Boundary line approach applied among crop emergence parameters and soil physical properties

Abstract

The boundary line technique has been proposed for interpreting biological data where one variable is a biological response and the other is an independent variable. The objective of this study was to correlate maize and soybean emergence parameters with soil seedbed physical properties using a boundary line approach. The study was performed at the experimental farm belonging to the Universidade Estadual de Ponta Grossa, in the municipality of Ponta Grossa, Paraná State, Brazil. The area has been managed under a no-tillage system for 18 years. The emergence percentage (EP) and emergence rate (ER) were determined for maize and soybean crops. Soil seedbed physical properties were evaluated for both crop species and included soil penetration resistance, volumetric water content, aggregate stability, tensile strength, friability, saturated soil hydraulic conductivity, bulk density, and the least limiting water range. The boundary line approach was applied to pairs of values of plant emergence parameters and soil seedbed physical properties, and then the regression model was adjusted to the boundary points. The boundary line approach indicated that crop emergence was dependent on soil seedbed physical properties. It was possible to determine the optimum values of soil seedbed physical variables for crop emergence. The boundary line approach is a promising and complementary tool to better understand crop emergence responses to soil seedbed physical properties.

Critical levels and sufficiency ranges for leaf nutrient diagnosis by two methods in soybean grown in the Northeast of Brazil

“…Studies using diagnoses generated by the nutrient balance methods (DRIS × CND) have shown that CND is more accurate than DRIS (Parent et al, 2013); and sufficiency ranges by the boundary line method are closer to those by the CND methods (Vizcayno-Soto and Côté, 2004;Blanco-Macías et al, 2010). Studies have reported that the boundary line is a promising tool to understand soil properties and evaluate the nutritional status of agricultural crops (Guedes Filho et al, 2019;Iheshiulo et al, 2019).…”