Determination of the Soil Quality Index by Principal Component Analysis in Cocoa Agroforestry System in the Orinoco Region, Colombia

Abstract

Soil quality index can be determined by assessing the physical, chemical and biological properties of the soil. When large datasets are used, redundant information is obtained very often. Therefore, principal component analysis (PCA) is a multivariate method that allows the reduction of datasets, and in this way, it is possible to determine management objectives. This study was carried out in order to obtain a Soil quality index in an agroforestry system of cocoa (Theobroma cacao L.) and yopo (Anadenanthera peregrine Vell) established in 2012 under Pie de Monte Llanero conditions in the Orinoco Region, Colombia. The properties used to obtain the index were: bulk density, pH in water (1: 1), pH KCl (1: 1), ΔpH, total porosity, drainage porosity, field capacity, available phosphorus, organic matter, clay, silt and sand content, and soil penetration resistance. Using the principal components analysis for this study, the soil quality was: 0.4931, which it can be classified as mean (medium), and this works in function of: BD, O.M, ΔpH, pHh2o and P. Therefore, after determination the sensitive elements of this soil and assess its quality regarding to the AFS applied, it was possible to assume that management strategies and decision making would be addressed towards an appropriate litter production, the improvement of organic matter and management of soil structure.