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The aim of this study was to develop regression models on the basis of correlation between yield parameters of soybean (plant height, thousand seed weight, and yield) and some physical and chemical characteristics of soils and to determine applicability of obtained models in estimation of plant yield grown in soils of Carsamba Plain. Soil and plant samples were taken from farmer’s fields in the plain. Regression models between soybean plant height and soil properties of bulk density (BD), electrical conductivity (EC), organic matter (OM), nitrogen (N), potassium (K), wilting point (WP), available water content (AWC) and clay yielded high coefficient determination (R= 0.766) and was significant (p=0.091); Model between thousand seed weight and OM, BD, sand, silt, lime (CaCO 3 ), cation exchange capacity (CEC), N, phosphorus (P), K, sodium (Na), field capacity (FC) and WP, resulted in R=0.782 and was insignificant; and model between seed yield and OM, CEC, N, P, copper (Cu), clay, sand, AWC, and FC yielded R= 0.853 and it was highly significant (p= 0.029). Determination coefficient (R), root mean square error (RMSE), index of agreement (d), model efficiency (ME) were evaluated together to determine the validity of regression models. In general, statistical parameters were within validity limits. The results suggested that the developed regression models can be applied in the estimation of yield parameters in soybean grown in study area.

Soyanın agronomik parametreleri ile toprağın bazı fiziksel ve kimyasal özellikleri arasındaki doğrusal regresyon ilişkilerin belirlenmesi