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Assessment of Soil Fertility Status in Paderu Mandal, Visakhapatnam

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Assessment of Soil Fertility Status in Paderu Mandal, Visakhapatnam The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx Contents lists available at ScienceDirect The Egyptian Journal of Remote Sensing and Space Sciences journal homepage: www.sciencedirect.com Research Paper Assessment of soil fertility status in Paderu Mandal, Visakhapatnam district of Andhra Pradesh through Geospatial techniques ⇑ Ramprasad Naik Desavathu a, , Appala Raju Nadipena b, Jagadeeswara Rao Peddada a a Department of Geo-Engineering, Andhra University, Visakhapatnam 530 003, India b Department of Geography, Andhra University, Visakhapatnam 530 003, India article info abstract Article history: 82 soil samples were collected randomly at different land use/cover locations, which includes agriculture, Received 20 May 2016 forest, built up area, scrubland and plantation at a depth of 0–30 cm, analyzed for soil pH, electrical con- Revised 24 December 2016 ductivity (EC) and presence of nitrogen (N), phosphorous (P) and potassium (K). Inverse Distance Accepted 15 January 2017 Weightage method (IDW) was employed for analyzing the spatial distribution of soil fertility through Available online xxxx geospatial techniques for sustainable agriculture. It is observed that soil pH varies between 4.8 and 7.5; showing nearly 83% of the study area is acidic in nature. The EC varies from 0.04 to 0.87 ds/m with Keywords: a mean of 0.21 ds/m and non saline in condition. Out of 435 km2 of total study area, 99% of area is less in Soil fertility nitrogen followed by potassium (70%) and phosphorus (42%) respectively. Spatial distribution Ó Inverse Distance method 2017 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. Sustainable agriculture This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc- nd/4.0/). 1. Introduction plying capability; moreover fertility of soil is subject to man’s con- trol (Deshmukh, 2012). It may be maintained by scientific crop In any agricultural operations, soil is the utmost importance as rotations, and the application of manure of fertilizers. it is the cradle for all crops and plants. There are non re-renewable The traditional even fertilizing method is not scientifically suit- resources, formed at the rate of 1 in. every 250–1200 years (John able and efficient to apply fertilizer in places with different soil Madeley, 2002). To make agriculturally productive, it may takes nutrients, because soil fertility various between region. Overuse another 3000–12,000 years (Venkata Ramana et al., 2015). This of fertilizers can certainly lead to a waste of fertilizer resources natural resource is finite in nature and also impossible for within and a serious environmental pollution (Clay, 2002; Yang and time span of a human life (Mandal et al., 2009). The top soil having Zhang, 2008). Hence, a comprehensive knowledge of soil fertility an average depth of about 15–30 cm on which plants grow and the provides a better understanding in the current situation and for farming activities flourishes. Now-a-days, it is facing serious prob- identifying soil nutrient distribution and trends (Dafonte et al., lems due to human pressure and utilization incompatible with its 2010). Earlier studies (Isaaks and Srivastava, 1989; Goovaerts, capacity. Hence, it is important to keep healthy and productive soil 1997; Wollenhaypt et al., 1997; Burrough and McDonnell, 1998; to continue our soil to function optimally to increase agriculture Li et al., 2003; Tan et al., 2005; Xu et al., 2013; Liu et al., 2014; production with appropriate soil amendment and crop manage- Behera and Shukla, 2015) proved that geo-statistical analysis ment practices (MacCarthy et al., 2013). In rural areas, the living methods are most useful for obtain the knowledge of characteris- standards of people mainly depend on agriculture, which is often tics, distribution and variability of soil fertility in a timely and determined by the fertility and productivity of soil. Soil fertility accurate manner for precision farming .It is a management practice is one of the primary constraints to agricultural production in for increasing productivity of agriculture for the site-specific man- developing countries like India (Gruhn et al., 2000). It comprises agement (Cahn et al., 1994). These farming operations are vital not only in supply of nutrient, but also indicates their nutrient sup- decision-making process for land use suitability in improving crop productivity (AbdelRahman et al., 2016), where there is a need to ensure efficiency in the management of soil (Mc Cauley et al., 1997). For the purpose of improving soil management and quality Peer review under responsibility of National Authority for Remote Sensing and as well as cost control/benefit results of agricultural producers by Space Sciences. ⇑ adapting to new technologies like Geospatial Technology (Iftikar Corresponding author. et al., 2010; ; Markoski et al., 2015). Using these advance E-mail address: [email protected] (R.N. Desavathu). http://dx.doi.org/10.1016/j.ejrs.2017.01.006 1110-9823/Ó 2017 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Please cite this article in press as: Desavathu, R.N., et al.. Egypt. J. Remote Sensing Space Sci. (2017), http://dx.doi.org/10.1016/j.ejrs.2017.01.006 2 R.N. Desavathu et al. / The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx technologies, so many emeritus scholars and scientists (Weber and 2. Study area Englund, 1992; Gotway et al., 1996; Kravchenko and Bullock, 1999; Robinson and Metternicht, 2006; Sen and Majumdar, 2006; The study area is lies between 18° 180–17° 560 N of latitudes and AbdelRahman et al., 2016; Tunçay et al., 2015) estimated and 82° 320–82° 530 E of longitudes covering an area of 435 km2 (Fig. 1). mapped the soil fertility distribution of un-sampled locations, Nearly, 73% of area is under forest land fallowed by agricultural using Inverse Distance Weightage method (IDW). It is the one of land (20.2%), plantations (2.5%) and built up land covers only the best interpolation method, because of its simplicity, robustness 2.1%.Where soils are mainly red sandy loams and light to medium and used to derive estimates of the soil fertility properties from in texture. They are continuously affected due to severe weather- irregularly spaced samples (Goovaerts, 1997). ing aberration of natural disturbances. The soil erosion is severe Therefore, the objective of this study was to conduct due to its varied and high topography of the land and heavy rainfall geo-statistical analysis for spatial distribution and variability received during the monsoon period and less vegetative cover on (allocation) of observed values and predicted values through IDW its upper parts of the hills. The normal annual rainfall is interpolation techniques, for estimating soil pH, electrical conduc- 1252 mm and mean annual temperature varies from 24 °Cto tivity (EC) and macro nutrients (N, P, K) as well as its status for a 35 °C. May is the hottest month and January is the coolest month. site specific management approach in the agriculture fields of Agriculture is the main source of livelihood of the people living in Paderu Mandal, Visakhapatnam district, Andhrapradesh state, this area and the people practice shifting cultivation on hill slopes. India. Shifting cultivation is locally known as the podu cultivation. Fig. 1. Location map showing soil sample in the study area. Please cite this article in press as: Desavathu, R.N., et al.. Egypt. J. Remote Sensing Space Sci. (2017), http://dx.doi.org/10.1016/j.ejrs.2017.01.006 R.N. Desavathu et al. / The Egyptian Journal of Remote Sensing and Space Sciences xxx (2017) xxx–xxx 3 3. Materials and methods name of the village, coordinates of samples, soil pH, electrical con- ductivity (EC) and available nutrients in respect of nitrogen (N), Firstly, a ‘‘V” shaped cut of 0–6 in. depth at random locations phosphorus (P) and potassium (K). Further the study analyzed was made, the same were geographically referenced using a hand- geo-statistical of the soils shown in Table 2. This table illustrates held GPS in each sampling site (Fig. 1) and one inch of soil on either variables values, including data size, mean, median, minimum side of the pit was scraped and collected in polythene bags. Quar- value, maximum value, lower quartile, upper quartile, range of tering technique was adopted to reduce the size of the sample of data, variance, standard deviation, standard error, coefficient of the required mass. A total of 82 samples were air-dried and ground variance, skenesss and Kurtosis from observed values of soil sam- to pass a 2 mm sieve for the analysis. The analysis of soil samples ples and predicted values from IDW interpolation method. Finally, has been done by using standard methods, i.e. pH of soil (1:2.5), Table 3 and Fig. 2–6 shows the existing soil fertility distribution electrical conductivity (1:2.5), available nitrogen (Alkaline Per- and its status, which can guide the users on the amount of fertiliz- manganate method), available phosphorus (Bray’s No. 1) and avail- ers to be applied for different crops in different areas for more pro- able potassium (Ammonium acetate method). ductivity of the study area. For evaluation of the soil fertility of the study area, the spatial distribution for each parameter attribute was assessed using spa- 4.1. Soil pH tial descriptive statistics (Iqbal et al., 2005). This data has X and Y coordinates in respect of sampling site location and Z field was It is important estimation for soils, determines the magnitude of used for different nutrients of soil fertility.
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