Spatial variability assessment in Central Farm Soils of Horticultural College and Research Institute, Periyakulam, Tamil Nadu using GIS techniques

A total number of 201 surface soil samples were collected encompassing the fields of Central Farm of Horticultural College and Research Institute, Periyakulam, Tamil Nadu. The GPS data (Latitude oN and Longitude oE) were recorded for each sampling site by using GPS-Garmin eTrex Vista HCX model. Field maps were collected and field number wise digitization was done. Soil samples were processed and anlaysed for soil physic-chemical and fertility parameters. Results indicated that soil samples were neutral to alkaline in reaction, non saline, and slightly calcareous to non calcareous in nature. Soil fertility groupings under percent category indicated that the soils were medium in soil organic carbon, low in available nitrogen, medium to high in available phosphorus, medium to high in available potassium, and low in available sulphur. With respect to DTPA extractable micronutrients, Fe, Zn, Mn and Cu were found to dominate by low to medium, low, high, medium to high categories, respectively. HWS-Boron was also recorded under the high category. The nutrient index values of the samples indicated a high status for organic carbon, available P and K, while medium for available N and adequate for available sulphur. With respect to micro nutrients, nutrient index values indicated that adequate for DTPA-Zn and very high for DTPA-Fe, Mn, Cu, and HWS-B. Thematic maps generated on the individual parameters depicted the spatial variability of parameters in the Central Farm of Horticultural College and Research Institute, Periyakulam. In the identified areas of poor fertility status, nutrient deficiency has to be eliminated by the application of organic and /or inorganic sources to maintain sustainable soil fertility status. Soil test-based fertilizer recommendations and micronutrients are to be followed to mitigate nutrient deficiencies and achieve sustained crop production and soil fertility.


INTRODUCTION
Soil is the medium for plant growth and hence, in-depth insight on soil is a prerequisite for planning, monitoring, and developing strategies viz., optimum land, water, fertilizer use, and management aiming at high returns. The regional varia tion in the yield of crops is primarily due to natural factors like soil and climate. For sustained production of crops and soil health, maintenance of nutrient and moisture availability have to be maintained and managed carefully. A continuous decline in soil fertility endangers the fertility and productivity of the soil. Cropping patterns, leaching, erosion, etc., lead to the loss of fertile soil and nutrients every year. Continued cropping patterns without restoring nutrients in the soil will reduce its natural fertility and crop yields will decline. Soil testing provides the nutrient status of soils and forms the basis for the fertilizer prescription for maximizing the crop yield.
Advanced technologies like Global Positioning System (GPS) and Geographic Information System (GIS) support in collecting georeferenced soil samples and generating spatial variability maps of nutrients (Sharma, 2004). Soil fertility mapping is possible by the integration of GIS and GPS. These techniques help in taking decisions to improve agricultural approaches towards balanced nutrition. Geographic information system has emerged as a powerful tool for spatial analysis of natural resources and database management. It is an efficient and versatile tool to automate soil data transformation into soil information (Kasthuri Thilagam and Sivasamy, 2013). In the present study, an attempt has been made to evaluate the soil fertility status and their spatial variability in the Central farm of Horticultural College and Research Institute, Periyakulam, Tamil Nadu. An appraisal of the potentialities and constraints of the farm soils is essential in the context of improving the productivity and increasing the economic returns of the farm without deteriorating the natural resources.

Collection of soil samples
A total of 201 surface soil samples were collected from the fields of Central Farm of Horticultural College and Research Institute, Periyakulam, Tamil Nadu. The geo-coordinates (Latitude ºN and Longitude ºE) were recorded for each sampling site using GPS (Figure 1). Soil samples were air-dried, sieved through a 2 mm sieve, labeled, and stored. For the estimation of organic carbon, processed soil samples were sieved with a 0.5 mm sieve. The soil samples were analyzed for pH and EC (Jackson, 1973), organic carbon (Walkley and Black, 1934), available nitrogen (Subbiah and Asija, 1956), available phosphorus (Olsen et al.,1954), available potassium (Stanford and English, 1949), available sulphur (Williams and Steinbergs, 1959), available Zn, Fe, Cu, and Mn (Lindsay and Norvell, 1978) and available Boron (Berger and Truog, 1944).
The analytical results of each soil sample were categorized as low, medium, and high for organic carbon (OC) and macronutrients; as deficient, moderate, and sufficient based on the critical limits for available sulphur and micronutrients as followed in Tamil Nadu (Table 1).

Nutrient index values and fertility rating
Nutrient index value was calculated from the proportion of soils under low, medium, and high available nutrient categories, as represented by Where, NIV = Nutrient Index Value P L, P M and P H are the percentage of soil samples falling in the category of low, medium, and high nutrient status and given weightage of one, two, and three, respectively (Ramamoorthy and Bajaj, 1969).

Generation of thematic soil fertility maps
Database on soil available nutrient status was generated in Microsoft Excel and the soil fertility maps were prepared at the Department of Remote sensing and GIS, TNAU, Coimbatore by using Arc-GIS software (version 10.6). The thematic maps on available nutrient status were generated by categorizing the fertility status such as 'Low', 'Medium' and 'High' by showing appropriate legend for soil fertility parameters by krigging geostatistical technique.

Soil Physicochemical Properties
The overall data (201 nos) (Table 2) revealed that the pH of the soil ranged from 6.75 to 8.87 with a mean value of 7.54. The electrical conductivity of the analyzed soil samples varied from 0.01 to 1.05 dSm -1 with a mean value of 0.22 dSm -1 and was found to be non-saline. The free CaCO 3 content in the soil samples ranged from non-calcareous to slightly calcareous in nature (3.65 to 4.23 %) with a mean value of 4.23%. The organic carbon content of the soil samples ranged from 1.15 to 9.94 g kg -1 with a mean of 5.79 g kg -1.

Available nutrient status
The available nutrient status is furnished in Table 2. The available N, P, and K status of the soils ranged from 109 to 252; 10.5 to 38.1 and 160 to 490 kg ha -1 with a mean of 177, 27.4, and 343 kg ha -1, respectively. The available S content of the soil ranged from 2.97 to 23.3 mg kg -1 with a mean of 11.8 mg kg -1 .
The DTPA extractable Fe, Zn, Mn, and Cu content ranged from 1.01 to 12.5; 0.20 to 2.95; 3.98 to 20.8; 0.78 to 8.60 mg kg -1 with a mean of 5.11, 0.81, 11.3 and 3.24 mg kg -1 respectively. The hot water soluble boron content varied from 1.41 to 8.76 mg kg -1 with a mean of 5.09 mg kg -1 . The total number of samples belonging to each category of fertility status for every analyzed parameter were worked out and the results are given in Table 3 micronutrients, 48, 136,17; 187, 10, 4; 0, 1, 200; 23, 33, 145 nos of samples were grouped under the low, medium, and high category for DTPA Fe, Zn, Mn, and Cu respectively. In the case of HWS-B, all the 201 samples fell under the category of high status.

Per cent samples for each fertility group
Per cent category samples for soil physicchemical properties and available nutrients were worked out and the results are given in Table 3 and

Nutrient index values
Nutrient index values for all available nutrient statuses were calculated separately besides organic carbon status (Table 4). Among the major nutrients, nitrogen registered the lowest nutrient index value of 2.01 followed by phosphorus (5.57) and potassium (5.59). Among the micronutrients, the order of nutrient index value was Mn>B>Cu>Fe>Zn. Nutrient index for available N was medium and for, organic carbon, available P, and K, the nutrient index were high. Available sulphur was found to be adequate. Among the micronutrients, DTPA-Fe was classified under the very high category. DTPA-Zn was adequate and while Mn, Zn, and Cu were high. Similar studies were carried out by Sellamuthu et al. (2015), Theresa et al. (2019), and Muthumanickam (2020) for assessing the nutrient index values in Tiruchirapalli District, rice ecosystem of Anaimalai Block, and vegetable grown soils of Horticultural College and Research Institute, Periyakulam respectively. The thematic maps on pH, EC, organic carbon, and available nutrient status were generated by showing appropriate legends for soil fertility parameters (Figures 4-6). Maps were generated and visual differences were clearly depicted the spatial variability of soil fertility parameters in the Central farm of Horticultural College and Research Institute, Periyakulam, Tamil Nadu. Similar studies were carried out by Arunkumar and Paramasivan, (2015) for Veeranam Command Area, Tamil Nadu. Similar thematic maps were created in vegetablegrown soils of Horticultural College and Research Institute, Periyakulam (Muthumanickam,2020). Mapping Soil Fertility and its Spatial Variability in Tiruchirapalli District, Tamil Nadu Using GIS.

CONCLUSION
Soils of Central farm of Horticultural College and Research Institute, Periyakulam were neutral to alkaline in reaction, non-saline, and slightly calcareous to non-calcareous in nature. Soil fertility groupings with per cent sample in each category revealed the dominance of medium in organic carbon, low in available nitrogen, medium to high in available phosphorus, high in available potassium, and low to medium in available sulphur. With respect to soil available micronutrients, the dominance of medium category in DTPA-Fe, low in DTPA-Zn, and high in DTPA-Cu, Mn, and HWS-B were observed. Figure 6. Spatial variability maps for the DTPA-Fe, Zn, Mn and Cu GIS found to be an essential tool in ceating visual images for a better understanding of soilrelated constraints and to generate location specific management strategies for enhancing soil productivity. Continuous application of organic manures or in-situ application of green or green leaf manures is necessary to improve the soil organic matter content and enhance nutrient use efficiency. The deficient nutrients have to be restored through chemical fertilizers and/or organic manures. Soil test-based fertilizer recommendations along with micronutrients is to be followed for sustained crop production and soil fertility.