Knowledge fusion in the Agro-environmental field: A global index for soil quality in olive groves from quantitative and qualitative variables

This work presents a synthetic, automated global soil quality index (GSQI), applied in the province of Jaen (Spain). This index has been built following a novel methodology, able to integrate quality indicators of both morphological (representing imprecise concepts) as analytical types, against other measures previosly established in the bibliography. This new methodology is based on an advanced data analysis statistical technique, Categorical Principal Component Analysis (CatPCA), applied to non numerical (ordinal or nominal) morphological indicators, properly transformed by means of optimal scaling, quantified and managed along with numerical, analytical indicators. Individual (morphological and analytical) indicators integration into a global index has been locally validated with olive grove soil samples from Atanor Valley (Sierra Magina Natural Park, Spain). This validation process permits the quality comparison between conventional managed olive soils and organic managed ones, the latter clearly showing a better value. This procedure means a great advance in the establishment of a quality improvement for soil degradation due to olive grove conventional management, encouraging more sustainable, soil-protecting, agricultural practices. The discussed methodology can be applied in other highly cultivated geographical areas in order to improve sustainability in agricultural systems.