed-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCa-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMineral P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTotal-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOrganic-P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMax\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e97.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e53.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e% of total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e55.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e44.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e62.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStd. error\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStand. dev\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e62.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e86.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDepthwise distribution of phosphorus fractions in soils.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS- P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAl-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOccl-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRed-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCa-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMineral P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTotal-P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOrganic-P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e72.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e15\u0026ndash;30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e61.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e30\u0026ndash;45\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e60.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e45\u0026ndash;60\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e57.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMax\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e72.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e62.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStd. error\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVariance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e44.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Saloid-P (S-P)\u003c/h2\u003e \u003cp\u003eSaloid-P and S-P are influenced by various soil characteristics, such as the silt content, pore space, sand content, clay content, bulk density, solid space, water holding capacity, specific gravity, pH, exchangeable magnesium, and free iron oxide. Overall, saloid-P is a critical phosphorus fraction in the soil that is influenced by various soil characteristics and plays a significant role in nutrient availability and optimal plant growth. Saloid-P, or S-P, is a key phosphorus fraction in the soil that is influenced by various soil characteristics, such as the silt content and pore space. Overall, saloid-P is an important factor for nutrient availability and optimal plant growth. Saloid-P, also known as S-P, is a crucial fraction of P in the soil.\u003c/p\u003e \u003cp\u003eThe soil P content ranged from 2.0 to 3.0 mg/L and was 4.13%. Sal-P was significantly positively correlated with the silt content (r\u0026thinsp;=\u0026thinsp;0.61*) and pore space (r\u0026thinsp;=\u0026thinsp;0.55*). It was significantly negatively correlated with sand (r = -0.41* ), clay (r = -0.32*), bulk density (r = -0.33* ), solid space (r = -0.53*), water holding capacity (r = -0.39* ), specific gravity (r = -0.41* ), and pH (r = -0.47* ) and could be carried out by the transformation of loosely bound surface-adsorbed P into a less soluble form of P(Sacheti and Saxena \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1973\u003c/span\u003e). Similar results were observed for clayey soils. exchangeable magnesium (r = -0.37*) and free iron oxide (r = -0.528*). There was a significant positive correlation between Ca-P (r\u0026thinsp;=\u0026thinsp;0.56*) and inorganic P (r\u0026thinsp;=\u0026thinsp;0.60*) due to strong weathering and a negative correlation between Fe-P (r = -0.42*) and organic P (r = -0.63*). This difference might be due to the neutral pH. Saloid P is loosely or weakly correlated with Fe-P, Red-P and Organic P, demonstrating that a profound correlation with the distribution of Saloid-P was detected, similar to the findings of Vishwanath and Doddamani 1991.\u003c/p\u003e \u003cp\u003eTo further understand the dynamics of phosphorus distribution in soil, it is important to consider the various phosphorus fractions and their relationships with soil characteristics. The negative correlation between Fe-P and organic P may be influenced by the neutral pH of the soil. In addition, the relationships between saloid-P and other phosphorus fractions, such as Fe-P and Red-P, indicate complex interactions and distributions of phosphorus in the soil. Interestingly, similar findings were reported by Vishwanath and Doddamani, highlighting the significance of saloid-P for soil fertility.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Aluminium-P (Al-P)\u003c/h2\u003e \u003cp\u003eThe Al-P content in these soil profiles ranged from 1.61 to 1.83 mg/L, and the mean value of Al-P was 1.35 mg/L. Al-P comprised 2.15% of the total P, and a very low content of total P in the soils is an indication of strong weathering and well-drained humid tropics (Sarkar et al.2014). Among the fractions, Al-P was significantly positively correlated with Occl-P (r\u0026thinsp;=\u0026thinsp;0.43*), Ca-P (r\u0026thinsp;=\u0026thinsp;0.60*), mineral or inorganic P (r\u0026thinsp;=\u0026thinsp;0.67*), and total P (r\u0026thinsp;=\u0026thinsp;0.47*) and negatively correlated with organic P (r = -0.11*), while Al-P was positively correlated with pore space (r\u0026thinsp;=\u0026thinsp;0.33*), aluminium oxide (r\u0026thinsp;=\u0026thinsp;0.89*), and total sesquioxide (r\u0026thinsp;=\u0026thinsp;0.89*). It was significantly negatively correlated with the clay content (r = -0.16*), solid space (r = -0.30*), pH (r = -0.40*), and exchangeable Mg (r = -0.21*).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Iron-P (Fe-P)\u003c/h2\u003e \u003cp\u003eThe Fe-P content of the soil is one of the most important P fractions influencing its availability in the soil. among inorganic fractions. Fe-bound P was the second largest pool. This was expected because the soils were dominated by Fe sesquioxides (Arbind et al., 2020). The Fe-P in the soils ranged from 5.61 to 7.29 mg/L, with a mean value of 6.53 mg/L. Fe-P comprised 10.44% of the total P. A significant positive correlation was observed between Fe-P and the sand percentage (r\u0026thinsp;=\u0026thinsp;0.64*), water-holding capacity (r\u0026thinsp;=\u0026thinsp;0.86*), and free iron oxide (r\u0026thinsp;=\u0026thinsp;0.56*). It was significantly negatively correlated with silt (r = -0.65*) and particle density (r = -0.42*), and Fe-P was positively correlated with Occl-P (r\u0026thinsp;=\u0026thinsp;0.62*), Red-P (r\u0026thinsp;=\u0026thinsp;0.64*), and total P (r\u0026thinsp;=\u0026thinsp;0.54*); similar findings were found with Prahalad et al. 2014 and Organic P (r\u0026thinsp;=\u0026thinsp;0.29*) due to mineralization and an increase in biological activity in soil. Similar findings were found by Sacheti and Saxsena (1973), Watham et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), Arbind et al. (2020) and Bhavsar et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Occluded-P (Occl-P)\u003c/h2\u003e \u003cp\u003eThe Occl-P in the soil P fractions ranged a medium level and it varies from 1.54 to 3.89 mg/L, with a mean value of 2.55 mg/Land it representing 3.98% of the Total-P. Significant positive correlations between Occl-P and sand (r\u0026thinsp;=\u0026thinsp;0.35*), water holding capacity (r\u0026thinsp;=\u0026thinsp;0.54*), available phosphorus (r\u0026thinsp;=\u0026thinsp;0.76*), available potassium (r\u0026thinsp;=\u0026thinsp;0.42*), free iron oxide (r\u0026thinsp;=\u0026thinsp;0.49*), aluminum oxide (r\u0026thinsp;=\u0026thinsp;0.51*), and Total Sesquioxide (r\u0026thinsp;=\u0026thinsp;0.53*) were observed and were negatively correlated with silt (r = -0. 35*), Occl-P was positively correlated with total P (r\u0026thinsp;=\u0026thinsp;0.80*) and inorganic P (r\u0026thinsp;=\u0026thinsp;0.55*). Ca-P (r\u0026thinsp;=\u0026thinsp;0.42*) and Organic P (r\u0026thinsp;=\u0026thinsp;0.31*). Similar findings have been reported by Bhavsar et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Arbind et al. (2020).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Red-P\u003c/h2\u003e \u003cp\u003eThe soluble P reductant in the soil is adsorbed by the oxides or hydroxides of Fe and Al. The Red-P in the studied soils ranged from 1.6 to 2.1 mg/L, with a mean value of 1.86 mg/L occupying 3.0% of the total P. Red-P was significantly positively correlated with the water holding capacity (r\u0026thinsp;=\u0026thinsp;0.56) and EC (r\u0026thinsp;=\u0026thinsp;0.45). It was significantly negatively correlated with silt content (r = -0.21*), particle density (r = -0.33*), and pore space (r = -0.31*). Red-P was significantly positively correlated with inorganic P (r\u0026thinsp;=\u0026thinsp;0.27*); similar findings were found by Bhavsar et al.2018, Prasad et al. 1986, and Arbind et al.2020. This fraction was the second least abundant fraction. A low Red-P value was observed in soils with a relatively high pH and sand content. This difference might be due to the increase in the iron- and aluminium-bound P contents and in the content of calcium-bound P, similar to the findings of (Viswanatha and Doddamani 1991, Sharma and Tripathi \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1992\u003c/span\u003e and Trivedi et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.8 Calcium-P (Ca-P)\u003c/h2\u003e \u003cp\u003eThe amount of Ca-P in the soils ranged from 15 to 25 mg/L, with a mean value of 19.72, accounting for 31.57% of the total P and resulting in the highest fraction among all the fractions. This may be because of the average range of Ca2\u0026thinsp;+\u0026thinsp;ions in the soil. Ca-P was significantly positively correlated with pore space (r\u0026thinsp;=\u0026thinsp;0.39*), organic carbon (r\u0026thinsp;=\u0026thinsp;0.55*), available nitrogen (r\u0026thinsp;=\u0026thinsp;0.55*), available potassium (r\u0026thinsp;=\u0026thinsp;0.35*), aluminum oxide (r\u0026thinsp;=\u0026thinsp;0.60*), and total sesquioxide (r\u0026thinsp;=\u0026thinsp;59*). Ca-P was significantly negatively correlated with clay (r = -0.32*), solid space (r = -0.403*), pH (r = -0.226*), EC (r = -0.232*), exchangeable magnesium (r = -0.388*), and free iron oxide (r = -0.22*); significantly positively correlated with mineral P (r\u0026thinsp;=\u0026thinsp;0.96*); and negatively correlated with organic P (r = -0.53*), similar to the findings of Bhavsar et al.2018 and Arbind et al. (2020). Calcium-bound P is typically the dominant inorganic soil P fraction. The close association between Ca-P and inorganic P was due to the dominance of Ca-P in soils (Bhavsar et al.2018), while the pH varied from 7.2 to 7.4. Within this range, calcium-bound P is often the dominant inorganic soil P fraction, and the calcareous character of most of these soils may be attributed to the large proportion of calcium-bound P.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.9 Inorganic-P\u003c/h2\u003e \u003cp\u003eInorganic P exists as an orthophosphoric acid salt. In general, inorganic P is the predominant form of soil P, constituting 20\u0026ndash;80% of the total P in the surface layer (Tomar \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Inorganic P included all the fractions of P, that is, S-P, Al-P, Fe-P, Occl-P, Red-P, and Ca-P; the values ranged from 27 to 44 mg/L; and there was a significant decrease in the levels of P from the surface layer to the subsurface layers in all the profiles. Inorganic P was significantly positively correlated with EC (r\u0026thinsp;=\u0026thinsp;0.491*), available nitrogen (r\u0026thinsp;=\u0026thinsp;0.48*), available phosphorus (r\u0026thinsp;=\u0026thinsp;0.33*), available potassium (r\u0026thinsp;=\u0026thinsp;0.35*), aluminum oxide (r\u0026thinsp;=\u0026thinsp;0.67*), and total sesquioxides (r\u0026thinsp;=\u0026thinsp;0.66*). It was significantly negatively correlated with the clay content (r = -0.30*), solid space (r = -0.35*), and pH (r = -0.32*). Among the fractions, inorganic or mineral P was significantly and positively correlated with saloid P (r\u0026thinsp;=\u0026thinsp;0.60*), Al-P (r\u0026thinsp;=\u0026thinsp;0.67*), Occl-P (r\u0026thinsp;=\u0026thinsp;0.55*), and Ca-P (r\u0026thinsp;=\u0026thinsp;0.96*), as they are the major contributors to the inorganic form of P.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.10 Organic-P\u003c/h2\u003e \u003cp\u003eThe total organic P concentrations ranged from 25 to 28 mg/L, and it has been shown that there was a significant decrease in and irregular arrangement of organic P in a few of the profiles. This arrangement, compared to that of inorganic P, is due to the availability of Fe and Al oxides, which are available in inorganic P (Arbind et al.2020). Organic P was significantly and positively correlated with clay content (r\u0026thinsp;=\u0026thinsp;0.42*), bulk density (r\u0026thinsp;=\u0026thinsp;0.52*), solid space (r\u0026thinsp;=\u0026thinsp;0.41*), available phosphorus (r\u0026thinsp;=\u0026thinsp;0.66*), and free iron oxide (r\u0026thinsp;=\u0026thinsp;0.49*). It was significantly negatively correlated with silt (r = -0.45*) and pore space (r = -0.410*), showing that more soils containing more silt had less organic P; similar results were found by Arbind et al. (2020) and available nitrogen (r = -0.34*). Organic P was positively correlated with Occl-P (r\u0026thinsp;=\u0026thinsp;0.31*) and Total-P (r\u0026thinsp;=\u0026thinsp;0.62*) The association of organic-P and Total-P highly correlated was reported by (Dongle 1993). Organic P was negatively correlated with saloid P (r = -0.63*), Ca-P (r = -0.53*), and inorganic P (r = -0.46*).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.11 Total-P\u003c/h2\u003e \u003cp\u003eThe average total P values ranged from 57 to 72 mg/L. A significant decrease in the P concentration from the surface layer to the subsurface layers was observed in all the profiles, possibly due to the continuous application of manures and P fertilizers to the top layers; similar results were found by Arbind et al.2020 and Dongale \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1993\u003c/span\u003e. Total P was significantly positively correlated with bulk density (r\u0026thinsp;=\u0026thinsp;0.47*), water-holding capacity (r\u0026thinsp;=\u0026thinsp;0.57*), available phosphorus (r\u0026thinsp;=\u0026thinsp;0.97*), available potassium (r\u0026thinsp;=\u0026thinsp;0.39*), and free iron oxide (r\u0026thinsp;=\u0026thinsp;0.38*). Aluminum oxide (r\u0026thinsp;=\u0026thinsp;0.47*) and total oxides (r\u0026thinsp;=\u0026thinsp;0.48*) were observed. It was significantly negatively correlated with silt (r = -0.29*) and exchangeable Mg (r = -0.23*). Total P was positively correlated with Al-P (r\u0026thinsp;=\u0026thinsp;0.478*), Fe-P (r\u0026thinsp;=\u0026thinsp;0.546*), Occl-P (r\u0026thinsp;=\u0026thinsp;0.806*), Ca-P (r\u0026thinsp;=\u0026thinsp;0.300*), and the mineral P (r\u0026thinsp;=\u0026thinsp;0.399*).\u003c/p\u003e \u003cp\u003eAccording to the results for soils in Prayagraj, which are neutral to alkaline, all the soil samples were under permissible limits, with the nonsaline condition of electrical conductivity being suitable for crops. Of the soil samples, 58.3% had medium-high organic carbon contents due to low and high temperatures and less decomposition of organic matter in the soil; more than 50% of the samples had low and medium ranges of nitrogen and phosphorus and a high range of potassium; more than 52% of the samples had a high range of exchangeable calcium ions; and 70% of the soil samples had low levels of magnesium. The total sesquioxide hydroxides of iron and aluminium ranged from low to medium for free iron oxide, and the overall saloid-P values ranged from an average of 2.53 mg/L (4.13%), whereas the average Al-P of the samples ranged from 1.35 mg/L (2.15%), the lowest among all the fractions. The Fe-P values ranged from second highest at 6.53 mg/L (10.44%). The Occl-P values ranged from 2.55 mg/L (3.9%), which was within a medium range compared to all the other fractions. Red-P ranged from 1.86 mg/L (3%). The Ca-P values ranged from 19.72 mg/L (31.27%), with the highest values among all the fractions. The total P concentration ranged from 34.58 mg/L, while the inorganic P concentration ranged from 62.84 mg/L, while the total organic P concentration ranged from 28.24 mg/L (44.70%).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eVarious phosphorus fractions (S-P, Al-P, Fe-P, Red-P, Occl-P, and Ca-P) contributed to the available and total P. Ca-P was found to be the most dominant in the inceptisols, and the content of the fraction sequence was Ca-P\u0026thinsp;\u0026gt;\u0026thinsp;Fe-P\u0026thinsp;\u0026gt;\u0026thinsp;S-P\u0026thinsp;\u0026gt;\u0026thinsp;Occl-P\u0026thinsp;\u0026gt;\u0026thinsp;Red-P\u0026thinsp;\u0026gt;\u0026thinsp;Al-P. Overall, the results indicate that organic P, available P, inorganic P, total P, and Occl-p are the main contributors to the decrease in available P with increased soil depth. Similar results were observed for the ultisols, for which the available P concentration was low, and the quantity and frequency of fertilizer additions and crop growth periods influenced the P fractions in the soil. The soil analysis results were interpreted using the literature, which helps farmers improve soil health and use proper fertilizers that supply deficient nutrients to crops. Further research is needed to develop bio interventions to convert mobile P into plant-available P, reduce the dosage of P fertilizer, and improve the application of organic P in the soil.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003ch2\u003eConflicts of interest: \u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this study.\u003c/p\u003e\n\u003ch2\u003eEthical Approval: \u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflicts of interest. Ethical approval for this study was not required by our institute.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.S. Desigined and prepared the experiements and wrote the manuscriptA.H. Approved the study and Supervision T.T. and A.A.D. guidance throughout the study and supervision A.B. and R.S.K. prepared datasets and carriedout the experiements\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArbind Kumar Gupta, Luxmi Kant Tripathi and Prasanta Kumar Patra (2022). Distribution of phosphorus fractions in different soil orders of the Indo-Gangetic Plains in India. \u003cem\u003eAnnals of Plant and Soil Research\u003c/em\u003e 24(2):221-225.\u003c/li\u003e\n\u003cli\u003eArbind Kumar Gupta, Prashanta Kumar Patra and Luxmi Kant Tripathi (2020). Distribution and Classification of Phosphorus Fractions and their Relationships with Soil Properties in Ultisols of Meghalaya. \u003cem\u003eJournal of the Indian Society of Soil Science\u003c/em\u003e 68, (4), 400-407.\u003c/li\u003e\n\u003cli\u003eBhavsar. M.S., Ghagare, R.B. and Shinde, S.N. 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L., and Nelson, W. L. (2004) Soil Fertility and Fertilizers: An Introduction to Nutrient Management, Sixth Edition., Pearson EdU. Pvt. Ltd., New Delhi.\u003c/li\u003e\n\u003cli\u003eHesse, R.R., (1971), \u003cem\u003eTextbook of soil Chemical Analysis\u003c/em\u003e. John Murray and Co., London.\u003c/li\u003e\n\u003cli\u003eJackson M.L. \u003cem\u003eSoil Chemical Analysis\u003c/em\u003e (1973) Prentice Hall of India (Pvt.) Ltd., New Delhi.\u003c/li\u003e\n\u003cli\u003eJakubus, M. (2015). Phosphorus forms in some grassland soils in Wielkopolska region: characterization and availability for plants. https://doi.org/10.17306/j.npt.2015.2.16\u003c/li\u003e\n\u003cli\u003eKaistha B.P., Sharma P.C, Dubey Y.P.. (1999) Effect of manure and Phosphorus on the inorganic Phosphorus fractions in mountain soil of Himalayas, \u003cem\u003eCrop Research\u003c/em\u003e 18, 206-210.\u003c/li\u003e\n\u003cli\u003eMuthuval, P., Udaysoorian, C., Natesan, R., and Ramaswami, P.P. (1992). 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(1966) \u003cem\u003eSoil and Plant analysis\u003c/em\u003e. IV edition. University of Acelcide Adeitada, Australia, 135-200.\u003c/li\u003e\n\u003cli\u003ePrahalad devra, S.R. Yadav and I.J. Gulati (2014). Distribution of different phosphorus fractions and their relationships with soil properties in the western plain Rajasthan. \u003cem\u003eAgropedology\u003c/em\u003e, 24 (01), 20-28.\u003c/li\u003e\n\u003cli\u003ePrasad, S. N., Singh, S. N., Singh, R. C. (1966). Correlation between the forms of P and soil properties. \u003cem\u003eJournal of Applied Biology\u003c/em\u003e, 4, 55-58.\u003c/li\u003e\n\u003cli\u003eSacheti, A.K., and Saxena, S.N. (1973). Relationship between soil characteristics and various inorganic phosphate fractions of soils in Rajasthan. \u003cem\u003eJournal of the Indian Society of Soil Science\u003c/em\u003e 21, 143-149.\u003c/li\u003e\n\u003cli\u003eSaleem, A., Irshad, M., Hassan, A., Mahmood, Q., \u0026amp; Eneji, A E. (2017, September 1). Extractability and bioavailability of phosphorus in soils amended with poultry manure composted with crop wastes. https://doi.org/10.4067/s0718-95162017000300005\u003c/li\u003e\n\u003cli\u003eShaheen, S M., Tsadilas, C., \u0026amp; Stamatiadis, S. (2007). Inorganic phosphorus forms in some entisols and aridisols of Egypt. https://doi.org/10.1016/j.geoderma.2007.08.013\u003c/li\u003e\n\u003cli\u003eSharma, P.K., and Tripathi, B.R. (1992). Fractions of phosphorus from acid hill soils of northwest India. \u003cem\u003eJournal of the Indian Society of Soil Science\u003c/em\u003e 40, 59-65\u003c/li\u003e\n\u003cli\u003eSheshu, M., Hasan, a., Thomas, T., David, A A., Barthwal, A., \u0026amp; Khatana, R N S. (2022) Nutrient indexing of olsen\u0026rsquo;s phosphorous with relationship between inorganic forms of phosphorous in the alluvial soils. https://doi.org/10.53550/ajmbes.2022.v24i03.010\u003c/li\u003e\n\u003cli\u003eSubbaiah, B. V., Asija, G. L. (1956) A rapid procedure for the estimation of available nitrogen in soils. \u003cem\u003eCurrent Science\u003c/em\u003e, 25, 259-260.\u003c/li\u003e\n\u003cli\u003eTomar, N.K. (2003). Effect of soil properties on the kinetics of P in acidic soil. \u003cem\u003eJournal of the Indian Society of Soil Science\u003c/em\u003e 51, 508-511.\u003c/li\u003e\n\u003cli\u003eTometin, L., Chouti, W K., Chitou, N E., Dakpo, M O., Dannon, M., Suanon, F., Yalo, N., Mama, D., \u0026amp; Bawa, L M. (2023, February 6). Phosphorus Fractionation in Sediment and Agricultural Soils Surrounding Lake Toho in the Rainy Season. https://doi.org/10.9734/ijecc/2023/v13i11617\u003c/li\u003e\n\u003cli\u003eTrivedi, S. K., and Tomar, R. A. S., Tomar, P. S., Gupta, Naresh. (2010). Vertical distribution of different forms of phosphorus in alluvial soils of the grid region of Madhya Pradesh. \u003cem\u003eJournal of the Indian Society of Soil Science\u003c/em\u003e 58, 86-90.\u003c/li\u003e\n\u003cli\u003eViswanath \u0026amp; Doddamani (1991) Distribution of fractions in some varieties \u003cem\u003eJournal of the Indian Society of Soil Science\u003c/em\u003e 39, 441-445.\u003c/li\u003e\n\u003cli\u003eWalkley, A and Black, C.A. (1934) An examination of rapid method for determination soil organic matter, and proposal for modification of the chromic acid titration method, \u003cem\u003eSoil Science\u003c/em\u003e 37, 29-38.\u003c/li\u003e\n\u003cli\u003eWatham, L., Athokpam, H.S., Chongtham, N., Devi, N.K., Singh, N.B., Singh, N.G., Sharma, P.T., and Heisnam, P. (2018) Phosphorus status in the soils of Imphal West District, Manipur, India. \u003cem\u003eInternational Journal of Current Microbiology and Applied Science\u003c/em\u003e 7, 3871-3877.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Phosphorus fractions, Yamuna region, P biogeochemistry, Organic phosphorus","lastPublishedDoi":"10.21203/rs.3.rs-4270803/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4270803/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo expand the research on soil phosphorus. Little is known about the concentrations of phosphorus fractions in the phosphorus-deficient area of the Yamuna River bank in Prayagraj. To overcome this gap, we suggest the exploitation of soil phosphorus fractions from soil samples in the study area.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analysed 24 soil samples from four different depths at six different sites in agricultural fields around the Yamuna River. The samples were analysed, and different phosphorus fractions were sequentially extracted. UV spectrometry was subsequently used to analyse the individual P fractions.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe found that P-deficient soils were neutral in pH and low in salinity. Among the P fractions, calcium-P was the most predominant, followed by Fe-P, S-P, Occl-P, Red-P, and Al-P. Overall, the available P, organic P, and total P decreased with increasing depth, whereas calcium P was significantly positively correlated with organic carbon (r\u0026thinsp;=\u0026thinsp;0.55*) and available nitrogen (r\u0026thinsp;=\u0026thinsp;0.55*) and significantly negatively correlated with clay (r = -0.32*), pH (r = -0.22*), and EC (r = -0.23*). However, the occurrence of P is a major contributing factor to the availability of P in soils.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur regression equations showed that soil pH was the main soil property influencing the different P fractions. Applying organic P fertilizers can improve the quantity of P in these soils, and if enhanced analytical techniques are applied to soil samples, it is possible to gain more detailed insights into the dynamics of phosphorus fractions.\u003c/p\u003e","manuscriptTitle":"Distribution of phosphorus fractions and their relationships with physiochemical properties in the Agricultural soils of the Yamuna River region","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-25 19:03:03","doi":"10.21203/rs.3.rs-4270803/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c9cc7bde-6377-48e7-be5e-ea5a4414cb45","owner":[],"postedDate":"April 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-05T08:30:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-25 19:03:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4270803","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4270803","identity":"rs-4270803","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}