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Soil sampling and chemical analysis
Soil testing is a useful tool to assess the nutrient deficiency in soil and fertilizer
recommendations are given for different crops based on soil testing. Application of secondary
and micronutrients in different crops and cropping systems is based on availability of these
nutrients in soil. During this process soil test results are compared with critical vales of these
nutrients in soil to assess their deficiency level.GPS based soil sampling and chemical analysis of
soil samples is a better way since soil testing for secondary and micronutrients is difficult and
expensive and it needs very high technical sophistication.
The first step for performing soil testing is collection of representative soil samples based on soil
types, crops and cropping systems and land holding capacity of the farmers’. Soil samples were
collected from top 15 cm soil depth. More than 2,00,000 soil samples were collected from more
than 500 districts of India. During sampling, the geographical position of the sampling points
was also recorded using a GPS.

Collected soil samples were air dried separately and debris and stones were removed. Grinding
of the samples were carried out (with the help in wooden mortal and pistil) to pass through 2 mm
size sieve. Soil samples were chemically analysed for secondary and micronutrients in
laboratories of different centres of AICRP on Micro and Secondary Nutrients and Pollutant
Elements in Soils and Plants, ICAR-Indian Institute of Soil Science, Bhopal. Soil pH was
measured in 1:2·5 (w/v) soil–water suspensions. The soil organic carbon content was analysed
using the Walkey and Black method (Walkley & Black, 1934). Available zinc, iron, copper and
manganese in soil samples were extracted using diethylene triamine penta-acetic acid extractant
(Lindsay & Norvell, 1978) measured by atomic absorption spectrophotometer. Available sulphur
content was extracted by 0·15% CaCl 2 (Williams & Steinbergs, 1959), and B was extracted by
hot water (Gupta, 1967) and estimated by using spectrophotometer.

Soil mapping
The parameters of descriptive statistics for soil properties and available micronutrients database
generated in the project as well as borrowed from scientists other than AICRP-MSPE were
obtained using SAS software (SAS, 2011). The minimum, maximum and mean value of each
nutrient was estimated for each district. The normality of dataset was verified by Kolmogorov-
Smirnov test (at p < 0.05). Geostatistical analysis of available sulphur and micronutrients was
carried out by ArcGIS 10.4.1. Semivariogram for each soil nutrient was calculated from
averaged values. Best fitted model (such as Spherical, Circular, Exponential, Stable, Gaussian
and K-Bessel etc.).) for each soil parameter was selected through the technique of cross-
validation. Spatial dependence of each nutrient element was assessed by estimating Nugget/Sill
ratio. The soil parameters having Nugget/Sill ratio ≤ 0.25, 0.25 to 0.75 and > 0.75 revealed
strong, moderate and weak spatial dependence respectively. Ordinary kriging (OK) was applied
for interpolation mapping and kriging biasness and accuracy was tested by cross-validation.