PREDICTION OF SOIL REACTION (PH) AND SOIL NUTRIENTS USING MULTIVARIATE STATISTICS TECHNIQUES FOR AGRICULTURAL CROP AND SOIL MANAGEMENT

Abstract

The prediction method is to explore application of multivariate data analysis methodologies to classify
and identify important soil nutrients and pH values. The Principal Component Analysis techniques were
used to recommend the higher or lesser amount of loadings in the soil among 470 soil samples from 94
villages in Vellore district. This is the most powerful analytical technique to determine which data is
highly impacted to soil and crop growth. Regression analysis technique was used to factorize the variable
with the importance and relationship between soil variables. Correlation Matrix technique was used to
compare the several variables to correlate with positive or negative signs. The soil testing procedure and
understanding of results showed that soil nutrients and pH level has significant effect on variation in
fertilizer usage, crop selection and high crop yield. PH determination can give indication whether soil is
suitable for the plants to be grown or needs to be adjusted to produce optimum plant growth. Based on
the predictive analysis results, nitrogen and potassium content are found to be naturally high compared
to other soil nutrients of this region and suggested fertilizers required for crop growth. Farmers should
select the crops as per soil types, nutrients level and pH level in order to produce healthy crop yield.