Soil Nutrients and pH Level Testing Using Multivariate Statistical Techniques for Crop Selection

Abstract

The multivariate data analysis technique is used to determine the highly impacted data in soil and crop growth. The importance and relationship between soil variables were factored by using the regression analysis technique. The correlation matrix technique was used for comparing several variables to correlate positive and negative signs. From the soil testing procedure and understanding of results, it shows that soil nutrients and pH level have a powerful effect on variation in the usage of fertilizers, crop selection, and high crop yield. pH determination can be used to indicate whether the soil is suitable for the plant's growth or in need of adjustment to produce optimum plant growth. Based upon the predictive analysis results, nitrogen and potassium content are naturally high compared to other soil nutrients of this region and suggested fertilizers required for crop growth. To produce healthy crop yield, farmers should select the crops as per soil types, nutrients level, and pH level.