MULTIVARIATE ANALYSIS ON CROP RESPONSE TO FERTILIZERS AND SOIL TYPES
Faculty
Department
Year of Publication
Publication Type
Abstract
This study investigates the relationship between crop performance, fertilizer application, and soil types using multivariate statistical analysis. The main objective is to determine how different fertilizer types and the rate of application, in combination with soil characteristics, influence major growth and yield parameters of crops. Data were collected on soil properties
(such as pH, organic matter, nitrogen, phosphorus, potassium, and texture) and crop growth parameters (including germination percentage, plant height, number of leaves, leaf area, biomass, and yield). The canonical correlation analysis was employed to identify patterns and quantify the strength of associations among these variables. The results revealed that soil fertility factors and fertilizer applications significantly influenced crop growth and yield performance, with organic matter and fertilizer rate producing optimal responses. The analysis demonstrates the usefulness of Canonical Correlation Analysis in handling complex agricultural data.
(such as pH, organic matter, nitrogen, phosphorus, potassium, and texture) and crop growth parameters (including germination percentage, plant height, number of leaves, leaf area, biomass, and yield). The canonical correlation analysis was employed to identify patterns and quantify the strength of associations among these variables. The results revealed that soil fertility factors and fertilizer applications significantly influenced crop growth and yield performance, with organic matter and fertilizer rate producing optimal responses. The analysis demonstrates the usefulness of Canonical Correlation Analysis in handling complex agricultural data.
Supervisor(s)
co-supervisor