Analysis of Interrelations Structure in Agro-Systems Using the Factor Analysis Technique (FA)

A model is not an exact copy of its original, but only idealised reproduction that simpler, more understandable, accessible and easier, safer effective to work with. In the presented study, we used technique factor analysis (FA). We 44 parameters describe agroecosystem, which proportionally main components study agroecosystem. Based on Malinowsky error analysis, extracted a 6-factor solution. found out Factor 1 [Climate factor] had primary loads in [average temperatures TIII-TIX (0.99) atmospheric precipitation ZIII-ZIV (0.99)] variables. 2 [Chemical geological foundation] was mainly saturated by [SiO2-G (0.92), Al2O3-(0.82), (CaO-G (0.83)] variables secondary were observed soil [SiO2-P (0.61], [CaO-P (0.64], [Al2O3-P (0.32)], [soil skeleton SKEL (0.47)] [granularity GRN (0.39)] 3 [Phytomass production potential [depth profile DSP (0.76)], [quality organic substances Q4/6 (0.63)], [slopeness SL (0.67)] [potential phytomass PROD (0.65)] 4 [Physical-chemical properties [Al2O3, (0.81)], (0.69)] [SiO2 (0.61)] have significant loads. 5 [Erosion water has highest [large-scale arable land ALL (0.70)] loss as result erosion EROS variables, [continuous length plot slope LS (0.53)] variable. 6 [Biochemical load values content [content H (0.69)]. Secondary can be seen [GRN (0.35)], (0.38)] groundwater surface GWS (0.39)]. determined weight coefficients for individual factors with aim quantifying ecological criteria obtained structure. The score F0 determines projections elements selection (it value soil-ecological units—VSEU). Row vectors this matrix represent distribution specific realisation (spatial distribution). re-scaled into seven categories projected them VSEU units. could propose sustainable agroecosystem management based each unit.