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Evaluation of Agricultural Soil Quality in Khandesh Region of Maharashtra, India

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Evaluation of Agricultural Soil Quality in Khandesh Region of Maharashtra, India Nature Environment and Pollution Technology p-ISSN: 0972-6268 Vol. 17 No. 4 pp. 1147-1160 2018 An International Quarterly Scientific Journal e-ISSN: 2395-3454 Original Research Paper Open Access Evaluation of Agricultural Soil Quality in Khandesh Region of Maharashtra, India S. T. Ingle†, S. N. Patil, P. M. Kolhe, N. P. Marathe and N. R. Kachate School of Environmental & Earth Sciences, Kavayitri Bahinabai Chaudhari North Maharashtra University, Jalgaon-425 001, Maharashtra, India †Corresponding author: S. T. Ingle ABSTRACT Nat. Env. & Poll. Tech. Website: www.neptjournal.com Being agronomy as a major profession, soil and water are key resources for the Indian subcontinent. Modern agro practices and anthropogenic human activities are mainly responsible for degradation of Received: 25-09-2017 agricultural soil. The present investigation deals with the cultivated soil quality in the Khandesh region Accepted: 18-12-2017 of Maharashtra state. The study area comprises Jalgaon, Dhule and Nandurbar districts of Khandesh Key Words: region. The soil quality analysis was conducted over three districts of the region. Total 108 soil Khandesh region samples were collected and processed for physicochemical characterization. The results were Soil fertility processed with linear regression with respect to pre-monsoon and post-monsoon, EC-SAR graphs Soil salinity with 95% CI and PI, ESP-SAR model, Bland-Altman plot and ternary diagrams. The statistical tools viz. Statistical analysis one variable statistics, a coefficient of correlation and other ratios were applied for the data analysis. The result shows, calcium, sodium and potassium concentrations are under the prescribed limit. However, magnesium concentration is between 836.77 and 1762.63 mg/kg, which is high as compared to other exchangeable cations. Finally, the results show unbalancing of soil minerals with higher salinity in the area. Regular monitoring and remediation will help to maintain soil quality of the area in the near future. INTRODUCTION discussed soil quality as well as soil productivity of Khandesh region, which comprises Jalgaon, Dhule and It is well known that from beginning, India has been an Nandurbar districts. agronomical country, means Indian economy is fully de- pendent on agriculture. The major crops sown in Khandesh STUDY AREA region are such as cereals (e.g. wheat, sorghum, rice, maize Khandesh region has been selected for the study, including and bajra), pulses (e.g. tur, mung and udid), fruits (e.g. ba- three districts; these are Jalgaon, Dhule and Nandurbar as nana and sugarcane), cotton, legumes and oilseeds (e.g. shown in Fig. 1. These three districts are situated in the groundnut, sesamum, sunflower, soybean, caster seed, saf- northern part of Maharashtra State in India. The Jalgaon flower, rape and mustard), vegetables and many others. I district is located at 20°-21° N latitude and 74.55°-76.28° past few years crop productivity and quality have dropped E longitude, Dhule district is located at 20.38°-21.61° N by excessive use of inorganic or chemical fertilizers, pesti- latitude and 73.50°-75.11° E longitude, whereas Nandurbar cides and insecticides. The continuous sowing of the same district is located at 21.00°-22.03° N latitude and 73.31°- crop year by year and reduced manure application in farm 74.32° E longitude. All 25 talukas, 15 from Jalgaon, 4 causes soil fertility to also decrease (Singh et al. 2007). from Dhule and 6 from Nandurbar were covered under the Usman & Kundiri (2016) clarified the importance of organic study. fertilizers over chemical fertilizers. GEOLOGY OF THE STUDY AREA Anthropogenic activities are negatively affecting the environmental factors; these effects may be direct or indi- The study area is covered by Deccan trap rocks of creta- rect effects on agricultural soil. From an agricultural point ceous to eocene age and alluvium layer is of quaternary age. of view, an essential environmental factor is a soil which Tapi river flows through Jalgaon, Dhule and Nandurbar dis- produces human and animal needed food (Brady & Weil tricts of Khandesh region. Thick alluvial deposits are present 2007). Hence, there is a requirement to analyse the soil qual- in Raver, Muktainagar, Yawal, Bhusawal, Chopda, Shirpur, ity in the sense of soil productivity at regular intervals to Shahada, Taloda and Navapur talukas. Most part of the study rectify the problems of soil irrigation. It allows us to focus area is covered by Deccan traps except few strips of alluvial to increase the farm yield. In this study, we determined and land on both sides of the Tapi river (Patil et al. 2015). 1148 S. T. Ingle et al. Fig. 1: Location map of study area. MATERIALS AND METHODS cal conductivity were analysed from 1:2 soil extract by us- ing a pH meter and conductivity meter respectively. Avail- Collection of soil samples: Pre and post-monsoon sampling able phosphorus was estimated from the soil by using the was conducted during 2016. The sampling locations were Olsen blue colour method, whereas magnesium concentra- chosen at random basis and determined by using GPS (Glo- tion by EDTA titration method. Sodium, potassium and cal- bal Positioning System) GARMIN (Model No. Montana cium concentrations were estimated by using a flame pho- 650) which are shown in Fig. 2. Total 108 soil samples (0 - tometer. Further, CEC was determined by the ammonium 15 cm) were collected from an irrigated field using a hand acetate method. Organic carbon was analysed by Walkley auger. After sampling, samples were dried, ground and sieved and Black method. to obtain < 2 mm size soil particles (Zare et al. 2014). Ions were converted from mg/L to mg/kg. Ions were also Analytical procedure: The processed soil samples (< 2 mm) converted from mg/kg to meq/kg to meq/100 g or centimole/ were used for analysis of different physicochemical param- kg wherever necessary. The resulted values of each param- eters. The physical parameters determined were colour, tex- eter were interpreted and calculated with irrigation indices ture, porosity, bulk density, moisture content and water using the following formulas of sodium adsorption ratio holding capacity. The chemical parameters analysed in- (SAR), exchange sodium percentage (ESP), electrochemical cluded pH, electrical conductivity, available phosphorus, stability index (ESI), sodium percentage (Na%), magnesium available potassium, sodium, cation exchange capacity percentage (Mg%) and Kelley’s ratio (KR) as follows: (CEC), organic carbon, organic matter, calcium and magne- Sodium Adsorption Ratio: This was calculated by employ- sium by using “Laboratory testing procedure for soil and ing the equation (Raghunath 1987) as: water sample analysis” (2009). Colour and texture of soil were determined on the basis of visual diagnosis, while porosity, bulk density, moisture content and water holding capacity were analysed by manual ...(1) of soil analysis (Margesin 2005) and laboratory manual of the water resources department (2009). Soil pH and electri- (Concentrations are in cmol/kg) Vol. 17, No. 4, 2018 Nature Environment and Pollution Technology EVALUATION OF AGRICULTURAL SOIL QUALITY 1149 Statistical Analysis All the soil samples were analysed using standard chemical methods and the results are presented using one variable sta- tistics. Data used for this study were analysed using graphical and statistical techniques. Firstly, scatter plots of a linear re- lationship of physical and chemical properties of pre and post-monsoon soil samples were prepared. One of the pur- poses of this study is to present regression equations for esti- mating SAR from electrical conductivity for Jalgaon, Dhule and Nandurbar. Initial graphical inspection of the data indi- cated linear relations between electrical conductivity and SAR for the study area. Linear regression is a tool that can be used to determine the relationship between two constituents. The simple linear regression equation can be expressed as: , i = 1,2,……,n ...(7) Fig. 2: Sampling sites of the study area. Where: th Exchangeable sodium percentage: This was calculated em- yi is the i observation of the dependent variable; ploying the equation (Seilsepour et al. 2009) as: m is the slope; th xi is the i observation of the independent variable; b is the y-axis intercept; and ...(2) n is the sample size. The terms ‘m’ and ‘b’ are the parameters that need to be (Concentrations are in cmol/kg) estimated from the data. For this study, a relation was deter- Electrochemical stability index: This was calculated by mined to be statistically significant at the 95% confidence the formula of (Mckenzie 1998) as: level. Prediction intervals were determined to evaluate the uncertainty of the estimated values using the regression ...(3) equation (Helsel & Hirsch 1992). Hence, the 95% predic- tion intervals were also determined from the regression equa- Sodium percentage: This was calculated by the formula of tion for each district. The mean difference confidence inter- (Patil et al. 2016) as: val approach was used to compare the soil ESP values pre- dicted using the soil ESP-SAR model with the soil ESP val- ues measured by the laboratory tests. The Bland-Altman ...(4) approach was also used to plot the agreement between the soil ESP values measured by laboratory tests, and the soil (Concentrations are in cmol/kg) ESP values predicted using the soil ESP-SAR model. The Magnesium percentage: This was calculated by the for- ternary diagram shows interrelation between four cations mula of (Patil et al. 2016) as: viz., Ca, Mg, Na and K by origin 6.1. Lastly, a tabular coef- ficient of correlation between all the soil parameters was made. MS-Excel 2007 and 2013 was used to generate the ...(5) regression equations in this study. (Concentrations are in cmol/kg) RESULTS AND DISCUSSION Kelley’s ratio: This was calculated employing the equation The motive behind examining seasonal variations by com- (Kelley 1963) as: paring this pre and post-monsoon period was to study changes in soil fertility due to use of excess chemical ferti- lizers and changes in precipitation regimes in the study area.
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