Assessment of Soil Fertility Status of Panipat District of Haryana

Introduction

The Panipat district is situated in the northern region of Haryana state in northwestern India, encompassing an area of 1,268 square kilometers. It is located approximately 90 kilometers north of Delhi. The district is bordered by Karnal district to the north, Sonipat district to the south, Jind district to the west, and the state of Uttar Pradesh to the east. Panipat district is part of the Indo-Gangetic plain, renowned for its fertile alluvial soil. The topography of the district is predominantly flat, with occasional undulations. The Western Yamuna Canal and its branches serve as the primary sources of irrigation in the district. The climate of Panipat district features hot summers, cold winters, and a brief monsoon. In summer (May-June), temperatures range from 35 to 45 °C, while in winter (December-January), they drop to 4 to 5 °C. The monsoon (July-September) offers relief with occasional heavy rain. Panipat is mainly agricultural, with farming as the primary occupation. Its fertile soil and irrigation make it ideal for crops like wheat, rice, sugarcane, cotton, and vegetables. Modern agricultural practices, including fertilizers and pesticides, sustain soil fertility and boost yields. Organic manures like farmyard manure and compost are also used, especially by small farmers. However, excessive chemical fertilizers and poor soil conservation have caused degradation in some areas. Soil fertility, a key factor in productivity, involves chemical and biological soil qualities (Singh and Singh, 2015) [16] . It denotes the soil's capacity to supply nutrients for crop growth when conditions are favorable. Understanding soil fertility is crucial for recommending appropriate crop nutrients (Bationo et al., 2018) [1] . Soil fertility assessment and mapping are vital for sustainable agriculture and land management. It involves collecting data on soil properties to determine fertility and crop suitability. Soil mapping creates a detailed map of soil types, their properties, and distribution within a region. Fertility assessment involves analyzing soil samples for physical and chemical properties like pH, nutrients, texture, and organic matter. This data creates a fertility map showing soil types and nutrient levels. Fertility mapping informs land-use decisions and crop management, identifying areas with varying nutrients to adjust fertilizers and select suitable crops. It also reveals soil health issues like erosion and nutrient depletion, aiding conservation strategies like cover cropping and rotation. As land is finite, sustaining food production for a growing population will be challenging. Soil fertility is dynamic, involving nutrient cycling and ensuring water and aeration for plant growth. In dry regions, fertility is limited by water scarcity and low organic matter. Soil fertility is crucial for agriculture sustainability (Hag et al., 2021) [7] . Fertility maps provide essential spatial planning data. Creating these maps requires modeling soil properties (Hounkpatin et al., 2022) [8] . Thus, assessing fertility status yields valuable management information. This study evaluates fertility status, characterizes, classifies, and prepares a fertility map of Panipat district.

Materials and Methods

General description of study area

The research was carried out on five blocks of the Panipat district of Haryana state. Bapoli, Israna, Madlauda, Panipat, and Samalkha. The Panipat district is located between 29.2315°N and 29.5667°N latitude and 76.7220°E and 77.2996°E longitude (Fig. 1). The climate of Panipat district is semi-arid, with hot summers and cool winters. It follows a typical North Indian pattern, with extreme temperatures and limited rainfall. Summers start in April and last until June, reaching 45°C. The monsoon season from July to September brings most of the annual 534.7 mm rainfall. Winters begin in December and last until February, with temperatures dropping to 2°C and frequent dense fog. These conditions impact cropping patterns in the district. Predominant crops include wheat, rice, sugarcane, and mustard, suitable for semi-arid climates. Wheat is mainly grown in winter, rice during the monsoon, sugarcane yearround, and mustard primarily in winter.

Collection & preparation of soil samples

For this study, 250 soil samples (0-15 cm depth) were randomly collected from farmers' fields in five blocks of Panipat district. Soil samples were obtained using a posthole auger. The longitude and latitude of all sampling locations were recorded using portable GPS. The locations of all sampling sites from which samples were collected are presented in fig. 2. All samples were brought to the Regional Soil Testing Laboratory, KVK, Karnal, and spread out on plastic sheets separately for air drying. After air drying, soil samples & were crushed with wooden & mortar and pestle and sieved through a 2 mm sieve. The soil samples were processed and stored in cloth or plastic bags in the laboratory with necessary labelling for further analysis.

Analysis of Soil Samples

The physicochemical parameters of the soil were investigated, including soil texture, soil pH, electrical conductivity, soil organic carbon, and available major nutrients (N, P, K, and S).

Soil texture, pH, EC & Organic carbon

Soil texture was analyzed using the feel method. Soil pH was determined by preparing a 1:2 soil: water suspension and stirring intermittently for half an hour. The pH reading was taken using a glass electrode of a digital pH meter after calibrating it with three buffer solutions of pH 4.0, 7.0, and 10.0 (Jackson, 1973) [9] . Subsequently, the suspensions were allowed to settle until a clear supernatant liquid phase was obtained. The EC was determined by dipping the electrode of the EC meter in the clear supernatant liquid (Jackson, 1973). The results were reported in dSm-1 at 25 °C. Soil OC was determined using the wet digestion method (Walkley and Black 1934) [23] . One gram of soil sample was placed in a 500 ml conical flask and oxidized by adding 10 ml of potassium dichromate and 20 ml of sulfuric acid. The contents were swirled and kept for 30 min to complete the reaction. Thereafter, the suspension was diluted by adding 200 ml distilled water along with 0.5 g of sodium fluoride (NaF) and 1 ml of diphenylamine indicator, which gives a violet color. Thereafter, soil OC was measured by titration of excess potassium dichromate against 0.5 N ferrous ammonium sulfate.

Available Soil Nitrogen

Available soil N was determined using the alkaline potassium permanganate method (Subbiah and Asija,1956) [22] . Two grams of soil was placed in a 1 l flask, and 10 ml each of 0.32% KMnO4 and 2.5% NaOH were added. The flask was heated and attached to the distillation assembly, and distilled ammonia was collected in 0.1N H2SO4. Finally, available soil N was determined by titration of excess sulfuric acid against 0.1N NaOH using a methyl red indicator.

Available Soil Phosphorus

Olsen's method was used to determine the available P (Olsen et al., 1954) [13] . Available P in the soil was extracted using 0.5 M sodium bicarbonate (NaHCO3) at pH 8.5 in the presence of Darco-G 60, shaken for approximately 30 min, and then filtered. The phosphorus in the extract was treated with ammonium molybdate solution, forming phosphomolybdate. This compound was then reduced with stannous chloride (SnCl2), creating a blue complex. Finally, the available was determined by measuring the intensity of the blue color with a spectrophotometer at a wavelength of 660 nm.

Available Potassium (K)

Available K was determined by Jackson (1973) [9] approach. Five grams of soil was placed in a 250 ml conical flask, and

International Journal of Agriculture and Nutrition https://www.agriculturejournal.net 25 ml of 1N neutral ammonium acetate was added to it, followed by shaking for 5 min and then filtered using filter paper. Finally, the available K was measured in the extract using a flame photometer.

Available Sulphur (S)

The available sulfur in the soil was determined using the method described by Chensin and Yien (1950) [4] . Five grams of soil was shaken for 30 min in a calcium chloride solution on a mechanical shaker to extract the available sulfur in the soil. Thereafter, turbidity was produced by adding barium chloride. A blue filter was used to detect the turbidity caused by the precipitation of SO4 2-using a spectrophotometer at a wavelength of 420 nm.

Statistical Analysis

Statistical analysis, that is, Pearson Correlation between soil parameters and nutrient contents, was performed using the OPSTAT-CCSHAU, Hisar (Haryana) program (Sheoran et al. 1998) [15] .

Results and Discussion

Surface soil samples (0-15 cm depth) were randomly collected from farmers' fields in various blocks using a

Global Positioning System (GPS) to study the fertility status of the district. The results of this study entitled "Assessment of soil fertility status of Panipat district" are summarized under different headings.

Soil pH and Electrical Conductivity (EC)

The data on soil pH are presented in [6] and Gora (2013) [5] also found similar outcomes in their research on the soils of Haryana. The interaction of applied fertilizer material with soil colloids, which resulted in the retention of basic cations on the soil's exchangeable complex, may have caused the pH shift from neutral to alkaline. Another reason could be the presence of basic parent material, which may be the cause of alkaline soil.

The electrical conductivity of the Bapoli, Samalkha, Panipat, Madlauda, and Israna blocks ranged from 0.09-0.66, 0.21-1. [11] .

Soil Organic Carbon

The data presented in table 2 clearly reveales that the organic carbon content of Bapoli, Samalkha, Panipat, Madlauda and Israna blocks ranged from 0.29-1.08, 0.33-0.96, 0.27-0.74, 0.37-0.93 and 0.38-0.90% with a mean value ranged from 0.60, 0.56, 0.52, 0.61 and 0.60 % respectively. The highest mean value of organic carbon was observed in the Matlauda block (0.61%), whereas the minimum organic carbon was observed in the Panipat block (0.52 %). In individual samples, the maximum value of organic carbon was recorded in the Bapoli block (1.08%), whereas the minimum value was observed in the Panipat block (0.27%). The status of soil OC in the Panipat district is represented by the map in figure 3(b). For ease of understanding, the percent distribution of OC in the low, medium, and high classes was calculated. The data in Table 3 clearly show that in the Bapoli block, 13, 69%, and 18% of the samples fell in the low, medium, and high categories, respectively. The respective values of OC in the other blocks (viz. Samalkha, Panipat, Madlauda, and Israna) were 16, 77, 7; 27, 73, 0; 9, 71, 20; and 6, 83, 11, respectively. The organic carbon status in all blocks ranged from 0.27-1.08. It was found that the majority of soils for organic carbon content were in the medium range. Among the various blocks, Bapoli (69%), Samalkha (77%), Panipat (73%), Madlauda (71%), and Israna (83%) fell in the medium range. Overall, the OC status of 74.6 % of soils was in the medium category, whereas only 14.2 % of soils were categorized under the low category. The fast rate of organic matter breakdown under the hyperthermic temperature regime, resulting in exceptionally high oxidizing conditions, is likely the cause of the low to medium levels of organic carbon in these places (Kameriya, 1995) [10] . In their previous investigations on the soils of Haryana, Singh et al.

(1997) [17] and Gora (2013) [5] also observed similar outcomes. The continuous rice-wheat system may have provided more residues to the soil, which may have caused the medium organic carbon status. Studies showing that the rice-wheat farming system enhances the soil's organic carbon status (Zhang and He, 2004; Benbi and Brar, 2009; Benbi et al., 2012) [2,3,24] provide evidence for this claim.

Available soil nitrogen and available soil phosphorus

The data presented in (2011) [19] .

Available Potassium and Sulphur

The data presented in Table 2 revealed that the available K in all blocks ranged between 67 and 747 kg ha-1. The mean value of available K was lowest in Bapoli block (156), and the highest in Madlauda (277) block. In the remaining blocks, the available K followed the order Smalkha (189), Panipat (221), and Israna (255 kg ha-1). The status of soil available potassium in the Panipat district is represented by the map in figure 3(f). Based on threshold values of potassium it was observed that 18, 72 and 10 % samples of Bapoli block, 5, 77 and 18% samples of Smalkha block, 3, 67 and 30 % samples of Panipat block, 0, 48, and 52 % samples of Madlauda block, 0, 65, and 35 % samples of Israna block were in low, medium, and high range, respectively (Table 3). The available potassium was mostly under medium to high status in the soils of district Panipat. Approximately 66 % of soils in the Panipat district were observed to be in the medium status for available potassium, whereas 28 % of soils were found to be in the high status, followed by 6 % in the low status of available potassium. The medium to high amount of available potassium in soil could be most probably due to its potassium-rich parent material, such as feldspar and illite (Sharma et al., 2012) [14] . Singh and Poonia (1982) [18] also reported that the available potassium in soil was low due to continuous uptake of potassium by field crops as the farmers' field has been intensively cultivated for a long period of time without potassium fertilization. Similar results were observed by Singh et al.

(2011) [19] . Similarly, the available sulfur value of individual sample was minimum in Bapoli Block (9.0) and maximum in Israna Block (530 kg ha-1) (Table 2). The minimum and maximum levels of available S were found in the Bapoli (65.6) and Israna blocks (161 kg ha-1), respectively. The Magnitude of Available S expressed as number of samples in a range followed the order Israna>Madlauda>Smalkha>Panipat>Bapoli, respectively. The status of soil available sulphur in the Panipat district is represented by the map in figure 3 (g). Based on threshold value of sulphur, 8, 17, and 75% samples of Bapoli block, 0, 7, and 93% samples of Smalkha block, 0, 7, and 93 % samples of Panipat block, 0, 0, and 100% samples of Madlauda block, and 0, 8, and 92% samples of Israna block were in low, medium, and high ranges of sulphur, respectively. (Table 3). Nearly 89 % of soils of Panipat district were high in available sulfur status, followed by medium (9 %) and low (2 %), while in each block, the magnitude of samples under high available sulfur was 75, 93, 93,100 and 92 % in Bapoli, Smalkha, Panipat, Madlauda, and Israna blocks, respectively. The higher status of available sulphur in these areas was due to S-rich parent material and the application of zinc sulfate as a common practice for correcting Zn deficiency in rice-wheat cropping systems.

Correlation between soil properties and nutrient content

The Relationship between soil properties and available nutrient status is presented in Table 4. The correlation matrix clearly revealed a positive and significant correlation between soil organic carbon and available nitrogen (r = 0.928), available phosphorus (r = 0.328), and available potassium (r = 0336**). Figure 4 shows the relationship between OC and N, with an R2 value of 0.8621. A significant positive correlation (r=0.081) was found between organic carbon and available potassium. This might be due to the creation of a favorable soil environment with the presence of high organic matter. A positive but non-significant correlation (r=0.042) was observed between organic carbon and available sulfur content. This relationship existed because most of the sulfur is associated with organic matter. The results obtained are in line with those observed by Nor (1981) [12] and Singh and Mishra (2012) [20] .

Conclusion

The soils of Panipat district are predominantly alkaline and non-saline, with textures ranging from sandy loam to clayey loam. Organic carbon content is generally low to medium, with a mean value of 0.58%, and approximately 74.6% of samples falling in the medium category. Available nitrogen status is low across all blocks, likely due to losses from volatilization, runoff, microbial fixation, and denitrification. In contrast, available phosphorus and sulfur levels are high, while available potassium ranges from medium to high, with the highest values observed in Madlauda and Israna blocks. The positive and significant correlations between soil organic carbon and available nitrogen, phosphorus, and potassium indicate the importance of organic matter in nutrient availability. These findings provide a comprehensive baseline for targeted soil fertility management and enhancement strategies tailored to the specific conditions of each block within Panipat district.

References

1. Bationo A, Fening JO, Kwaw A. Assessment of soil fertility status and integrated soil fertility management in Ghana. In: Improving the profitability, sustainability and efficiency of nutrients through site specific fertilizer recommendations in West Africa agroecosystems. 2018. pp. 93-138.
2. Benbi DK, Toor AS, Kumar S. Management of organic amendments in rice-wheat cropping system determines the pool where carbon is sequestered. Plant Soil. 2012;68:25-43.
3. Benbi DK, Brar JS. A 25-year record of carbon sequestration and soil properties in intensive agriculture. Agronomy for Sustainable Development. 2009;29:257-265.
4. Chesnin L, Yien CH. Turbidimetric determination of available sulphates. Proceedings of the Soil Science Society of America. 1950;14:149-151.
5. Gora V. Distribution of potassium and sulphur in soils under rice-wheat and cotton-wheat cropping systems of Haryana [M. Sc Thesis]. Hisar: CCS Haryana Agricultural University; 2013.
6. Gyawali C, Mohammad B, Daljit D, Dev R, Rishi B. Spatial distribution of physico-chemical properties and macronutrients in rice growing soils of Haryana. The Ecoscan. 2016;10:365-370.
7. Hag Husein H, Lucke B, Bäumler R, Sahwan W. A contribution to soil fertility assessment for arid and semi-arid lands. Soil Systems. 2021;5(3):42.
8. Hounkpatin KO, Bossa AY, Yira Y, Igue MA, Sinsin BA. Assessment of the soil fertility status in Benin (West Africa)-Digital soil mapping using machine learning. Geoderma Regional. 2022;28:e00444.
9. Jackson ML. Soil Chemical Analysis. Prentice Hall of India Pvt. Ltd; 1967.
10. Jackson ML. Soil Chemical Analysis. Prentice Hall, New Jersey, USA; 1973.
11. Kameriya PR. Characterization of soils of agro climatic zone of transitional plain of inland drainage (Zone II-A) of Rajasthan. Journal of the Indian Society of Soil Science. 1995;42:100-101.
12. Nazif W, Perveen S, Saleem I. Status of micronutrients in soils of district Bhimber (Azad Jammu and Kashmir). Journal of Agricultural and Biological Science. 2006;1(2):35-40.
13. Nor YM. Sulphur mineralization and adsorption in soils. Plant Soil. 1981;60:451-459.
14. Olsen SR, Cole CV, Watanabe FS, Dean LA. Estimation of available phosphorus in soils by extracting with sodium bicarbonate. Circular of United States Department of Agriculture. 1954;939:1-19.
15. Sharma BD, Sidhu GS, Sarkar D, Kukal SS. Soil organic carbon, phosphorous, and potassium status in rice-wheat soils of different agro-climatic zones in Indo-Gangetic plains of India. Communications in Soil Science and Plant Analysis. 2012;43(10):1449-1467.
16. Sheoran OP, Tonk DS, Kaushik LS, Hasija RC, Pannu RS. Statistical software Package for agricultural research workers. In: Recent Advances in Information theory, Statistics and Computer Application. Hisar: Department of Mathematics and Statistics, CCSHAU; 1998. pp. 139-143.
17. Singh B, Singh Y. Soil fertility: Evaluation and management. In: Soil Science: An Introduction. Journal of the Indian Society of Soil Science. 2015;649-669.
18. Singh CP, Gupta SP, Gupta VK. Distribution of micro and secondary nutrients in ber (Ziziphus mauritiana Lamk.) orchard soil profiles. Haryana Journal of Horticultural Sciences. 1997;26:199-201.
19. Singh M, Poonia SR. A decade of soil research. Department of Soil Science, CCS Haryana Agricultural University, Hisar; 1982.
20. Singh M, Grewal KS, Panwar BS, Narwal RP. GPS and GIS based fertility maps of major nutrients in soils of Haryana. Research Bulletin, Department of Soil Science, CCS Haryana Agricultural University, Hisar; 2011.
21. Singh RP, Mishra SK. Available macronutrients (N, P, K and S) in the soils of Chiraigaon block of district Varanasi (U.P.) in relation to soil characteristics. Indian Journal of Scientific Research. 2012;3(1):97-100.
22. Singh U, Pandey AK, Singh A. Assessment of Soil Fertility of Some Villages of Mahishi Block, Saharsa, Bihar. Journal of Experimental Agriculture International. 2022;44(10):55-60.
23. Subbiah BV, Asija GL. A rapid procedure for the determination of available nitrogen in soil. Current Science. 1956;25:259-260.
24. Walkley AJ, Black CA. Estimation of soil organic carbon by chromic acid titration method. Soil Science. 1934;37:29-38.
25. Zhang M, He Z. Long-term changes in organic carbon and nutrients of an Ultisol under rice cropping in southeast China. Geoderma. 2004;118(3-4):167-179.