INTERDEPENDENCE RELATIONSHIPS BETWEEN AGROCHEMICAL INDICES FOR CHARACTERIZATION AN AGRICULTURAL LAND

摘要

This study evaluated the relationship of interdependence between agrochemical indices of the soil in the pedoclimatic conditions of Beregs?u area, Timi? County, Romania. The agrochemical indices that characterize the agricultural soil, were taken into consideration: soil pH, nitric nitrogen (????????3 ?), ammoniacal nitrogen (????????4 ), mineral nitrogen (Nmin), phosphorus (P2O5), potassium (K2O), secondary macro-elements (Ca, Mg, S), sodium (Na), and microelements (Fe, Mn, Cu, Zn, and B). Very high positive correlation was recorded between Nmin and ????????3 ? (r = 0.990), and very high negative correlation was recorded between Mn and pH (r = -0.973). High positive correlations were recorded between Cu and K (r = 0.857), between Cu and Mg (r = 0.834), and between Na and Mg, respectively (r = 0.893); high negative correlation was recorded between Mg and Ca (r = -0.855). Moderate positive correlations were recorded between B and pH (r = 0.783), between Mg and K (r = 0.700), and moderate negative correlations were recorded between Ca and K (r = -0.738), and respectively between Na and Ca (r = -0.703). Based on the values of the coefficients of variation (CV) it was appreciated that pH, and potassium had the highest degree of uniformity in the characterization of the studied soil. High degree of variation was recorded in the case of nitrogen (????????3 ?,????????4 , Nmin), phosphorus, followed by secondary macroelements, and micro-elements. The interdependence relationships between certain agrochemical indices were described by different mathematical model in the form of linear equations (????????3 ?and Nmin, in condition of R2 = 0.981, p 0.001; Mn and pH, in condition of R 2 = 0.947, p 0.001), and in the form of polynomial equations, respectively (Mg and Ca, in condition of R2 = 0.779, p = 0.0107; Cu and K, in condition of R2 = 0.768, p = 0.012; Cu and Mg, in condition of R2 = 0.819, p = 0.0059). PCA explained 98.7808% of variance in relation to the main soil macro-elements, 99.9986% of variance in relation to the secondary soil macro-elements and 99.8228% of variance in relation to the soil microelements, respectively.